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Seminars and Events
Current
CS PhD Dissertation Defense: Computational issues in Long-Term Fairness among Groups of AgentsMonday, December 07, 2009, AbstractFairness within groups is important to a very broad range of problems, from policies for battery-operated soccer robots to distributed traffic control. While no single action may be fair to everyone, it is possible to achieve long-term optimal fairness for everyone through choice of repeated actions I explore the issue of achieving such long-term fairness among multiple agents, and provide a unified view of the problem and solutions to it. The issue of constructing long-term fair policies among multiple agents has not been well studied in the literature. I focus on a particular definition of fairness, called “leximin” fairness, but most of the results apply to other measures as well. After examination of fairness through an infinite series of repeated actions, I extend analysis in several directions. First, I consider how to achieve as fair a result as possible given a finite series of actions, where the length of the series is not precisely known beforehand but rather is chosen from an unknown or stochastic distribution of time horizons. My solution guarantees the beneficiaries the fairest possible long-term results, minus a bounded worst-case loss due to the game ending unexpectively. I show that finding sequences of actions with optimal worst-case loss is NP-hard, and I propose a family of approximation algorithms. Second, I examine stateful domains, where one’s choices have side-effects that influence the effects of actions in the future. I introduce a multi-objective genetic algorithm for finding good tradeoff points between beneficiaries utilities and their worst-case losses. Third, I focus on decision-making processes which have been decentralized in the form of hierarchies. I propose an algorithm based on my stochastic time-horizon solution, and show empirically that an agent hierarchy running that algorithm is able to achieve optimal long-term utilities. Volgenau School Seminar: The Importance of Models in the Design & Analysis of Computer SystemsNovember 19, 2009, AbstractTwo important question need to be addressed when designing a computer system: “What functions will it accomplish?” and “How well will it accomplish these functions?” This talk addresses the second question and shows how quantitative models are essential to dealing with that question. A walk through the speaker’s memory lane will highlight a few examples of how such models have been successfully used in the design and analysis of a wide range of environments including: multiprogrammed mainframes, distributed database systems, client-server systems, supercomputers, parallel computing, mass storage systems, web and e-commerce systems, authentication systems, software systems, grid computing, and service oriented architectures. The talk concludes with a discussion on how quantitative models have been used by the speaker in the design of computer systems that are self-optimizing and self-configuring. Bio:Daniel Menasce is the Senior Associate Dean at The Volgenau School of Information Technology and Engineering and a Professor of Computer Science at George Mason University. He holds a Ph.D. degree in Computer Science from UCLA, is a Fellow of the ACM, and a recipient of the Computer Measurement Group’s 2001 A.A. Michelson Award for lifetime “outstanding contributions to computer metrics.” Menasce published 200 technical papers and was the chief author of seven books some of which have been translated into Korean, Russian, Portuguese, and Spanish. His research has been funded by DARPA, NASA, NSF, National Geospatial-Intelligence Agency (NGA), Virginia's Center for Innovative Technology, and several private companies. Menascé was the recipient of various prizes including, teaching awards, research awards, and best paper awards. His areas of interest include autonomic computing, e-commerce, performance modeling and analysis, and software performance engineering.Volgenau School Seminar: Opportunistic Spectrum Access in Cognitive Radio NetworksNovember 18, 2009, AbstractWith the increasing ubiquity of wireless devices, radio spectrum has become a scarce resource. Moreover, recent measurement studies of the radio spectrum have shown that frequency bands allocated to licensed users are highly underutilized. I will give an overview of my recent research on the design and analysis of wireless networks that exploit this underutilized spectrum opportunistically while avoiding harmful interference to the licensed users. The enabling technology for such opportunistic spectrum access is cognitive radio, which is a type of wireless device that can dynamically modify its transmission and reception parameters in response to its radio environment. My research results suggest that opportunistic spectrum access based on cognitive radio technology has the potential to dramatically increase the capacity of wireless networks. Real-world applications and future research directions will also be discussed. CS Seminar: Faculty Research OverviewWednesday, November 18, 2009, AbstractWe will have the third monthly seminar reviewing research activities and projects of computer science faculty. Professors Allbeck, Shehu and Sousa will each speak for 15 minutes about their current interests and projects, followed by questions and discussions. Prof. Allbeck: Places Everyone: Creating an Animated Background of Human Activity Creating virtual scenarios that simulate a human population with typical and varied behaviors can be an overwhelming task. In addition to modeling the environment and characters, tagging the environment with semantic data, and creating motions for the characters, the simulation designer also needs to create character profiles for the population and link these character traits to appropriate behaviors to be performed at appropriate times and places during the simulation. I'll describe an architecture, called CAROSA (Crowds with Aleatoric, Reactive, Opportunistic, and Scheduled Actions), that facilitates the creation of heterogeneous populations for simulations by using Microsoft Outlook®, a Parameterized Action Representation (PAR), and crowd simulator. Prof. Shehu: Model-based Search for Molecular Structures Search is an important topic in AI. The talk will summarize some robotics-inspired search methods developed in our lab to find biologically-relevant structures of important biomolecules like proteins. Prof. Sousa: Software issues for Smart Spaces. Smart spaces, aka ambient intelligence, aka ubiquitous computing, enables users to freely interact with multiple computers embedded on furniture, appliances, and vehicles. Or does it? We'll talk about current research issues for software design, end-user programming, human-computer interaction, security and trust, context-awareness, and conflict resolution among multiple users. SANG seminar: On the Internet, "Am I Really not a Dog?''Friday, November 13, 2009, AbstractAnonymity is one of the main virtues of the Internet. It protects privacy and freedom of speech, but makes it hard to assess the credibility of online users and the content they post. This paper presents FaceTrust, a system that uses online social networks to provide lightweight and attribute-based credentials while preserving a user's anonymity. FaceTrust employs a ``game with a purpose''design to elicit a user's friends' opinions about his self-claimed attributes such as profession or approximate age, and uses attack-resistant trust inference algorithms to estimate the likelihood that an attribute is true. It then provides a credential, which a user can use to corroborate his online assertions. We evaluate FaceTrust using a crawled social network graph as well as a real-world deployment. The results show that our credibility estimations correlate well with the ground truth, even when a large fraction of the social network users are dishonest. Note: You can install FaceTrust's Facebook application, called "Am I Really?", at http://apps.facebook.com/am-i-really BioMichael Sirivianos is a Ph.D. student at Duke University. His research interests include network security and peer-to-peer systems. He received a B.S in Electrical and Computer Engineering from the National Technical University of Athens in 2002, and an M.S. in Computer Science from the University of California, San Diego in 2004. More information is available at http://www.cs.duke.edu/~msiriviaGRAND seminar: United we stand, divided we fall: Integrating Continuous Robot MotionTuesday, November 10, 2009, AbstractResearch in robotics has focused since its inception towards increasing the ability of robots to plan and act on their own in order to complete assigned high-level tasks. Toward this goal, this talk presents a multi-layered approach that automatically and efficiently plans the sequence of motions the robot needs to execute so that the resulting trajectory is dynamically feasible, avoids collisions with obstacles, and satisfies a given high-level specification. In distinction from traditional approaches in motion planning, the proposed approach can take into account sophisticated high-level specifications given by Finite State Machines, Linear Temporal Logic, STRIPS, Hidden Markov Models, and other planning-domain definition languages. Such expressive models make it possible to specify complex tasks that frequently arise in navigation, manipulation, robotic-assisted surgery, search-and-rescue missions. Initial validation in physics-based simulations with high-dimensional robotic models demonstrate significant computational speedups over related work and show the ability of the proposed approach to efficiently plan valid trajectories that satisfy complex high-level specifications. BioErion Plaku is a Postdoctoral Fellow at the Laboratory for Computational Sensing and Robotics at Johns Hopkins University. He received the Ph.D. degree in Computer Science from Rice University in 2008. His research focuses on motion planning and control of cyber-physical systems for human-machine cooperative or fully automatic task performance in complex domains. Some applications include robot navigation, manipulation, haptic exploration, and robotic-assisted surgery. His research interests encompass robotics, hybrid systems, AI, logic, data mining, and large-scale distributed computing.Software Engineering Seminar: Continuous Learning for Self-Adaptive Software SystemsMonday, November 09, 2009, AbstractRecent computing trends, such as pervasiveness and mobility of systems, increase the software complexity to a point where the software itself must adapt at run-time. In order to meet functional and quality requirements in a setting of ever changing conditions and constraints, self-adaptation is one possible answer. Adaptive system design, development, and maintenance add additional challenges for software engineers. In addition to the complexity of static system engineering, systems must know when to adapt, where to adapt, and how to adapt. Acquiring knowledge to answer these questions is a challenging task and the problem becomes even more complex as the systems, and number of conditions and constraints grow. In this talk we present and exemplify work in progress on a dual learning process with architecture support that combines off-line and on-line mechanisms. Off-line, the system is simulated or subject for controlled executions. The collected information is used to derive configuration knowledge, i.e., configuration rules. We realize that off-line learning will never be 100 percent correct or complete in the general case. We address this issue by employing on-line learning strategies for gradually tuning/extending/replacing configuration knowledge. BioJesper Andersson is an assistant professor at Växjö University in Sweden. His main research interests are in software architectures, end-user programming and reuse for self adaptive systems development and self adaptation in distributed architectures.Software Engineering Seminar: Architectural Patterns for Decentralized Self-Adaptive SystemsMonday, November 09, 2009, AbstractSelf-adaptability has been proposed as an effective approach to tackle the increasing complexity of constructing and managing contemporary software systems. Self-adaptability endows a system with the capability to adapt itself to changes in its environment and user requirements. Several researchers have argued that software architecture provides the right level of abstraction and generality to deal with the challenges of self-adaptability. One of the major challenges in self-adaptive systems is dealing with distribution and decentralization. Decentralized control is crucial for quality requirements such as openness and scalability. Over the past 8 years, we have been studying decentralized architectures for realizing self-adaptability based on multi-agent systems (MAS). A MAS architecture structures the software in a number of interacting autonomous entities (agents) that cooperatively realize the system goals. Agents flexibly adapt their behavior and interactions to dynamics in the system or its environment. In the course of designing and building various MAS applications, we derived several architectural patterns that provide generic solution schemes for recurring design problems. In this talk, I will zoom in on a number of these patterns and illustrate them with practical examples. BioDanny Weyns is a post-doctoral researcher at the Katholieke Universiteit Leuven, Belgium. His main research interests are in software architecture, self-adaptive systems, multi-agent systems, and middleware for decentralized systems. Danny is currently visiting researcher at Valoria Lab of the Université de Bretagne-Sud, France where he works with Prof. Flavio Oquendo on formal modeling of dynamic software architectures of decentralized systems.Joint CS/Volgenau School Seminar: A Day in the Life of an Access Controller on the WWWNovember 4, 2009, AbstractWe still wish to govern the accesses to resources residing on large, loosely coupled and mostly uncoordinated distributed systems such as the WWW. In order to do so, we wish to create access control frameworks that are sufficiently generic so that they can be used by multiple application domains. In order to do so, one needs to be able to define all relevant entities in a manner that is name-space independent, but yet customizable as needed. In addition, the framework needs to be able to interpret security policies and provide decisions that have to be computed amidst (distributed) divergences and failures. Additionally, enforcing some decisions made by such policy frameworks may change the policies themselves, thereby requiring the transactional and locking mechanisms in order enforce the rendered decisions. Yet, these policy frameworks, being constructed out of a collection of communicating processes, have to evolve from their birth to death in a manner that reflects their operational environment in a policy consistent manner. This talk describes some work that has been conducted in cooperation with a group of individuals on enhancing the eXtensibe Access Control Meta Language (XACML) and its enforcement framework. GRAND seminar: Computing structural changes in proteinsTuesday, November 03, 2009, AbstractProteins are involved in virtually every process and aspect in life ? from the flexing of our muscles to our immune system response. It is widely accepted that proteins are dynamic molecules with generally well-defined three-dimensional structures, and that understanding the structure and dynamics of proteins is crucial for understanding their function and the processes they mediate. Various computational methods exist for modeling and simulating protein structure and dynamics, but several traditional methods are limited due to the large amount of calculations involved. This talk will present a number of methods for searching the conformational space of proteins at various time and space scales. On the one end of the spectrum, Molecular Dynamics calculations are used for detailed analysis of local structural changes in proteins. On the other end, robotics-inspired search techniques are used to characterize the structure and dynamics of proteins by representing them using a mechanistic/geometric models subject to physics constraints. BioNurit Haspel is an assistant professor in the department of Computer Science at the University of Massachusetts in Boston. She received her BSc. in Chemistry and Computer Science from Tel Aviv University and her Masters and Ph.D in Structural Bioinformatics (Computer Science) from Tel Aviv University in 2007. She did her postdoctoral research in the department of Computer Science at Rice University in Houston, TX. Her research involves developing and applying computational methods to explore the structure and dynamics of protein molecules. Some applications include the computational design of nano-structures, applying computational simulations and search techniques to understand aspects of the human immune system inhibition and developing algorithms taken from Robotics and graph theory to simulate large scale structural changes in protein complexes.Joint CS/Volgenau School Seminar: Exploring the Maze of MIX Networks and MalwaresWednesday, October 28, 2009, AbstractThe concept of MIX is fundamental to all anonymous communication networks, and almost all existing anonymous networks used traffic mixing and transformation to achieve anonymity. It has long been believed that flow mixing and transformations would effectively disguise network flows, thus achieve good anonymity. In the first half of this talk, I will overview my work in investigating the fundamental limitations of flow mixing and transformation in achieving anonymity. I will describe how active flow watermarking in packet timing could transparently make a sufficiently long flow uniquely identifiable. I will also discuss how active flow watermarking can be applied to track anonymous, peer-to-peer VoIP calls on the Internet. In the second half of my talk, I will overview my work in malware analysis and defense. Bio:Xinyuan Wang is currently an Assistant Professor in the Department of Computer Science at George Mason University. He received his BS and MS in Computer Science from Peking University and Chinese Academy of Space Technology respectively. He received his PhD in Computer Science from North Carolina State University in 2004 after years of professional experience in the networking industry. His main research interests are around computer network and system security including malware analysis and defense, attack attribution, anonymity and privacy, VoIP security, digital forensics. He has developed the first inter-packet timing based packet flow watermarking scheme that is provably robust against timing perturbation. He has first demonstrated that it is feasible to track encrypted, anonymous peer-to-peer VoIP calls on the Internet. In his later work, he has demonstrated the fundamental limitations of existing low-latency anonymous communication systems in the presence of timing attack, and developed the first practical attack that has penetrated the Total Net Shield the ultimate solution in online identity protection of www.anonymizer.com with less than 11 minutes worth of Internet traffic. Xinyuan Wang received the 2009 NSF Faculty Early Career Development (CAREER) Award, the 2009 GMU CS Outstanding Faculty Research award, and the 2004 ACM Graduate Student Research Competition Grand Finals Award (Third Place).GRAND seminar: Role of promiscuous binding and intrinsic disorderTuesday, October 27, 2009, AbstractCellular processes are highly interconnected and many proteins are shared in different pathways. Some of these shared proteins or protein families may interact with diverse partners using the same interface regions. Analysis of such regions is essential for understanding the mechanisms of specific molecular recognition of multiple diverse partners. We find that only 5 percent of protein families in the structure database have multibinding interfaces, and they do not show any higher sequence conservation compared with the background interface sites. We highlight several important functional mechanisms utilized by multibinding families. Promiscuous interactions can also be studied by using our recently developed IBIS server (Inferred Biomolecular Interaction Server, http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.html) which analyzes and annotates the interaction partners and locations of binding sites in proteins. It has been suggested that intrinsic disorder contributes to the ability of some proteins to interact with multiple partners as folding of disordered proteins into ordered structures may occur upon binding to their specific partners.We performed a large-scale study of intrinsically disordered regions in proteins and protein complexes. In accordance with the conventional view that folding and binding are coupled, in many of our cases the disorder-to-order transition occurs upon complex formation and can be localized to binding interfaces. Moreover, analysis of disorder in protein complexes depicts a significant fraction of intrinsically disordered regions, with up to one third of all residues being disordered. We find that the disorder in homodimers, especially in symmetrical homodimers, is significantly higher than in heterodimers and offer an explanation for this interesting phenomenon. The fascinating diversity of roles of disordered regions in various biological processes and protein oligomeric for ms shown in our study is an important subject for future endeavors in this area. HostAmarda ShehuSoftware Engineering Seminar: Mutation Testing: Towards industrial applicationMonday, October 26, 2009, AbstractSince the 1970s, mutation has been a testing technique widely used by researchers, who have applied it mainly for the validation of test suites, as well as for the validation of strategies for test case or test data generation. In our opinion, mutation is today mature enough for its application in industrial environments. Although the three main steps of mutation (mutant generation, test case execution and result analysis) may be quite costly, research has produced a good set of results that make possible the application of all this knowledge in industry. This work reviews some of this cost problems and the solutions proposed by the research and present a tool, Bacterio, which try to combine this solutions to facilitate the application of the mutation in the industry. BioPedro Reales has a MSc degree in Computers Science by the university of Castilla-La Mancha and has a Master in Avanced Computers Technologies by the university of Castilla-La Mancha. Currently, he is an active member of the Alarcos Research Group and is an Interchange Visitor in the George Mason University. His research areas are related to the automation software testing tasks.Joint CS/Volgenau School Seminar: Improving and Securing Mobile Internet AccessesWednesday, October 21, 2009, AbstractWith the rapid advancement of mobile communication technology, increasingly more users rely on mobile devices, such as smart phones and PDAs, to connect to the Internet, However, this technology trend and wide user accessibility have presented new challenges to the current practice from various aspects, ranging from improved Quality of Service to better security and privacy demanded by mobile users. In this talk, I will discuss some of these challenges and my research solutions to address them, in addition to an overview of my research. Specifically, I will discuss how to efficiently address the multiple dimensional heterogeneity problem in both on-demand and live streaming services. In order to solve increasingly serious problems of mobile malware on mobile devices, I will also present a novel technique to detect mobile malware in order to protect mobile users. Bio:Dr. Songqing Chen is an Assistant Professor of Computer Science in the Volgenau School of IT & Engineering. He received his Ph.D. from the College of William and Mary, 2004. His research interests mainly focus on design, analysis, and implementation of algorithms and experimental systems in distributed and networking environments, particularly, in the areas of Internet content delivery systems, Internet measurement and modeling, operating systems and system security, distributed systems, and high performance computing. Dr. Chen has served on various system and networking conference TPCs, including IEEE INFOCOM, ICDCS, ACM MM, and WWW. Currently, he is serving as the vice co-chair of ICDCS 2010 for the Internet/network protocol track. His research has been supported by NSF, HP Labs, and AFOSR. He is a recipient of the NSF CAREER Award and AFOSR YIP Award.CS Seminar: Faculty Research OverviewWednesday, October 21, 2009, AbstractWe will have the second monthly seminar reviewing research activities and projects of computer science faculty. Professors Brodsky, Wechsler and Sood will each speak for 15 minutes about their current interests and projects, followed by questions and discussions. Prof. Brodsky: Decision-Guidance Systems How would you design a computer systems to interract and guide human decision makers to move a complex process toward most desirable outcomes? How would you help find the best course of action in emergency, best business transactions, or recommend public policies guided by most positive outcomes? This talk will tell you about recent advances in decision-guidance systems, and exciting research opportunities in this area. Prof. Wechsler: Robust Biometrics Robust biometrics is about reliable authentication and identity management despite less than (1) perfect sensors, (2) missing data, and (3) corrupt information. Prof. Sood: Beyond Prevention and Detection – Intrusion Tolerance Our response to cyber security challenges is a time based intrusion tolerance system. We call our approach Self Cleansing Intrusion Tolerance (SCIT). SCIT servers are focused on limiting the losses that can occur because of an intrusion. To achieve this goal we limit the exposure time of the server to the internet. In the SCIT approach our goal is sub-minute exposure time for servers without service interruption. GRAND Seminar: Toward Physical Universal Constructors: Materials, Processes, Modules, and SystemTuesday, October 20, 2009, AbstractMore than 50 years ago the mathematician John von Neumann introduced the idea of a Universal Constructor - a machine that could build anything described to it, including copies of itself. Initially von Neumann investigated a physically realistic design, often called the "Kinematic Model", before abandoning it to focus on a more abstract formulation of the problem. Together with mathematician Stanislaw Ulam, von Neumann developed the concept of Cellular Automata (CA) as a mathematical tool for rigorous study of Universal Constructors. The CA model has seen a fair amount of success, and is currently an active area of study. Progress in Kinematic Universal Constructors has lagged behind, although the field has seen a resurgence in activity in recent years. This talk begins with a brief historical overview of Universal Constructors and Self-Replicating Machines. We then present some recent results from our lab: a network of materials and fabrication processes designed to facilitate self-replication, a set of universal electromechanical modules, and some larger scale system designs. The talk is concluded with a discussion of some open questions that may be of interest to those with a Computer Science background. Short BioMatt Moses is currently a doctoral student in Professor Greg Chirikjian's lab at the Department of Mechanical Engineering, Johns Hopkins University. Mr. Moses holds a M.S degree in Mechanical Engineering from University of New Mexico, and from 2001-2005 worked as an engineer for General Dynamics Robotic Systems in Westminster, Maryland. Mr. Moses's research interests include self-replicating and universal-constructing machines, biologically-inspired robotics, and dynamic running and locomotion in robot vehicles.Software Engineering Seminar: Tulips, Potatoes, Apples, ISO 9001 and the CMMIFriday, October 16, 2009, AbstractThere are many influences that come into play when creating new processes or improving existing processes. One can be a result of processes or experiences people bring into an organization from the outside. Others include the influence of existing company culture; or having to be in compliance with a particular best practice model like the CMMI or standard like ISO 9001; or even what one comes across in literature, on the internet or even at forums such as conferences and SPIN meetings. We are continually being influenced to change and improve the way we do things. This presentation shows an example of how influences come in play to create and improve an example process. In this case, a verification and validation (V&V) process for a software application that has to meet nuclear quality standards (NQA-1 and IEEE). We will explore how this example process comes into existence under various influences, including how it is affected by personal experience, different best practice models, cultural resistance, and continuous improvement. In the end, the most successful processes are those that incorporate multiple influences to create a best fit solution. Not unlike how plants adapt and evolve to successfully survive in a constantly changing world. Plants do this naturally by pollination, but sometimes plants receive outside “help” from other sources. These pollination vectors work together to influence the resulting offspring across multiple generations. In the end, aren’t we all doing the same thing, pollinating and spreading our ideas and controlling the evolution of processes? This presentation will show how us human pollinators work together to bring about the continuing adaptations needed for successful process improvement. BioNelson Perez is president of Sierra’s Edge, Inc. a process development and improvement consultant. With over 25 years of work experience, he has worked the entire product development life cycle and held numerous management and engineering positions on such high visibility programs as the B2 Stealth Bomber; NASA Space Shuttle; and National Missile Defense. He has worked a variety of other domains including security systems, information systems, computer integrated manufacturing, wireless communication, commercial software development, aircraft systems, and non-destructive testing. He has co-authored 1 NASA-related patent, has authored several papers and is an active presenter at conferences, software process improvements network (SPIN) meetings and other venues. Perez consults with companies in management, technology innovation and process and business improvement including ISO 9001:2000, CMMI, and ITIL v3.SANG seminar: Exploitation and Threat Analysis of Open Mobile DevicesFriday, October 16, 2009, AbstractThe increasingly open environment of mobile computing sys- tems such as PDAs and smartphones brings rich applica- tions and services to mobile users. Accompanied with this trend is the growing malicious activities against these mobile systems, such as information leakage, service stealing, and power exhaustion. Besides the threats posed against individual mobile users, these unveiled mobile devices also open the door for more serious damage such as disabling criti- cal public cyber physical systems that are connected to the mobile/wireless infrastructure. The impact of such attacks, however, has not been fully recognized. In this talk, we show that mobile devices, even with the state-of-the-art security mechanisms, are still vulnerable to a set of carefully crafted attacks. Taking Linux-based cellphones as an example, we show that this vulnerability not only makes it possible to attack individual mobile devices such as accessing unauthorized resources, disabling predefined security mechanisms, and diverting phone calls, but also can be exploited to launch distributed denial-of-service attacks against critical public services such as 911. BioLei Liu is a Ph.D. student in Computer Science Department of George Mason Univesity. His research interests incude system security, network application, operation systems and sogrware engineering. Before pursuing his Ph.D. degree, he has several years' experience in IT industry.Engineering Building: Grand OpeningFriday, October 02, 2009, AbstractCome visit the Robotics Lab (Room 2201) and the Visual Computing Lab (Room 4405) for demos and see posters displaying research by CS faculty in Room 2901. Software Engineering Seminar: A Modeling Language for Activity-Oriented Composition of Service-Oriented Software SystemsWednesday, September 30, 2009, AbstractThe proliferation of smart spaces and emergence of new standards, such as Web Services, have paved the way for a new breed of software systems. The functional and QoS requirements of such software systems are often not known a priori at design-time, and even if they are, they may change at run-time. Unfortunately, the majority of existing software engineering techniques rely heavily on human reasoning and manual intervention, making them inapplicable for automatic composition of such software systems at run-time. Moreover, these approaches are primarily intended to be used by technically knowledgeable software engineers, as opposed to domain users. In this talk, we present Service Activity Schemas (SAS), an activity-oriented language for modeling software system’s functional and QoS requirements. SAS targets service-oriented software systems, and relies on an ontology to provide domain experts with modeling constructs that are intuitively understood. SAS forms the centerpiece of a framework intended for user-driven composition and adaptation of service-oriented software systems in a pervasive setting (SASSY). BioNaeem Esfahani is a PhD candidate in Computer Science Department, Volgenau School of Information Technology and Engineering. He got his bachelor’s degrees on Computer Engineering with major of Software Engineering from University of Tehran, Tehran, Iran. He also holds a Master of Science degree in Computer Engineering with major of Software Engineering from Sharif University of Technology, Tehran, Iran. His current research mainly focuses on Software Architecture, Autonomic Computing, Model Driven Development, Pervasive Systems, and Software Development Processes.GRAND Semianr: Reconstruction, Localization and Semantic Parsing of Urban ScenesTuesday, September 29, 2009, AbstractI will describe a method for 3D reconstruction of urban scenes, which along with the ego-motion estimation and depth map fusion constitutes a robust, purely vision based method for capturing 3D models of urban environments. I will also talk briefly about some on-going work on semantic segmentation of urban areas using spatial co-occurrence of visual words and 3D geometry. I will show some preliminary results on challenging urban scenes with varying viewpoints and large number of categories appearing simultaneously. SANG seminar: On the Effectiveness of Low Latency Anonymous Network in theFriday, September 25, 2009, AbstractAn anonymous network provides services to hide the correspondence between its incoming and outgoing messages. Timing attack is a significant challenge for anonymous networks that support interactive and low-latency applications. We introduce a novel metric that can quantitatively measure the practical effectiveness (i.e. anonymity) of all anonymous networks in the presence of timing attack. Our metric is based on a novel measurement of the distortion of the packet timing between the incoming and the outgoing flows to and from the anonymous network and it uses wavelet based analysis to measure the variability of the distortion. To the best of our knowledge, our approach is the first practical method that can quantitatively measure the packet timing distortion between flows that may have gone through such transformations as flow mixing/spliting/merging, adding chaff, packet dropping. To validate our anonymity metric, we have conducted real-time timing attacks on various deployed anonymous networks such as Tor, anonymizer.com and have used the timing attack results as the ground truth for validating our anonymity metric. We have found strong correlation between our anonymity metric and the timing attack results. Our metric measurements and timing attack results show that the circuit rotation in Tor network could significantly increase its resistance to timing attack at the cost of more timing disturbances to the normal users. In addition, we have found that adding constant rate chaff (i.e. cover traffic) has diminishing effect in anonymizing packet flows. BioJing Jin is a Ph.D. student in Computer Science Department of George Mason University. Her research interests include system and networking security, software engineering.CS Seminar: Faculty Research OverviewWed, Sept 23, 2009, AbstractWe will have the first monthly seminar reviewing research activities and projects of computer science faculty. Professors Duric, Rangwala and Kosecka will each speak for 15 minutes about their current interests and projects, followed by questions and discussions. Prof. Zoran Duric: Understanding Human Movement (Area: Computer Vision, Robotics, AI) Prof. Huzefa Rangwala: Learning for Metagenomics and Structural Bioinformatics (Area: Bioinformatics, Data Mining) Prof. Jana Kosecka: Virtual Travel using Image Based Models (Area: Computer Vision, Robotics, AI) GRAND Seminar: From recognizing biological sequences, to identifying search keywords: A feature generation frameworkTuesday, September 22, 2009, AbstractThe set of attributes or features selected to model an entity is very important for correct classification. In this talk I will present an integrated process, which I refer to as feature generation. This method allows the user to construct informative features based on domain knowledge, and to search a large space of potential features effectively. I applied this approach to the problem of splice-site prediction and obtained new predictive models for these biological signals for two different organisms. These models have achieved significant improvements in accuracy over existing, state-of-the-art approaches. In each case, the identified sets of features were used to discover biologically interesting motifs. They are available to the public through an easy-to-use website, SplicePort (http://www.spliceport.org). Spliceport can be used to predict new splice sites from user-input sequences, and to browse the whole collection of features for biologically significant signals. I also applied this approach to the problem of keyword identification for effective document retrieval. The automatic identification of ?clickable? words in the title and abstract of articles is of central importance in improving the retrieval quality of the search engine. It is also important to authors as it increases the chances that their article will get better visibility. PubMed (http://www.ncbi.nlm.nih.gov/PubMed), a free Web service provided by the U.S. National Library of Medicine, provides daily access to over 19 million biomedical citations for millions of users. The current retrieval algorithm in PubMed finds all the articles that match the terms in the user query and presents them in reverse chronological order. I studied PubMed log data for the clickthrough activities of users after they have issued a query. Linking the query terms to the clicked articles, I built a novel machine learning model that identifies "keywords" that are preferred by users to access a particular article. Short BiographyDr. Rezarta Islamaj received her Ph.D. degree in Computer Science from University of Maryland at College Park in 2007. Her research focused on applying machine learning and data mining approaches to computational biology problems. Specifically she worked on construction, selection and discovery of appropriate motifs to model biological signals for accurate classification and prediction.SANG seminar: Quantification of Computer Security: Some Case StudiesThursday, September 17, 2009, AbstractIn this talk, I will discuss several case studies related to the quantification of computer security. In particular, I will present results obtained from a test-bed deployed at the University of Maryland to collect attack data using target computers (i.e., honeypots). The data provided the evidence needed in the following four research threads. (1) Within the security community, scans are usually considered as precursors to an attack. However, few studies quantified the validity of this hypothesis. We introduced packet-counting models to identify TCP scans and attacks and applied these models to analyze malicious traffic towards honeypots. (2) We developed a methodology for determining the characteristics that separated attacks most efficiently. A comparison between the analysis of attack messages and the outcome of a clustering algorithm indicated the efficiency of the characteristic. (3) We built a profile of attacker behavior following a remote compromise by looking for specific actions taken by attackers. The results represent solid statistical evidence to support widely held beliefs about post-compromise attacker behavior. (4) We compared malicious traffic originating inside UMD with that originating outside UMD. We showed that internal malicious traffic often contained different malicious content compared to that of external traffic. Speaker's bioProf. Michel received a degree in physics engineering from the Free University of Brussels, Belgium, in 1991, and a doctorate in computer science from the National Polytechnic Institute of Toulouse, France, in 1996. From 1996 to 2001, he was a researcher at the University of Illinois, Urbana-Champaign.He joined the University of Maryland in 2001 as Assistant Professor. His research covers dependability and security issues. His latest research focuses on the empirical quantification of computer security. He has published over 60 papers in journals and refereed conference proceedings in those areas. GRAND Seminar: Digital Geometry and 3D Imagery: Topological methodsFriday, September 11, 2009, AbstractIn this talk, we will focus on digital geometry and topology methods of 3D image processing and computer vision. We first introduce connectivities in digital space and algorithms for component extraction. Then we discuss digital surfaces and manifolds including their recognition procedures. We will also present fast algorithms to compute invariants such as genus and homology groups for 3D objects in 3D space. Finally, we will discuss the methods for high dimensional cloud point data processing including persistent analysis and its relationship to manifold learning. Short BioDr. Li Chen is an associate professor of computer science at the University of the District of Columbia. He is currently working on problems in image segmentation algorithms, complexity analysis of algebraic groups, and the relationship between finite elements and gradually varied fitting. Li Chen received his BS, MS, and Ph.D. all in CS from Wuhan University (1982), Utah State University (1995), and the University of Bedfordshire (Luton, UK, 2001), respectively. His work includes: 1) The definitions of digital surfaces and manifolds; 2) Digital surface points classifications; and 3) The lambda-connected search algorithm for image segmentation, a dual-technique to threshold segmentation, the most popular segmentation method.SANG seminar: Business-Oriented Autonomic Load Balancing for Multitiered Web SitesThursday, September 10, 2009, AbstractThis presentation will discuss the application of autonomic computing to load-balancing for a multi-tiered auction web site. Autonomic computing systems are able to adapt to changing environments (such as changes in the workload intensity or component failures) in a way that preserves high-level operational goals, such as service level objectives. The autonomic load balancer of the web site divides the bottleneck server tier into clusters, each of which is dedicated to a certain priority class of users. The autonomic load balancer dynamically adjusts resource allocations to the clusters in an effort to maximize a utility function based on response time and bid throughput. To reduce switching costs, the load balancer also considers load balancing policies that redirect a percentage of requests intended for one cluster to a different cluster. To make allocation and policy decisions, the autonomic load balancer uses an efficient heuristic search to explore a utility landsc ape generated by the predictions of an analytic performance model. Another key contribution presented here is a novel method for the random generation of realistic stress tests. Using this stress test method, the autonomic load balancer is assessed against both a round-robin load balancing approach and a dedicated cluster approach. Speaker's bioJohn Ewing is currently a PhD student in the Computer Science Department at George Mason University. From 2001 to 2005, John worked at the Defense Information Systems Agency conducting capacity planning studies and performance troubleshooting of large, distributed software systems with millions of users. From 1999 to 2001, John worked as a government IT contractor analyzing performance of computer systems and developing prototype software. John received his Masters in computer science from the Illinois Institute of Technology in 2003 and his Bachelors in chemistry from the University of Richmond in 1997.SANG Seminar: VirusMeter: Protecting Your Cellphone from SpiesFriday, September 04, 2009, AbstractDue to the rapid advancement of mobile communication technology, mobile devices nowadays can support a variety of data services that are not traditionally available. With the growing popularity of mobile devices in the last few years, attacks targeting them are also surging. Existing mobile malware detection techniques, which are often borrowed from solutions to Internet malware detection, do not perform as effectively due to the limited computing resources on mobile devices. In this work, we propose VirusMeter, a novel and general malware detection method, to detect anomalous behaviors on mobile devices. The rationale underlying VirusMeter is the fact that mobile devices are usually battery powered and any malicious activity would inevitably consume some battery power. By monitoring power consumption on a mobile device, VirusMeter catches misbehaviors that lead to abnormal power consumption. For this purpose, VirusMeter relies on a concise user-centric power model that characterizes power consumption of common user behaviors. In a real-time mode, VirusMeter can perform fast malware detection with trivial runtime overhead. Speakers' BioLei Liu is a Ph.D. student in Computer Science Department of George Mason Univesity. His research interests incude system security, network application, operating systems and software engineering. Before pursuing his Ph.D. degree, he has several years' experience in IT industry.Computer Science: Mandatory GTA WorkshopThursday, September 03, 2009, Orientation: PhD StudentsThursday, August 27, 2009, Orientation: GTAThursday, August 27, 2009, Orientation: New Graduate StudentWednesday, August 26, 2009, AbstractThe Volgenau School of Information Technology and Engineering is hosting its annual special orientation event to welcome all newly admitted graduate students. Although orientation is not mandatory, it is strongly recommended that all degree-seeking graduate students plan to attend. Essential information regarding university services for graduate students and program information from the Computer Science departments will be provided. Most importantly, this is your opportunity to meet your peers, the administrative and academic staff members who will assist you during the pursuit of your graduate course work and degree. RSVP Please RSVP online for orientation by visiting: http://ite.gmu.edu/graduateresearch/responseform/ Please contact the Office of Graduate Admissions & Enrollment Services at itegadm@gmu.edu should you have any questions. PhD Dissertation Defense: Efficient Resource Management for Heterogeneous Devices Accessing Internet Streaming ContentWednesday, August 19, 2009, AbstractThe volume of streaming media content has surged on the Internet in recent years. In parallel, with the technology advancement in wireless and third generation (3G) networks, more and more Internet users today use their mobile devices, such as smart phones and PDAs, to access Internet streaming content. However, compared with desktops, mobile devices normally have different display sizes, color depths, bandwidth capacities, CPU speeds, and battery capacities, which are termed Multiple Dimensional Heterogeneity (MDH). Due to the MDH problem, these mobile devices normally cannot directly display the data streamed to desktops. A few solutions based on Multiple Description Coding (MDC) or Scalable Coding (SC) have been proposed, but none of these solutions is practical due to their various limitations. In this dissertation, novel efficient resource management and transcoding schemes are investigated to address the MDH problem in both Internet on-demand and live streaming systems. First, in on-demand streaming systems, meta-data caching is leveraged during the online transcoding to reduce the overall CPU consumption. A model is further constructed to study the tradeoff between the CPU and the storage consumption for different meta-caching schemes under various conditions. Accordingly, an adaptive scheme that always outperforms existing schemes is proposed. Second, in live streaming systems, the idle peer computing cycles are leveraged for efficient online transcoding based on an additional transcoding overlay constructed by participating transcoding peers. This proposed scheme effectively explores the tradeoff between the CPU and the bandwidth resources. Third, considering resource contributions made by heterogeneous devices and their limited available resources, e.g., battery capacity, we propose a dynamic rotation scheme in both streaming and meta-transcoding overlays to balance the resource consumption among different peers, aiming to improve the fairness among peers and the overall system robustness. Fourth, a general theoretical framework is constructed to maximize the resource utilization in heterogeneous streaming systems. Accordingly, a distributed algorithm is proposed to achieve near-optimal performance with acceptable control overhead. Non-Degree Open House: AugustWednesday, August 12, 2009, The Volgenau School of IT & Engineering will offer a series of Non-Degree Open Houses this summer where prospective students interested in taking graduate coursework for the Fall 2009 term an incredible opportunity to:* Learn about our graduate programs * Apply as a non-degree student * Obtain an 'on-the-spot' admissions decision * Register and pay for classesThis is a one-stop opportunity to get started on the road towards your graduate education! Eligibility Disclaimer: Individuals seeking or holding F1 or J1 visas are not eligible for non-degree status, but may apply for any of our degree programs. Be sure to bring the application materials indicated on our Non-Degree Open House requirements checklist. RSVPs are required: http://volgenau.ite.gmu.edu/graduateresearch/responseform/ Find Directions/Map: http://coyote.gmu.edu/map Parking Information/Cost: http://parking.gmu.edu/visitors.htm If you have questions about this event please contact us at itegrad@gmu.edu. GRAND seminar: Secure Computation on Encrypted DatabaseThursday, July 23, 2009, AbstractGoogle and Amazon have turned their huge infrastructure into a cloud computing environment and are aggressively recruiting businesses to run applications on their platforms. Many top-tier IT vendors have been promoting cloud computing as a new service model. However, serious concern has been raised about the security and privacy on such a service platform. Corporate users would need to protect their data running on the cloud computing platform from the “untrusted” service provider. Unfortunately, traditional encryption methods that aim at providing “unbreakable'' protection are often not adequate because they are not designed to support applications to be executed on the encrypted data. In this seminar, the general problem of computing on encrypted data will be discussed. The key issue is how to balance the need on security and the requirement to perform computation. As a case study, the problem of k-nearest neighbor (kNN) computation will be used to illustrate a new model of secure computation on encrypted database. Short BioProfessor David Wai-lok Cheung is the Head of Department of Computer Science and Director of the Center for E-commerce Infrastructure Development (CECID) in The University of Hong Kong. He conducts research in database, data mining and e-commerce technologies. He was the recipient of the HKU Outstanding Researcher Award. Most recently, he received the Distinguished Contribution Award in the 2009 Pacific-Asia Data Mining and Knowledge Discovery Conference. He was the program chairman of the 2001 and 2005 Pacific-Asia Knowledge Discovery and Data Mining Conferences, the conference chairman of the 2007 PAKDD Conference. Most recently he is the conference co-chair of the 2009 CIKM Conference. Concerning applied research, he has received more than HK$60M grants from the Hong Kong Innovation and Technology Commission. His team at HKU has developed open-source ebXML gateway, which has been used by developers in e-commerce and logistics from more than 80 countries. The open-source product has received awards in various prominent competitions, including the Hong Kong 2004 IT Excellence Awards, the 2004 Asia-Pacific ICT Awards, and the 2005 Linux Business Awards.Non-Degree Open House: JulyWednesday, July 15, 2009, The Volgenau School of IT & Engineering will offer a series of Non-Degree Open Houses this summer where prospective students interested in taking graduate coursework for the Fall 2009 term an incredible opportunity to:* Learn about our graduate programs * Apply as a non-degree student * Obtain an 'on-the-spot' admissions decision * Register and pay for classesThis is a one-stop opportunity to get started on the road towards your graduate education! Eligibility Disclaimer: Individuals seeking or holding F1 or J1 visas are not eligible for non-degree status, but may apply for any of our degree programs. Be sure to bring the application materials indicated on our Non-Degree Open House requirements checklist. RSVPs are required: http://volgenau.ite.gmu.edu/graduateresearch/responseform/ Find Directions/Map: http://coyote.gmu.edu/map Parking Information/Cost: http://parking.gmu.edu/visitors.htm If you have questions about this event please contact us at itegrad@gmu.edu. Non-Degree Open House: JuneWednesday, June 17, 2009, The Volgenau School of IT & Engineering will offer a series of Non-Degree Open Houses this summer where prospective students interested in taking graduate coursework for the Fall 2009 term an incredible opportunity to:* Learn about our graduate programs * Apply as a non-degree student * Obtain an 'on-the-spot' admissions decision * Register and pay for classes This is a one-stop opportunity to get started on the road towards your graduate education!Eligibility Disclaimer: Individuals seeking or holding F1 or J1 visas are not eligible for non-degree status, but may apply for any of our degree programs. Be sure to bring the application materials indicated on our Non-Degree Open House requirements checklist. RSVPs are required: http://volgenau.ite.gmu.edu/graduateresearch/responseform/ Find Directions/Map: http://coyote.gmu.edu/map Parking Information/Cost: http://parking.gmu.edu/visitors.htm If you have questions about this event please contact us at itegrad@gmu.edu. PhD Dissertation Defense: Online Topic Detection, Tracking, and Significance Ranking Using Generative ModelsTuesday, June 09, 2009, AbstractOnline processing of text streams is an essential task of many legitimate applications. The objective is to deconstruct the documents into semantically coherent threads or topics, analyze the development of the topics over time, and identify newly emerging topics. This must be accomplished by processing only the textual content and publication time of document streams without requiring any metadata, such as hyperlinks or citation data. This dissertation presents an "Online Topic Model " (OLDA), a generative topic model that automatically captures the thematic patterns and identifies emerging topics in text streams and their changes over time. The proposed approach allows the topic modeling framework, specifically the Latent Dirichlet Allocation (LDA) model, to work in an online fashion such that it incrementally builds an up-to-date model (mixture of topics per document and mixture of words per topic) when a new document (or a set of documents) appears based on the Empirical Bayes method. The idea is to incrementally update the current model according to the information inferred from the new stream of data with no need to access previous data. The dynamics of the proposed approach also provide an efficient means to track drifts in topics and detect the emerging topics in real time. This dissertation also extends the proposed online topic model to incorporate semantic history propagated from models that were estimated within a "sliding history window." Since the proposed approach is totally unsupervised and data-driven, the effect of different factors is analyzed, including the window size, history weight, and equal/decaying history contribution. Since the actual number of underlying topics is unknown and there is no definite and efficient approach to accurately estimate it, the inferred topics of any topic model do not always represent meaningful themes. This dissertation presents the first automated unsupervised analysis of LDA models to rank the topics based on their semantic significance and, eventually, identify and distinguish junk topics from legitimate ones. The basic idea consists of measuring the distance between topic distribution and some "junk distribution." In particular, three definitions of "junk distribution" are introduced, and a variety of metrics are used to compute the distances, from which an expressive figure of the semantic significance of the topics is implemented using a 4-phase Weighted Linear Combination approach. SANG Seminar: Towards Optimal Resource Utilization in Heterogeneous P2PFriday, May 08, 2009, AbstractThough plenty of research has been conducted to improve Internet P2P streaming quality perceived by endusers, little has been known about the upper bounds of achievable performance with available resources so that different designs could compare against. On the other hand, the current practice has shown increasing demand of server capacities in P2P-assisted streaming systems in order to maintain high-quality streaming to end-users. Both research and practice call for a design that can optimally utilize available peer resources. In the paper, we first present a new design, aiming to reveal the best achievable throughput for heterogeneous P2P streaming systems. We measure the performance gaps between various designs and this optimal resource allocation. Through extensive simulations, we find out that several typical existing designs have not fully exploited the potential of system resources. However, the control overhead prohibits the adoption of this optimal approach. Then, we design a hybrid system in trading off the cost of assignment and utilization of resources. This hybrid approach has a proved theoretical bound on efficiency of utilization. Simulation results show that compared with the optimal resource allocation, our proposed hybrid design can achieve near-optimal (up to 90 percent) utilization while only use much less (below 4 percent) control overhead. Our results provide a basis for both server capacity planning in current P2Passisted streaming practice and future protocol designs. BioDongyu Liu is a Ph.D. candidate in Dept. of Computer Science at George Mason University. His research interests are in the areas of networking and systems, particular on Internet streaming delivery and QoS.GRAND Seminar: An Introduction to iPhone DevelopmentFriday, May 01, 2009, AbstractThe iPhone is easily one of the most enticing platforms for the new developer to try and stake their claim in the gold-rush environment that Apple has fostered on its application store. Unlike the Open Source realm, programming in the iPhone environment introduces its own complexities and Apple imposed restrictions upon the new developer. Drop in and learn about the issues I encountered during a semester of coding on the iPhone platform. I will discuss building an application from the inception to a working application, talk about the various issues faced along the way, and attempt to answer any questions you may have about bootstrapping your own attempts at finding fame and fortune in the iTunes AppStore. Short BioKarl Majer is a part-time undergraduate student in the Computer Science Department, Volgenau School of Information Technology and Engineering. When not attending class, Karl is an IT Professional with over 15 years of industry experience as an architect, systems administrator, and programmer.SANG Seminar: A Case Study of Traffic Locality in Internet P2P Live Streaming**Friday, May 01, 2009, AbstractWith the ever-increasing P2P Internet traffic, recently much attention has been paid to the topology mismatch between the P2P overlay and the underlying network due to the large amount of cross-ISP traffic. Mainly focusing on BitTorrent-like file sharing systems, several recent studies have demonstrated how to efficiently bridge the overlay and the underlying network by leveraging the existing infrastructure, such as CDN services or developing new application-ISP interfaces, such as P4P. However, so far the traffic locality in existing P2P li ve streaming systems has not been well studied. In this work, taking PPLive as an example, we examine traffic locality in Internet P2P streaming systems. Our measurement results on both popular and unpopular channels from various locations show that current PPLive traffic is highly localized at the ISP level. In particular, we find: (1) a PPLive peer mainly obtains peer lists referred by its connected neighbors (rather than tracker servers) and up to 90 percent of listed peers are from the same ISP as the requesting peer; (2) the major portion of the streaming traffic received by a requesting peer (up to 88 percent in popular channels) is served by peers in the same ISP as the requestor; (3) the top 10 percent of the connected peers provide most (about 70 percent) of the requested streaming data and these top peers have smaller RTT to the requesting peer. Our study reveals that without using any topology information or demanding any infrastructure support, PPLive achieves such high ISP level traffic locality spontaneously with its decentralized, latency based, neighbor referral peer selection strategy. These findings provide some new insights for better understanding and optimizing the network- and user-level performance in practical P2P live streaming systems. PhD Dissertation Defense: Service Composition Framework to Unify Simulation and Optimization in Supply ChainsThursday, April 30, 2009, AbstractIn supply chains, decisions have to be made regularly to coordinate production and delivery of goods or services effectively across enterprises, and to respond to constantly changing and increasingly customized market demands. Decision-making for supply chains requires the implementation of simulation and/or optimization techniques. Object-oriented simulation provides many advantages in ease of model development, testing, and extensibility, yet it is mainly based on trial-and-error, and thus, lacks systematic optimization. Mathematical programming (MP), on the other hand, allows supply chain problems to be solved efficiently using solvers with well-established optimization algorithms. However, MP uses relatively low-level mathematical abstraction, and thus, is challenging for individuals who are not Operations Research experts. This research introduces a novel approach to address these challenges. Proposed in this dissertation is a framework and language that unify the simulation and optimization of supply chains, which provides modelers with the advantages of simulation-like model development, testing, and reuse, and at the same time, the efficiency of MP. The proposed Service Composition (SC) model represents a business transaction as a Service; consequently, the supply chain can be modeled as a Service with interrelated composite or atomic sub-services. A Service is a class in Java programming language in which its constructor computes a business objective associated with the service instance. The constructor may involve decision-choice constructs for one or more decision variables and assert statements. While the procedural language provides the “simulation-like†semantics, the optimization semantics is achieved by automatic compilation of the simulation model into a MP model and solving it using an external solver. The proposed extensible library of simulation-like modeling components allows quick construction of complex supply chain simulation models and the development of new composite services. This dissertation also studied modeling supply chain services that involve uncertainty factors. The proposed two-stage recourse stochastic programming extension provides an environment to model services for decision-making with future corrective response. The decision variables are represented by means of a special structure to capture the random parameters. The effectiveness of our proposed framework is assessed with experiments that compare the performance of automatically compiled supply chain models with expertly crafted ones. SWESeminar: Privacy-Enhanced Trust ManagementThursday, April 30, 2009, AbstractThis talk will focus on research being conducted as part of Dalal Al-Arayed's dissertation which aims to produce a conceptual framework that extends current trust models to cover the needs of smart spaces (Trust in Smart Spaces- TISS); and that is generalized to be applicable across multiple problem scenarios (Generalized- TISS). It will cover the employment of privacy policies right at the beginning of the trust formation function to direct the application of the trust model for decision making. This adds a human factor and enables the user to personalize the trust model. BioDalal Al-Arayed is a doctoral candidate in the IT program. She has her BS in Computer Science with a minor in Business Administration from Coastal Carolina University, and her MS in IT from the University of North Carolina at Charlotte. She is an international student from Bahrain.SWE Seminar: Game Theory for DummiesThursday, April 30, 2009, AbstractOptimization problems are computational problems that address to find the best solution among all feasible solutions. This field of research sits in the intersection of Artificial Intelligence, Mathematics, and Software Engineering. An optimization can be the interest of one or more users. One user optimization problems can be like best choice of essentials, shortest traveling route etc. Multi user optimization problems can be network load distribution, bidding optimization, or QoS optimization when the system is used by more than one person. This type of problems requires balancing the outcome within all users. Game theory formalizes the outcomes of each user considering every possible way of action for each user. It formulates the best choice of a user depending of choices of other users. When there is a global or local optimal solution where all users want to stay with their strategies, this situation is called Equilibrium. The desired solution of a multi user optimization problem is to formulate it game theoretically and reach to an equilibrium point. BioZeynep Zengin is a PhD student in Computer Science Department, Volgenau School of Information Technology and Engineering. She got her bachelor’s degrees on Information Systems with double major of Computer Engineering from Isik University, Istanbul, Turkey. She also holds a Master of Science degree in Computer Engineering from Bogazici University, Istanbul, Turkey. Her current research mainly focuses on end-user development, self adapting systems, ubiquitous computing, and Computation Tree Logic.SANG Seminar: Open Problems in Vehicular Ad Hoc Network SecurityFriday, April 24, 2009, AbstractIn the past decade, more and more research has been done on nearly every aspect of vehicular networks, which are quite likely to become popular on the world's highways. Perhaps not surprisingly, security has become an issue. As with any network, attacks may come from a variety of directions. Vehicular networks present unique challenges in that the network itself is markedly atypical in terms of topology and node mobility. In addition, unmitigated attacks carry potentially very significant consequences. High node mobility coupled with frequent network changes makes traditional authentication and security mechanisms impractical in many cases. The problem becomes then the authentication of the data content within the network given the presence of adversaries. We identify probable attacks against vehicle-to-vehicle message applications and propose potential mitigation methods. BioEric John Swankoski is a third-year Ph.D. student in Dept. of Computer Science at George Mason University. He obtained his B.S. and M.S. at Penn State in 2002 and 2004, respectively.PhD Dissertation Defense: Routing in Delay Tolerant NetworksThursday, April 23, 2009, AbstractDelay tolerant networks (DTNs) are a newly emerging class of mobile distributed systems that are designed for extreme environments such as disaster response, wildlife management and planned networks in space. DTNs require a re-design of existing mobile network routing protocols because fully connected end-to-end paths between senders and receivers may never exist. The design and analysis of efficient DTN routing protocols is largely based upon a fundamental understanding of the mobility characteristics of individual nodes. My research focuses on providing performance models for DTN node mobility as well as basic routing protocols for unicast and multicast applications. I provide analytical results for parameters such as nodal contact and inter-contact times, and propose and evaluate several novel modeling techniques for evaluating multicopy DTN routing. Using the insights from these techniques I have designed and tested two DTN routing protocols. The first is a core-based technique for unicast routing, and the second is CERM, Controlled Epidemic Routing for Multicasting. Experimental results demonstrate that my approach has a highly accurate predictive value for routing performance and protocol efficiency, and can be used in a wide-variety of application settings. GRAND Seminar: Affine Invariant-Based Classification of Inliers and Outliers for Image MatchingTuesday, April 21, 2009, AbstractThis presentation describes a new approach to classify tentative feature matches as inliers or outliers during wide baseline image matching. Wide-baseline matching is the process of matching one image to another. After typical feature matching algorithms are run and tentative matches are created, our approach is used to classify matches as inliers or outliers to a transformation model. The approach uses the affine invariant property that ratios of areas of shapes are constant under an affine transformation. Thus, by randomly sampling corresponding shapes in the image pair we can generate a histogram of ratios of areas. The matches that contribute to the maximum histogram value are then candidate inliers. The candidate inliers are then filtered to remove any with a frequency below the noise level in the histogram. The resulting set of inliers are used to generate a very accurate transformation model between the images. In our experiments we show similar accuracy to the standard RANSAC approach and an order of magnitude efficiency increase using this affine invariant-based approach. Short BioDan Fleck is currently an instructor of Computer Science at George Mason University (GMU). He earned his B.S. in Electrical Engineering from the University of Texas at Austin before moving to Northern Virginia. While working full-time Dan completed his M.S. in Software Engineering from GMU.Currently he is pursuing a doctorate degree in Computer Science. Dan's doctoral research is in Computer Vision under Dr. Zoran Duric. Specifically researching novel approaches to matching images taken at different viewing angles, locations and scales. Previously, Dan was a technical lead and project manager at SRA International. At SRA he led projects ranging from 5 to 50 people for a variety of government clients. Dan worked within SRA's Health Systems group, Data Mining Center and most recently as technical lead within the Advanced Technology Group. Dan continues to serve in an advisory role at SRA. SANG Seminar: Defeating Anti-detection for Application-level Malware Analysis**Friday, April 10, 2009, AbstractMalware analysis is critical for malware detection and prevention. To defeat malware analysis and detection, today malware commonly adopts various sophisticated anti-detection techniques. For example, malware often performs various debugger, emulator, and virtual machine fingerprinting. These mechanisms produce more and more stealthy malware that challenges malware analysis schemes. In this work, we propose Malyzer to defeat malware anti-detection mechanisms at startup and runtime so that malware behavior during execution can be accurately captured and distinguished. For analysis, Malyzer starts a process copy, referred to as a shadow process, on the same host by defeating anti-detection mechanisms. Since ultimately malware will conduct local information harvesting or dispersion, Malyzer constantly monitors the shadow process's behavior and adopts a hybrid scheme for its behavior analysis. In our experiments, Malyzer can accurately detect all malware samples that employ various anti-detection techniques. BioLei Liu is a Ph.D. student in Computer Science Department of George Mason Univesity. His research interests incude system security, network application, operation systems and sogrware engineering. Before pursuing his Ph.D. degree, he has several years' experience in IT industry.GRAND Seminar: Towards a Universal Text Classifier: Transfer Learning from Encyclopedic KnowledgeTuesday, March 31, 2009, AbstractDocument classification is a key task for many text mining applications. However, traditional text classification requires labeled data to construct reliable and accurate classifiers. Unfortunately, labeled data are seldom available, and often too expensive to obtain. In this work, we propose a universal text classifier, which does not require any labeled training document. Our approach simulates the capability of people to classify documents based on background knowledge. As such, we build a classifier that can effectively group documents based on their content, under the guidance of few words describing the classes of interest. Background knowledge is modeled using encyclopedic knowledge, namely Wikipedia. Wikipedia's articles related to the specific problem domain at hand are selected, and used during the learning process for predicting labels of test documents. The universal text classifier can also be used to perform document retrieval, in which the pool of test documents may or may not be relevant to the topics of interest for the user. In our experiments with real data we test the feasibility of our approach for both the classification and retrieval tasks. The results demonstrate the advantage of incorporating background knowledge through Wikipedia, and the effectiveness of modeling such knowledge via probabilistic topic modeling. The accuracy achieved by the universal text classifier is comparable to that of a supervised learning technique for transfer learning. Short BioPu Wang is a PhD student in the Department of Computer Science at George Mason University. He received a Masters degree in Computer Science from Beijing University in 2007, and was an intern at Microsoft Research Asia from May 2006 to July 2007. His research interest is in machine learning, currently focusing on graph learning.Sotware Engineering Seminar: Comparison of Unit-Level Automated Test Generation ToolsWednesday, March 28, 2009, AbstractData from projects worldwide show that many software projects fail and most are completed late or over budget. Unit testing is a simple but effective technique to improve software in aspects of quality, flexibility, and time to market. However, testing each unit by hand is very expensive, possibly prohibitively so. Automation is essential to support unit testing and as unit testing is achieving more attention, developers are using automated unit testing tools more often. However, developers have very little information about which tools are effective. This experiment compares three well-known public-accessible unit test tools, JCrasher, TestGen4j, and JUB. We apply these tools to a variety of Java programs and evaluate them based on their mutation scores. As a comparison, we manually created two additional sets of tests. One test set contained random values with the same number of tests the three test tools created, and the other contained values to satisfy edge coverage. BioShuang Wang is a PhD student and a teaching assistant in Computer Science Department, Volgenau School of Information Technology and Engineering, George Mason University. Her current interests include software testing, Web Application testing, and Mutation testing. Her advisor is Dr. Jeff Offutt.Sotware Engineering Seminar: An Experimental Comparison of Four Unit Test Criteria: Mutation, Edge-Pair, All-uses and Prime Path CoverageWednesday, March 28, 2009, AbstractIn this talk, I present the results from a comparison of four unit level software testing criteria. Mutation testing, prime path coverage, edge-pair coverage, and all-uses testing were compared on two bases: the number of seeded faults found and the number of tests needed to satisfy the criteria. The comparison used Java classes and hand-seeded faults. Tests were designed and generated mostly by hand with help from tools that compute test requirements and mu-Java. I also present a secondary measure, a cost benefit ratio, computed as the number of tests needed to detect each fault. I also discuss some specific faults that were not found and present analysis for why not. BioNan Li is a PhD student in Computer Science Department, Volgenau School of Information Technology and Engineering. His current research mainly focuses on software testing and he is also interested in other fields of software engineering.Research Seminar: Efficient Algorithms for Protein Structure-Sequence Alignment and ApplicationsThursday, March 26, 2009, AbstractThe immediate need for knowing tertiary proteins structure intensifies as the applications of engineered proteins for drugs, carriers, enzymatic activities, receptors, vaccines, antibodies, biomaterials and nanotechnology, in vitro synthesis, and detection systems grow. Due to the high cost of experimental determination of protein structures, there is tremendous demand for efficient and accurate computational predictions of protein structures from primary sequence data and inference of protein functions from structure for rational protein or drug design. However, current computational approaches provide limited accuracy, often cannot handle large proteins, and require significant computational time. We developed a novel parameterized algorithm for structure-sequence alignment, which is the highly challenging computational part for protein structure prediction based on threading. The algorithm incorporates a graph theoretic model, parameterized computation and tree decomposition techniques. Experimental results demonstrate a successful application of the algorithm to non-coding RNA structure search in genomes. Methods based on this algorithm provide analogous increases in efficiency and accuracy in response to the protein structure prediction challenges. Through collaborative research with biologists and biomedical researchers, we are applying these methods to structure-function studies on proteins (like RTB and UGTs) with direct significant medical applications. BiographyXiuzhen Huang received the PhD degree in Computer Science from Texas A&M University in 2004. Since then she has been working as an assistant professor in the Department of Computer Science, Arkansas State University. She is currently the principal investigator of the bioinformatics lab at Arkansas Bioscience Institute (ABI). She holds an adjunct appointment in Information Science Department, University of Arkansas at Little Rock (UALR), is the graduate faculty member of the Molecular Biosciences PhD Program at ABI, and the joint PhD Program in Bioinformatics of UALR and University of Arkansas for Medical Sciences (UAMS). Her research strengthens and foci are in bioinformatics and computational biology, algorithm design and analysis. Her work includes collaborative projects with biologists at ABI and UALR, and biomedical researchers at UAMS, and has been supported by NIH INBRE and NSF EPSCoR grants for which she serves as the PI or a co-PI.Faculty Candidate Seminar: The Role of Computation in Cellular and Molecular Investigations of Human DiseaseTuesday, March 24, 2009, AbstractComputational approaches can play an important role in improving our understanding of diseases. I will discuss two critical applications of computation – the use of image processing and computer vision algorithms for quantitative analysis of bioimaging data and molecular modeling of disease-associated proteins. Two examples from my research will be discussed - image analysis of airway epithelial cells under conditions mimicking an asthma attack and computational modeling of conformational preferences of tau protein in Alzheimer’s disease. The presentation is for a general audience – extensive background in computational biology is not assumed. Faculty Candidate Seminar: Analysis and Control for Biological NetworksThursday, March 19, 2009, AbstractThe ultimate goal of studying the systems biology of biological networks is to apply intervention to living organisms for effective treatment of diseases. Starting with a project of comparing protein interaction networks of different organisms, I will present an efficient framework based on hidden Markov models (HMMs) to identify conserved homologous pathways in networks of interest. Finding these common interaction patterns across or within organisms can lead to a better understanding of the regulatory mechanisms underlying various cellular functions. With the regulatory relationship learned either from prior knowledge or interaction measurements, we further analyze long-run genome behavior based on its underlying Markov chain in the framework of the probabilistic Boolean network (PBN) model. The change of steady-state distribution of the Markov chain caused by possible perturbations to a network is the key measure for intervention. We derive analytic results for changes in the steady-state distributions of probabilistic Boolean networks resulting from modifications to the underlying regulatory rules. From these analytic results, we derive intervention strategies to obtain therapeutic benefits for future drug design or gene therapy design. The preliminary results in a network modeling melanoma cell line have shown that our methods can potentially serve as future intervention strategies to identify potential drug targets and design gene-based therapeutic strategies. BiographyXiaoning Qian obtained his Bachelor and Master degrees in Electronic Engineering from Shanghai Jiao-Tong University in China in 1997 and 1999. After receiving his Ph.D. degree in Electrical Engineering for his work on shape-based indexing in medical image databases at Yale University in 2005, he worked as a postdoctoral associate in the Department of Diagnostic Radiology at Yale on several biomedical image analysis projects. In 2007, he joined the Bioinformatics Training Program at Texas A&M University as an associate research scientist in the Department of Electrical and Computer Engineering and a research assistant professor in the Department of Statistics. His current main research focus is to develop statistical and geometric models and relevant algorithms for the inference, analysis, and intervention of biologicalFaculty Candidate Seminar: Heuristics are important for improving the performance of search-based algorithmsMonday, March 16, 2009, AbstractPattern databases are the most common form of memory-based heuristics, and have been well-studied over the last decade. But, in many domains pattern databases are ineffective at improving heuristic estimates. In this talk I will describe several of these domains, including path-finding for commercial video games, and motivate how improved heuristics can be used. I will then present new research on canonical and differential heuristics. These heuristics provide an order of magnitude or larger reduction in search effort over the previous best-known techniques. BiographyNathan Sturtevant is currently an adjunct professor in Computer Science at the University of Alberta, in Edmonton, Canada. He received his bachelor's degree from UC Berkeley and his PhD in from UCLA in 2003. His main research focus is in heuristic search with an interest in single- and multi-player games. Nathan's techniques have been implemented in BioWare's upcoming game, Dragon Age (http://dragonage.bioware.com/). Nathan is also known as the author of the popular 1990s Mac shareware game, Dome Wars.Faculty Candidate Seminar: Creating 3D Animated Human Behaviors for Virtual WorldsFriday, March 06, 2009, AbstractAs we journey through our day, our lives intersect with other people. We see people leaving for work, waiting for trains, meeting with friends, hard at work, and thousands of other activities that we may not even be conscious of. People create a rich tapestry of activity throughout our day, a "human texture". We may not always be aware of this texture, but we would definitely notice if it were missing, and it is missing from many simulations and games. Most crowd simulations to date include only basic locomotive behaviors possibly coupled with a few stochastic actions or are meticulously hand scripted. I will describe an architecture, called CAROSA (Crowds with Aleatoric, Reactive, Opportunistic, and Scheduled Actions), that facilitates the creation of heterogeneous populations for simulations by using a commercial off-the-shelf software package (Microsoft Outlook®), a Parameterized Action Representation (PAR), and crowd simulation software (HiDAC). We incorporate four different broad action types into CAROSA: scheduled, reactive, opportunistic, and aleatoric. Scheduled activities arise from specified roles for individuals or groups; reactive actions are triggered by contextual events or environmental constraints; opportunistic actions arise from explicit goals and priorities; aleatoric actions are random but structured by choices, distributions, or parametric variations. The CAROSA architecture enables the specification and control of actions for more realistic “human textures” in virtual worlds such as buildings and cities, links human characteristics and high level behaviors to animated graphical depictions, and relieves some of the burden in creating and animating heterogeneous 3D animated populations. BiographyJan Allbeck is a Ph.D. candidate in the Department of Computer and Information Science at the University of Pennsylvania. She is also Associate Director of the Center for Human Modeling and Simulation, where she coordinates and participates in the research projects affiliated with HMS as well as coordinating the operational aspects of the lab facility, the SIG Center for Computer Graphics. HMS is a part of CG@Penn which also includes the Digital Media Design undergraduate program and a masters program, Computer Graphics and Game Technology. She has a Bachelors degrees in Mathematics and Computer Science from Bloomsburg University and a Masters degree in Computer Science from Penn. She has had the great opportunity to explore many aspects of computer graphics, but is most drawn to research at the crossroads of animation, artificial intelligence, and psychology in the simulation of virtual humans. Her current research focuses on the creation and simulation of functional crowds.SANG/GRAND Seminar: Online Scheduling of Packets with Deadlines in a Bounded BufferTuesday, March 03, 2009, AbstractMotivated by the Quality-of-Service buffer management problem, we consider online scheduling of packets with deadlines in a size-bounded buffer. This model is called bounded-buffer model. Time is discrete. Packets arrive at a buffer over time. Each packet p has an integer release time r_p, a non-negative value w_p, and an integer deadline d_p. d_p specifies the time by which p should be sent. If p is transmitted by its deadline d_p, p contributes our objective its value w_p. At any time, the buffer can store no more than b packets. In each time step, at most one packet can be sent. This model is preemptive: packets already existing in the buffers can be dropped at any time before they are sent and the dropped packet cannot be delivered any more. Our objective is to maximize the total value of the packets sent by their deadlines. This bounded-buffer model generalizes the bounded-delay model proposed in (INFOCOM 00, CISS 01, STOC 01) in which the buffer's size b is assumed larger than any packet's slack time (a packet p's slack time is defined as d_p - r_p). In SWAT 06, Azar and Levy consider a model called multi-buffer model with multiple size-bounded buffers. The lower bound of competitive ratio 1.618 (INFOCOM 00, CISS 01, Algorithmica 03) for the bounded-delay model applies to the multi-buffer model. The authors (Azar and Levy, SWAT 2006) developed a deterministic 9.82-competitive algorithm which applies to the bounded-buffer model as well. For the bounded-buffer model, we present a deterministic 3-competitive online algorithm and a randomized 2.618-competitive online algorithm. We also show that the lower bound of competitive ratio for a broad family of deterministic algorithms is improved from 1.618 to 2. Short BioDr. Fei Li is an assistant professor at Computer Science Department of George Mason University since Fall 2007. His major research interests are online algorithms, approximation algorithms, randomized algorithms and online learning algorithms. He got his PhD in February 2008 from Columbia University, in computer science.Faculty Candidate Seminar: Highly Interactive Scalable Virtual WorldsFriday, February 27, 2009, AbstractThe arrival, in the past decade, of commercially successful virtual worlds used for online gaming and social interaction has emphasized the need for a concerted research effort in this media. A pressing problem is that of incorporating ever more elaborate gaming scenarios into virtual worlds while ensuring player numbers can be measured in the millions. In this talk I will describe the work I have led over the past five years in this area. The development of a highly scalable platform for online gaming will be described and a number of performance results presented BiographyGraham Morgan is a lecturer in the School of Computing Science. He received his PhD in Computing from Newcastle University in 2000. He was appointed to a Lecturer position in September 2000 and is a member of the Distributed Systems Research Group. He is currently a visiting faculty member with the Department of Computer Science at George Mason University.Dr. Morgan’s interests are in : game engineer technologies, online gaming, physics simulations, fault-tolerant computing, scalable server-side clustered solutions, collision detection, group communications, distributed transactions. SANG Seminar: One Cell is Enough to Break Tor's AnonymityFriday, February 20, 2009, AbstractTor is a real-world, circuit-based low-latency anonymous communication network, supporting TCP applications over the Internet. In this talk, we will present a new class of attacks, protocol-level attacks, against Tor. Different from existing attacks, these attacks can confirm anonymous communication relationships quickly and accurately by manipulating one single cell and pose a serious threat against Tor. In protocol-level attacks, a malicious entry onion router may duplicate, modify, insert, or delete cells of a TCP stream from a sender. The manipulated cells traverse middle onion routers and arrive at an exit onion router along a circuit. Because Tor uses the counter mode AES (AES-CTR) for encrypting cells, the manipulated cells disrupt the normal counter at exit onion routers and decryption at the exit onion router incurs cell recognition errors, which are unique to the investigated protocol-level attacks. If an accomplice of the attacker at the entry onion router also controls the exit onion router and recognizes such cell recognition errors, the communication relationship between the sender and receiver will be confirmed. Protocol-level attacks can also be used for launching the denial-of-service (DoS) attack to disrupt the operation of Tor. We systematically analyze the impact of these attacks. We have implemented these attacks on Tor and our experiments validate their effectiveness and efficiency. We also present guidelines for defending against such attacks. Speaker's bioDr. Xinwen Fu is an assistant professor in the Department of Computer Science, University of Massachusetts Lowell. He received his B.S. (1995) and M.S. (1998) in Electrical Engineering from Xi'an Jiaotong University, China and University of Science and Technology of China respectively. He obtained his Ph.D. (2005) in Computer Engineering from Texas A&M University. Dr. Fu's current research interests are in network security and privacy, information assurance, computer forensics, system reliability and networking QoS. He has been publishing papers in conferences such as IEEE Symposium on Security and Privacy (S&P), IEEE International Conference on Computer Communications (INFOCOM) and IEEE International Conference on Distributed Computing Systems (ICDCS), journals such as IEEE Transactions on Parallel and Distributed Systems (TPDS), and book chapters. His research is supported by NSF.CS/GRAND Seminar: Lifelines2: Interactive Visualization of Temporal Categorical DataTuesday, February 17, 2009, AbstractAs large data repositories of temporal data become more prevalent today, it also becomes more important to develop appropriate techniques to support visual exploratory tasks on this type of data. Although much work has been done to develop techniques for numerical time series, temporal categorical data has been mostly overlooked. This type of data is best characterized by events that have names and time stamps. To be able to study the ordering of events and the prevalence of ordering can reveal interesting relationships among the different events, and consequently help analysts formulate new hypotheses, gain new insights. I present Lifelines2, an interactive visualization system designed for visual analysis of temporal categorical data across multiple records. At the center of Lifelines2 is the Align-Rank-Filter (ARF) framework. It allows users to quickly manipulate how they see the data by their features. Alignment lets users specify a reference event, and subsequently change the view of data to be relative to that event. This facilitates the discovery of important temporal relationships associated with the reference events. Rank and Filter are old ideas that let users reorder and trim the data. Coupled with alignment, however, they also offer new affordances to support more sophisticated exploratory tasks. In this talk, I present the features of Lifelines2, and show a video on how a medical researcher might use Lifelines2 to identify patients who exhibit a certain pattern of medical events. I will also present the results from our controlled study, which shows that the alignment feature is instrumental in aiding users to perform complex tasks. Finally, I will talk about the first impressions of Lifelines2 from our collaborators, and peek at our future research on the topic. Short BioTaowei David Wang is a Ph.D candidate in the Department of Computer Science in the University of Maryland. He is part of the Human Computer Interaction Lab, and is advised by Ben Shneiderman. His dissertation topic is on interactive visualization techniques of temporal categorical data for the purpose of hypothesis generation. He is currently working closely with physicians and clinicians on searches over electronic health records for this purpose, and is scheduled to graduate in the winter of 2009.SANG Seminar: Preventing SQL Injection Attacks: A Policy-based Data Type CheckingFriday, February 13, 2009, AbstractSQL injection attacks (SQLIAs) use maliciously crafted SQL input to force web application to function differently from what the query designed to be. Several researchers have developed intrusion prevention techniques based on input validation, learning, or static analysis. A weakness of these techniques is that they primarily focused on identifying malicious input, but not the output. To address this weakness, we develop a policy-based type checking approach that first identifies all the database access points, then use security policy to enforce each of them. The novelty of our approach, as compare to other SQLIAs prevention techniques, is that it focuses on the meaning of the query and the necessary information sending between the program and the database. An interesting aspect of our technique is that when the policies integrate with the control flow graph of user of different privilege level, it can significantly increase the precision of prevention. To evaluate the effectiveness and the performance of our system, we implemented a prototype system which tested by real SQL attacks. We demonstrate that our approach is robust enough and holds promise for more precise detection. BioAnyi Liu is a Ph.D. student in the Department of Information and Software Engineering/Computer Science at George Mason University. He received a BS and MS in Computer Science from Dalian University of Technology, China, in 1997 and 2001, respectively. He is now pursuing a Ph.D. in Information Technologies from George Mason University. His research interests include information security, intrusion detection/prevention, and security issues of web applications.GRAND Seminar: A Survey of Approximate Convex Hull AlgorithmsTuesday, Feburary 10, 2009, AbstractThe convex hull of a point set S, often denoted as conv(S), is the smallest convex set that contains S. This essentially means that a line connecting any pair of vertices in S is enclosed by conv(S). This talk will introduce the convex hull problem and briefly survey existing state of the art for exact algorithms. The crux of the discussion, however, will focus on the current state of affairs of approximation algorithms for the convex hull. The talk might also touch upon related issues such as kinetization and dynamization of these algorithms and the core-set framework as time permits. Short BioRaimi Rufai is a doctoral student in the CS Department, George Mason University. His research interests span Computational Geometry, Software Engineering and enterprise software development and modeling. He is currently working on his dissertation in Computational Geometry under the tutelage of Prof. Dana Richards.SANG Seminar: Sampling Attacks Against Hidden Web DatabasesFriday, January 30, 2009, AbstractA large number of online databases are hidden behind form-like interfaces which allow users to execute search queries by specifying selection conditions in the interface. Most of these interfaces return restricted answers (e.g., only top-k of the selected tuples), while many of them also accompany each answer with the COUNT of the selected tuples. We shall present techniques which leverage the COUNT information to efficiently acquire unbiased samples of the hidden database. We also discuss variants for interfaces which do not provide COUNT information. * Collaborative work with Arjun Dasgupta and Dr. Gautam Das of the University of Texas at Arlington BioDr. Nan Zhang is an Assistant Professor of Computer Science at the George Washington University. Prior to joining GWU, he was an assistant professor of Computer Science and Engineering at the University of Texas at Arlington from 2006 to 2008. He received the B.S. degree from Peking University in 2001 and the Ph.D. degree from Texas A&M University in 2006, both in computer science. His current research interests span security and privacy issues in databases, data mining, and computer networks, including privacy and anonymity in data collection, publishing, and sharing, privacy-preserving data mining, and wireless network security and privacy. He received the NSF CAREER award in 2008.Software Engineering Seminar: GMU Software Engineering Seminar SeriesWednesday, January 28, 2009, AbstractNumerous properties of an increasing number of sites on Earth are now thoroughly measured due to routinization of remote sensing and the progress in the GIS techniques. This new found richness of geospatial data in conjuncture with intelligent data processing transforms our understanding of geospatial phenomena. This project seeks to contribute to this trend by developing methods for auto-modeling causal relationships that are present between geographically collocated geo-variables but have been difficult or impossible to identify using traditional methods. Specifically, the project aims at providing the scientific community with an efficient tool for auto-analyzing the root causes behind observed patterns in geospatial data. We propose to integrate techniques from association analysis, reinforcement learning, and similarity measurement to design a tool that provides a domain expert with a complete yet comprehensible empirical model of an observed phenomenon. Novel solutions are required at all stages of the method development: (i) integration of geospatial data into the format suitable to association analysis, (ii) determining a scope and footprint of the studied phenomenon, (iii) selecting patterns of controlling factors that are indicative of the phenomenon, and (iv) summarizing the patterns into the products which are of immediate use to a domain experts. Speaker's BioWei Ding is an Assistant Professor of Computer Science at the University of Massachusetts Boston. She received her M.Sc. Degree in Software Engineering from the George Mason University in 2000 and her Ph.D. degree in Computer Science from the University of Houston in 2008. Her main research interests include Data Mining, Machine Learning, Artificial Intelligence and with applications to astronomy, geosciences, and environmental sciences.GRAND Seminar: Reciprocal Velocity Obstacles for Real-Time Multi-Agent NavigationTuesday, January 27, 2009, AbstractWe propose a new concept ---the "Reciprocal Velocity Obstacle"--- for real-time multi-agent navigation. We consider the case in which each agent navigates independently without explicit communication with other agents. Our formulation is an extension of the Velocity Obstacle concept, which was introduced for navigation among (passively) moving obstacles. Our approach takes into account the reactive behavior of the other agents by implicitly assuming that the other agents make a similar collision-avoidance reasoning. We show that this method guarantees safe and oscillation-free motions for each of the agents. We apply our concept to navigation of thousands of agents in densely populated environments containing both static and moving obstacles, and we show that real-time and scalable performance is achieved in such challenging scenarios. Short BioMSc: University of Groningen, The Netherlands PhD: University of Utrecht, The Netherlands. Advisor: prof. Mark Overmars currently: Postdoctoral Researcher at University of North Carolina with profs. Dinesh Manocha and Ming Lin next year: Postdoctoral Researcher at UC Berkeley with prof. Ken GoldbergINFS 519 and SWE 510 Foundation Test-out ExamsFriday, January 16, 2009, AbstractJanuary 16, Science & Technology II Room 9 INFS 519: 2:00 PM SWE 510: 3:30 PM Exam Preparation In preparation for an examination, you may wish to review the following textbooks. INFS 519: Program Design and Data Structures Data Structures and Problem Solving Using JAVA, by Weiss, published by Addison-Wesley, ISBN: 0-201-74835-5. Syllabus o Chapter 1: Primitive Java o Chapter 2: References o Chapter 3: Objects and Classes o Chapter 4: Inheritance o Chapter 5: Algorithm Analysis o Chapter 6: Collections API o Chapter 7: Recursion o Chapter 8: Sorting Algorithms o Chapter 11: Stacks and Compilers o Chapter 14: Graphs o Chapter 16: Stacks and Queues o Chapter 17: Linked Lists o Chapter 18: Trees o Chapter 19: Binary Search Trees o Chapter 20: Hash Tables o Chapter 21: Priority Queue: The Binary Heap SWE 510: Object-Oriented Programming in Java Java Gently, by Judith Bishop, 3rd Edition, Addison-Wesley, 2001, ISBN: 0-201-71050-1. Syllabus o Chapter 1: Introduction o Chapter 2: Basic of Object Orientation o Chapter 4: Input and Output o Chapter 5: Flow of Control o Chapter 6: Arrays and Tablees o Chapter 9: Abstraction and Inheritance o Chapter 10: Graphics and User Interfaces o Chapter 11: Event-driven Programming o Chapter 12: Applets and Servlets o Chapter 13: Multithreading INFS 501 and INFS 515 Foundation Test-out ExamsThursday, January 15, 2009, AbstractJanuary 15, Science & Technology II Room 9 INFS 501: 2:00 PM INFS 515: 3:30 PM Exam Preparation In preparation for an examination, you may wish to review the following textbooks. INFS 501: Discrete Math Discrete Mathematics with Applications, third edition, by Susanna S. Epp, Published by Brooks Cole, ISBN: 0-534-94446-9. Syllabus o Chapter 1: The Logic of Compound Statements: 1.1, 1.2, 1.3 o Chapter 2: The Logic of Quantified Statements: 2.1, 2.2, 2.3, 2.4 o Chapter 3: Elementary Number Theory and Methods of Proof: 3.1, 3.2, 3.3, 3.4, 3.5, 3.6 o Chapter 4: Sequences and Mathematical Induction: 4.1, 4.2, 4.3 o Chapter 5: Set Theory: 5.1, 5.2, 5.3 o Chapter 7: Functions: 7.1, 7.2, 7.4 o Chapter 8: Recursion: 8.1, 8.4 o Chapter 9: O-Notation and the Efficiency of Algorithms: 9.1, 9.2, 9.3, 9.4 o Chapter 10: Relations: 10.1, 10.2, 10.3, 10.5 o Chapter 11: Graphs and Trees: 11.1, 11.2, 11.4, 11.5 o Chapter 12: 12.2 INFS 515: Computer Organization The Essentials of Computer Organization and Architecture, 2nd Edition, Linda Null and Julia Lobur, Jones and Barlett Publishers, 2006, ISBN: 0-7637-3769-0. Syllabus o Chapter 1: Introduction - Historical Overview o Chapter 2: Data Representation o Chapter 3: Boolean Algebra and Digital Logic o Chapter 4: MARIE o Chapter 5: Instruction set Architectures o Chapter 6: Memory Concepts o Chapter 7: Input/Output and Storage Systems o Chapter 8: System Software o Chapter 9: Alternative Architectures o Chapter 10: Embedded Systems o Chapter 11: Performance Measurement and Analysis New Graduate Student OrientationWednesday, January 14, 2009, AbstractFor the fourth year, the Volgenau School of Information Technology and Engineering is welcoming its newly admitted graduate students to a special orientation event. Although orientation is not mandatory, it is highly recommended that both domestic and international students plan to attend. Essential information regarding university services for graduate students and program information from academic departments will be provided. Also, this is your opportunity to meet your peers, the administrative and academic staff members who will assist you during the pursuit of your graduate course work and degree. Students admitted for the Spring 2009 semester: Date: Wednesday, January 14, 2009 Time: 5:30-8PM Location: Fairfax Campus, Enterprise Hall, Room 80 The following departments and majors will be represented: * Applied Information Technology * Civil, Environmental & Infrastructure Engineering * Computer Science * E-Commerce * Electrical & Computer Engineering * Information Security & Assurance * Information Systems * Information Technology * Real Estate Development * Software Engineering * Statistics * Systems Engineering & Operations Research * Telecommunications RSVP Please RSVP online for orientation by visiting: http://ite.gmu.edu/graduateresearch/responseform/ SANG Seminar: Bluetooth Security: Overview, Analysis, and Research OpportunitiesFriday, December 05, 2008, AbstractBluetooth is one of the most widely available wireless technologies with over 1.5 billion Bluetooth-enabled devices shipped. Used by cell phones, laptops, gaming consoles and many other devices, it is the predominant wireless personal area networking technology. With the publication of the Bluetooth 2.1 specification in July 2007, a number of security enhancements were introduced by the Bluetooth Special Interest Group (SIG) that are designed to make Bluetooth products more secure yet easier to use. However, there are still residual security issues that need to be researched. This presentation will provide a technical background on how Bluetooth works, and then dive into the inner workings of the native security mechanisms - including new v2.1 features such as Secure Simple Pairing and Security Mode 4. This will culminate in a discussion of interesting Bluetooth security research opportunities. Speaker's BioJohn Padgette, an Associate with Booz Allen Hamilton, has over 17 years of Information Technology experience and has spent the last 5 years focused on wireless security challenges. His Bluetooth experience includes in-depth link security analysis of Bluetooth-enabled smart card readers and headsets for use with handheld devices and PCs.John is co-author of the NIST Special Publication 800-121 Guide to Bluetooth Security as well as a contributor to the DoD Security Requirements for Bluetooth-enabled Smart Card Readers and Headsets. He is also currently Co-Chair of the Bluetooth SIG's Security Experts Group. John holds Master's degrees in Computer Science and Mechanical and Aerospace Engineering. He is currently pursuing a PhD in Information Security at George Mason University. John also holds several professional certifications including CISSP, CWSP, CWNA, and CCNA. Non-Degree Open HouseWednesday, December 03, 2008, AbstractThe Volgenau School of IT & Engineering offers non-degree students the opportunity to learn about graduate programs and apply as a non-degree student. Admissions decisions are guaranteed within 5 business days for attendees who complete their applications at the event. Eligibility Disclaimer: US Citizens, Permanent Residents, and individuals with H or A visas are eligible for non-degree studies. Individuals seeking or holding F1 or J1 visas are not eligible for non-degree status, but may apply for any of our degree programs. A presentation will be given, light refreshments will be served, and you will have an opportunity to meet with Computer Science Department faculty who will answer your questions. Please RSVP at: http://volgenau.ite.gmu.edu/graduateresearch/responseform/ Directions/Map: http://coyote.gmu.edu/map Parking: http://www.gmu.edu/univserv/parking/visitors For complete details of the event: http://volgenau.ite.gmu.edu/graduates/non_degree_open_house.php PhD Dissertation Defense: Learning of Mixed-Initiative Human-Computer Interaction ModelsTuesday, December 02, 2008, AbstractMixed-initiative interaction facilitates a collaboration between intelligent agents and their users that takes advantage of their complementary capabilities by supporting each of them in taking the initiative to perform the tasks for which they are most qualified, at the appropriate time. This thesis presents a learning-based approach to the development of mixed-initiative interaction models that govern the interaction between an end-user and a multi-agent system consisting of a collection of knowledge-based assistants specialized in helping the user perform different tasks. In general, developing such interaction models is a software engineering task of programming complex interfaces. Our approach transforms this software engineering task into a knowledge engineering one of representing the interaction models into a knowledge base. Moreover, the knowledge engineer does not need to manually define the reasoning rules that govern the user-agent interactions. Instead, the knowledge engineer teaches the agent how to interact with the user based on specific interaction scenarios from which the agent learns general interaction rules. This learning ability allows the agent to also adapt to the changing needs and preferences of the user. At the basis of our approach is a task analysis methodology that results in the learning of executable interaction models by the mixed-initiative assistants. It includes general methods and guidelines for translating conceptual interaction plans into interaction models executable by a state-based interaction engine, the conceptualization of the interactions into an interaction ontology, and the adaptation and application of methods for learning general problem solving rules to the learning of general interaction patterns. The task analysis methodology is supported by a general architecture for the mixed-initiative interaction of a multi-agent system. We have developed two assistants in this architecture, the Assumption Assistant and the Modeling Assistant, each with its own interaction model. The Assumption Assistant helps its user to solve problems in application domains with incomplete or uncertain information, by facilitating the definition of hypothetical solutions to the unsolved sub-problems. The Modeling Assistant helps a user to extend the partial reasoning tree generated by an agent by suggesting plausible ways to reduce unsolved problems. The mixed-initiative interaction framework developed and its associated methods have been implemented as an extension of the Disciple learning agent shell. This shell allows subject matter expert to teach an agent how to solve problems in an application domain. Our mixed-initiative methods allow a knowledge engineer (and the expert) to teach the agent how to more efficiently interact during the problem solving process. GRAND/SANG Seminar: AITVS: Advanced Interactive Traffic Visualization SystemFriday, November 21, 2008, AbstractThe explosive growth of spatial data obtained by government agencies and research institutes has created a need for next generation spatial analysis tools that can automatically transform the collected data into useful information and knowledge. Spatial data mining is concerned with the discovery of interesting and useful but implicit knowledge from spatial data. Visualization is the process of visually exploring data for identifying patterns and trends. Visualization and mining techniques allow organizations and companies to extract practical information from the vast amount of data they have gathered, thus helping them make effective decisions. We have developed the Advanced Interactive Traffic Visualization System (AITVS), a web-based visualization system, for observing and analyzing the summarization of spatiotemporal patterns in transportation data. Existing transportation visualization systems exhibit some useful but limited tools for in-depth exploration, and do not provide the critical instruments for comprehensive study. AITVS mitigates the shortcomings of existing systems by provides a rich set of multidimensional visual components for real-time and historical traffic data analyses. In addition, through the combination of advanced optimization techniques and the delegation of visual data processing, AITVS can achieve the quick response times of 1-5 seconds for complex queries. The discovered traffic patterns and rules from AITVS can assist decision-making for transportation managers, establish traffic models for researchers and planners, and allow commuters to select optimal commuting routes. The traffic data of I-66 and I-95 in Metropolitan Washington region are used to demonstrate the concepts. BioDr. Chang-Tien Lu is an Associate Professor in the Department of Computer Science at Virginia Polytechnic Institute and State University. He received an M.S. degree from the Georgia Institute of Technology, and a Ph.D. degree from the University of Minnesota. He served as Program Chair for the 2006 IEEE International Conference on Tools with Artificial Intelligence and the 2007 IEEE International Workshop on Spatial and Spatial-temporal Data Mining. Dr. Lu's research work focuses on emerging requirements for storing, analyzing, exchanging, visualizing, and disseminating spatial (and spatio-temporal) data in geospatial applications. His research group has developed several web-based spatial analysis and visualization systems for managing and mining various kinds of spatial information. Specific projects include discovering spatial anomalies, identifying recurrent or unexpected events, and predicting future trends. His research projects have been sponsored by the Department of Defense, the Virginia Department of Transportation, and the Virginia Transportation Research Council.CS Seminar: Analysis and modelling of complex biological systemsWednesday, November 19, 2008, AbstractBiological systems are very complex and present a great variety of scientific challenges. Is it really possible to find novel drug targets by analysing protein interaction networks of bacteria and their hosts? Can we understand how and why selfish individuals share their precious resources with others and cooperate regularly? How do neural systems work to generate wide ranges of complex behaviours in animals? This talk will present results that indicate some answers to these question. First, we show how network analysis methods can be used to identify structural integrity vulnerabilities in protein interaction networks that correspond to actual and potential antibiotic targets. Second, we discuss agent-based simulations to analyse the role of uncertainty in the evolution of cooperative behaviour. Third, we present results of high spatio-temporal resolution optical imaging of the crab stomatogastric ganglion (STG) using voltage-sensitive dyes. This technique allows simulatenous recording of many (possibly all) neurons in this small neural system (26 neurons) which generates many muscle driving rhythms. This makes possible to analyse at single neuron resolution details the interactions of many neurons and can help revealing of how this relatively simple but still complex neural system works. BioDr Peter Andras studied computer science (BSc, 1995), artificial intelligence (MSc, 1996), and mathematical analysis of neural networks (PhD, 2000) at the Babes-Bolyai University, Cluj, Romania. He worked in the Department of Computer Science at the University of Maastricht (Netherlands, 1998-2000) and the Department of Psychology of the Newcastle University (UK, 2000-2002) before joining as Lecturer (Assistant Professor) the School of Computing Science of the Newcastle University in 2002. In 2005 he was promoted to the rank of Reader (Associate Professor).His research interests are in the area of information processing in complex systems. His work includes analysis of protein interaction systems, analysis and modelling of neural systems, network analysis of organisations, and applications of network analysis and computational intelligence methods in a range of areas (e.g. ecosystem analysis, financial predictions, etc). He has one patent, and published two books, and over 70 scientific papers in journals, edited volumes, and conference proceedings. He is on the editorial boards of two scientific journals, participated in the organisation of many international conferences (e.g. recent ICANN, IJCNN conferences), and has been member of the Executive Board of the European Neural Network Society (2004-2007). His work contributed to the formation of a university spin-out company in the area of computational biology and drug development (the company has been introduced to the stock exchange in November 2007). He is currently working on the formation of another spin-off company in the area of e-commerce. PhD Dissertation Defense: Virtual Human Anatomy and Surgery SystemsTuesday, November 18, 2008, AbstractHistorically, medical students have practiced on cadavers to learn human anatomy, as have physicians wanting to brush up on their knowledge. However, because of storage cost and limited availability of cadavers, practice on cadavers has proven problematic. As computers become more powerful, medical professors have dreamed of a day when they will be able to dissect bodies with the assistance of virtual reality. We have developed the Virtual Human Anatomy and Surgery System (VHASS) as a potential solution. VHASS uses cryosection images (natural-color images generated by slicing a frozen cadaver) to reconstruct computerized three-dimensional cadavers. VHASS enhances human anatomy education by creating three-dimensional volume models that include details of human organs, giving medical students and physicians unlimited access to realistic virtual cadavers. Major components in VHASS include three-dimensional virtual humans, direct volume rendering of virtual humans, surface models of segmented human parts, and real-time manipulation on virtual humans. Direct volume rendering on un-segmented cryosection images is still an open research topic. Different from traditional volume rendering, which uses transfer functions to map scalar values to colors and opacity, direct volume rendering on cryosection images needs efficient transfer functions mapping vectors to opacity, which is complicated by the non-linearity of color space. We have created a series of new transfer functions for volume rendering on un-segmented cryosection images. To create human part surface models, we separate human tissues within cryosection images, dissect all human organs according to their anatomic structures, and reconstruct a three-dimensional volume model for each part. VHASS renders each part as a high-resolution, natural-appearance three-dimensional model and labels it properly to facilitate learning. This enables users to group different parts to better understand human anatomy. VHASS allows real-time interactions, such as drilling, scanning and slicing on human parts. We re-generate human part surface models at run-time for deforming interactions. We have analyzed the limitation of the well-known Marching Cubes algorithm and modified the algorithm to work with our data. We also have developed a new neighbor-based surface reconstruction algorithm, which has the same performance as the Marching Cubes algorithm but without the limitation of the Marching Cubes method. For better performance, the new algorithm has been ported onto the new graphics hardware using the geometry shader. Our implementation on the geometry shader serves as an example of exploiting the new GPU parallel processing hardware. VHASS supports stereo rendering, haptic interaction, tracking and three-dimensional content production. Using the Sharp three-dimensional display on a laptop, VHASS provides low-cost, portable stereo rendering of human parts without the requirement of special glasses. Integrating with large size stereo projector and ultrasonic trackers, VHASS allows people to manipulate human parts in the immersive stereo environment. By integrating SensAble Onmi haptic device, VHASS enables people to feel the touch on human parts. VHASS integrates three-dimensional content creation by allowing students to print out physical models of human parts. Dissertation director: Dr. Jim X. ChenSecurity Seminar: Physical Security Controls and WeaknessesTuesday, November 18, 2008, AbstractPhysical security is an oft-overlooked component of data and system security in the technology world. While frequently forgotten, it is no less critical than timely patches, appropriate password policies, and proper user permissions. You can have the most hardened servers and network but that doesn't make the slightest difference if someone can gain direct access to a keyboard or, worse yet, march your hardware right out the door. Those who attend this session will leave with a full awareness of how to best protect buildings and grounds from unauthorized access. Discussion as well as direct example will be used to demonstrate the grave failings of low-grade hardware... much of which will be opened by audience members with no prior training. What features to look for in locks and safes will be covered, and how to invest in systems that are easiest to manage in large environments will be discussed. PhD Dissertation Defense: Secure Data Aggregation in Wireless Sensor NetworksFriday, November 14, 2008, AbstractWireless sensor networks have proved to be useful in several applications, such as environment monitoring and perimeter surveillance. In a large sensor network, in-network data aggregation (i.e., combining partial results at intermediate nodes during message routing) significantly reduces the amount of communication and energy consumption. Recently, the research community has proposed a robust aggregation framework called synopsis diffusion which combines multi-path routing schemes with duplicate-insensitive algorithms to accurately compute aggregates (e.g., Count, Sum) in spite of message losses resulting from node and transmission failures. However, this aggregation framework does not address the problem of false sub-aggregate values contributed by compromised nodes resulting in large errors in the aggregate computed at the base station, which is the root node in the aggregation hierarchy. This is an important problem since sensor networks are highly vulnerable to node compromises due to the unattended nature of sensor nodes and the lack of tamper-resistant hardware. In this thesis, we make the synopsis diffusion approach secure against attacks in which compromised nodes contribute false sub-aggregate values. In particular, we present two classes of algorithms to securely compute Count or Sum. First, we propose a lightweight verification algorithm which enables the base station to determine if the computed aggregate includes any false contribution. Second, we present attack-resilient computation algorithms which can be used to compute the true aggregate by filtering out the contributions of compromised nodes in the aggregation hierarchy. Thorough theoretical analysis and extensive simulation study show that our algorithms outperform other existing approaches. This thesis also addresses the security issues of in-network computation of Median, and presents verification algorithms and attack-resilient computation algorithms to securely compute an approximate estimate of this aggregate. To the best of our knowledge, prior to this dissertation there was no other work related to the security of in-network computation of Median. We evaluate the performance and cost of our algorithms via both analysis and simulation. The results show that our approach is scalable and efficient. Dissertation directors: Dr. Sushil Jajodia and Dr. Sanjeev SetiaJoint Volgenau School/CS Seminar: Performance Engineering in Secure Distributed SystemsFriday, November 14, 2008, AbstractOver the last 10 years, my research has focused on issues in performance engineering of secure distributed systems. In this talk, I will provide an overview of my research, while discussing some selected contributions in greater detail. Specifically, I will discuss my research on supporting secure communication in both wide-area networks as well as emerging networks such as mobile ad hoc networks (MANETs) and wireless sensor networks. I will also describe a recent project on reliable bulk data dissemination in sensor networks, and discuss future research directions. Speaker BioSanjeev Setia is an Associate Professor in the Computer Science Department at George Mason University. He received his PhD from the University of Maryland, College Park in 1993. His research interests are in ad hoc and sensor networks, network security and performance evaluation of computer systems. In recent years, he has worked extensively on security mechanisms and protocols for ad hoc and sensor networks. He was the founder of the ACM Workshop on Security in Ad hoc and Sensor Networks (SASN) and served as its co-organizer 2003 and 2004. His research has been funded by NSF, NASA and DARPA.Joint CS/GRAND Seminar: Computer Science and Video Games: Teaching and Research in Higher EducationThursday, November 13, 2008, AbstractThis talk will be on how links with the video games industry can strengthen research and teaching in universities. Considering the market worth of commercial video games one may be surprised to find that collaboration between academics and their industrial counterparts in the games industry is not common. Consequently, computer science graduates tend not to satisfy game industry programming requirements and gaming studios rarely interact with universities. To overcome such a scenario requires time and effort, but the rewards of collaboration between the video games industry and universities can be significant in terms of student teaching and research initiatives. Speaker BioGraham Morgan gained his PhD in the area of distributed systems and continues to work in this area, creating tools and techniques to ease the development of highly available Internet applications. Over the past few years the video games industry presented a series of case studies which Graham used to highlight his distributed systems work. Working with the games industry in the UK, Graham has created a number of university level courses and programs to help ensure students are sufficiently qualified to succeed in the video game industry. |
