•   When: Wednesday, November 08, 2017 from 01:00 PM to 02:00 PM
•   Speakers: Huzefa Rangwala, PhD
•   Location: Johnson Center 334- Meeting Room E
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Abstract: Today we are in the "data'' age. Data-driven science and engineering  are at the forefront of new discoveries and unbounded  positive societal impact. Meaningful  discovery and actionable insights  requires  extracting useful information from large,  heterogeneous  and complex  datasets, ubiquitous across several domains. Complexity within these  datasets  arises due to heterogeneity, incompleteness, missing information, noisy nature and  inter-dependencies between the input and output domains. Structured prediction is a framework for solving classification and regression problems, in which the output/input variables are mutually dependent or constrained. Examples of dependencies and constraints include sequential, combinatorial or spatial structure in the problem domain and capturing these interactions leads to better prediction models. Several real world applications have  dependencies between output labels (multi-label, hierarchical classification), or have an internal structure that is described by inter-dependent components (e.g., sequences, trees, networks, dyadic relationships). 

 In this talk, I will provide an overview of my contributions related to the development  of structured prediction algorithms and their applications. I  will present a sample of my work across multiple  inter-disciplinary applications in (i) educational mining, (ii) genome analysis, (iii) social forecasting and (iv) cyber-physical systems. 

Bio: Huzefa Rangwala is an Associate Professor at the Department of Computer  Science & Engineering, George Mason University. He was a Visiting Faculty Member  at Department of Computer Science, Virginia Tech in 2015-2016. His research interests  include data mining, learning analytics, bioinformatics and high performance computing. He is the recipient of the NSF  Early Faculty Career Award in 2013, the 2014 GMU Teaching Excellence Award, the 2014 Mason Emerging Researcher Creator and Scholar Award, the 2013 Volgenau Outstanding  Teaching Faculty Award, 2012 Computer Science Department Outstanding Teaching Faculty Award and 2011 Computer Science Department Outstanding Junior Researcher Award. His research is funded by  NSF,  NIH, NRL, DARPA, USDA and nVidia Corporation.