Seminars and Events
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SANG Seminar Series

GRAND Seminar Series

Test-out Exam: INFS 501

Tuesday, January 17, 2012
2:00 PM
Eng 4201
Registration is required.

Abstract

Please email your intent to csadmin@cs.gmu.edu. Include your name, G number and the exams you wish to register for. A photo ID must be presented on the day of the exam. Each exam will be one hour in length.

It is important to note that you will be permitted to take each exam one time only. Failure to pass the exam will mean that you MUST take the foundation classes before enrolling in any core curriculum course.

Test-out Exam: INFS 515

Tuesday, January 17, 2012
3:30 PM
Eng 4201
Registration is required.

Abstract

Test-out Exam: INFS 519

Wednesday, January 18, 2012
2:00 PM
Eng 4201
Registration is required

Abstract

Test-out Exam: SWE 510

Wednesday, January 18, 2012
3:30 PM
Eng 4201
Registration is required

Abstract

GTA: Orientation

Thursday, January 19, 2012
11:00AM - 12:00PM
Eng 4201
This event is mandatory for all CS department graduate teaching assistants

SWE Seminar: Atomic Section Analysis Tool (AtSAT)

Friday, January 20, 2012
12:00 pm
Eng 4201
Lima Beauvais, Sr. SWE Pal-Tech Inc.

Abstract

Testing the presentation layer of web applications requires novel methodologies. In general analyzing, modeling, and testing web applications and their three main layers creates challenges. However the testing techniques used for traditional software can be applied to the data computation and data representation layers. This talk discusses the Atomic Section Analysis Tool (AtSAT), which helps to mechanize the process of testing the presentation layer of web applications. AtSAT is based on the proposed framework of Offutt and Wu (2009) and automates seven of the nine steps; reducing the time to apply the methodology and minimizing human errors.

Speaker's Bio

Lima Beauvais earned an MS degree in Instructional Technology at Bloomsburg University, PA in June 2001. He is currently a candidate for the Engineer Degree at GMU, Fairfax, with a concentration on software testing. He worked as a Senior Multimedia Developer at PerformTech, Inc. from June 2001 to November 2007, developing computer-based and web-based courseware. He has been working as a Senior Software Engineer at Pal-Tech, Inc. since November 2007, developing web applications and training packages. He taught seminar classes on multimedia development at the Art Institute of Washington in Arlington, VA and Sanford Brown college in McLean, VA. He is a member of the Corporate Advisory Council (CAC) of the Institute of Interactive Technology at Bloomsburg University.

SWE Seminar: A Tour of the Piazza Discussion Forums

Tuesday, January 24, 2012
12:00 pm
Research I, Rm. 163
Piazza Team

Abstract

Members of the Piazza team are visiting GMU on Tuesday, January 24 for a lunchtime seminar, with lunch provided. They will spend some time demonstrating the site, sharing best practices, and answering any questions.

Piazza is a free online gathering place where students can ask, answer, and explore 24/7, under the guidance of their instructors. Students as well as instructors can answer questions, fueling a healthy, collaborative discussion. Instructors can go into deeper detail on complex topics, and spot areas where students are struggling.

In SWE 432, we found that Piazza streamlined the teaching experience. All those hours spent responding to individual emails can now be put to better use. You will never have to answer the same question twice. Better yet, a student might answer it for you. On top of that, you always have complete editorial control over your class.

Most bulletin boards are organized top-down with the instructor creating and controlling all topics and threads. Piazza allows bottom-up organization by students, leading to a richer, more interactive, more collaborative, and more free learning experience. This leads to more participation from students and more learning by students.

You can read more about Piazza in this article from the New York Times: http://www.nytimes.com/2011/07/04/technology/04piazza.htm. Or you can see demos and sign up at http://www.piazza.com.

CS Dept Colloquium: Searching in Sequences of Documents and in Biological Sequences

Thursday, February 23, 2012
11:00 AM
Eng 4201
Dimitris Gunopulos

Abstract

We consider the problem of searching in two domains where the ordering is important, namely biological sequence data, and data from live, time-stamped data collections (such as blogs). As the number and size of such data collections increase, the problem of efficiently indexing and searching such data becomes more important. We present novel approaches for subsequence matching and for keyword search and event identification in document sequences.

Speaker's Bio

Dimitrios Gunopulos got his PhD from Princeton University in 1995. He has held positions as a Postoctoral Fellow at the Max-Planck-Institut for Informatics, Research Associate at the IBM Almaden Research Center, Visiting Researcher at the University of Helsinki, Assistant, Associate, and Full Professor at the Department of Computer Science and Engineering in the University of California Riverside, and Associate Professor in the Department of Informatics and Telecommunications, University of Athens. His research is in the areas of Data Mining, Knowledge Discovery in Databases, Databases, Sensor Networks, Peer-to-Peer systems, and Algorithms. He has co-authored over a hundred journal and conference papers that have been widely cited and a book. He has supervised 10 Ph.D. theses and 19 MS. His research has been supported by NSF (including an NSF CAREER award), the DoD, the Institute of Museum and Library Services, the Tobacco Related Disease Research Program, the European Commission, AT&T and Nokia. He has served as a General co-Chair in IEEE ICDM 2010, as a PC co-Chair in ECML/PKDD 2011, IEEE ICDM 2008, ACM SIGKDD 2006, SSDBM 2003, and DMKD 2000, and as an associate Editor at KAIS, at IEEE TKDE, at IEEE TPDS, and at ACM TKDD.

Host: Carlotta Domeniconi (carlotta@cs.gmu.edu)

Seminar: Probabilistic Hashing Methods for Fitting Massive Logistic Regressions and SVM with Billions of Variables

Friday, February 24, 2012
11:00AM - 12:00PM
Johnson Center, 3rd Fl, Room B
Ping Li, Department of Statistical Science, Cornell University

Abstract

In modern applications, many statistics tasks such as classification using logistic regression or SVM often encounter extremely high-dimensional massive datasets. In the context of search, certain industry applications have used datasets in 264 dimensions, which are larger than the square of billion. This talk will introduce a recent probabilistic hashing technique called b-bit minwise hashing (Research Highlights in Comm. of ACM 2011), which has been used for efficiently computing set similarities in massive data. Most recently (NIPS 2011), we realized that b-bit minwise hashing can be seamlessly integrated with statistical learning algorithms such as logistic regression or SVM to solve extremely large-scale prediction problems. Interestingly, for binary data, b-bit miwise hashing is substantially much more accurate than other popular methods such as random projections. Experimental results on 200GB data (in billion dimensions) will also be presented.

SWE Seminar: Taming Uncertainty in Self-Adaptive Software

Tuesday, February 28, 2012
12:00 pm
Eng 4201
Naeem Esfahani, Ph.D. Candidate Computer Science

Abstract

Self-adaptation endows a software system with the ability to satisfy certain objectives by automatically modifying its behavior. While many promising approaches for the construction of self-adaptive software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation decisions. This has been one of the key obstacles to wide-spread adoption of self-adaption techniques in risk-averse real-world settings. In this talk, I describe an approach, called POssIbilistic SElfaDaptation (POISED), for tackling the challenge posed by uncertainty in making adaptation decisions. POISED builds on possibility theory to assess both the positive and negative consequences of uncertainty. It makes adaptation decisions that result in the best range of potential behavior.

Speaker's Bio

Naeem Esfahani is a Ph.D. candidate in Computer Science Department, Volgenau School of Engineering. He got his B.Sc. degrees on Electrical and Computer Engineering from University of Tehran in 2005. He also received a M.Sc. degree in Computer Engineering from Sharif University of Technology in 2008. His current research mainly focuses on Software Architecture, Self-Adaptive Software Systems, and Software Quality of Service Analysis & Improvement.