Machine Learning Approaches for Annotating BioData

When: Monday, February 16, 2015
Where: PGH 232
Time: 11:00 AM

Speaker: Prof. Huzefa Rangwala, George Mason University

Host: Prof. Ioannis Pavlidis

Biological systems are complex and not completely understood. New generation of high-throughput      (“Big Data”) technologies capture large volumes of complex, multi-modal data associated with these systems. Scientific discovery and advancement requires extracting useful information from these datasets, which presents unique and challenging computing problems.  Complexity within biological data arises due to heterogeneity, incompleteness, missing information, noisy nature and inter-dependencies between the input and output domains.

In this talk, I will provide an overview of my contributions related to the development of accurate and efficient mining approaches for annotating these datasets. I will present a multi-task learning approach that seeks to leverage the hierarchical structure present within multiple biological archives for classification. I will provide a highlight of how these developed approaches are integrated within computational pipelines to solve bio-informatics problems and closing off with a summary of current funded projects in the field of prosthetic arm development and learning analytics.

Bio:

Huzefa Rangwala is an Associate Professor at the department of Computer Science & Engineering, George Mason University. He holds an affiliate appointment with the Bioengineering Department and the School of Systems Biology, George Mason University. He received his Ph.D. in Computer Science from the University of Minnesota in the year 2008. His research interests include machine learning, 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.