-------- Original Message --------
Subject: VSE Seminar: Machine Learning Approaches for Annotating
Biological Data- Wed 10/9, 2pm, Research Hall 163-
Date: Tue, 1 Oct 2013 16:45:32 -0400
From: Nooshi Mohebi <[log in to unmask]>
To: [log in to unmask] <[log in to unmask]>
*Machine Learning Approaches for Annotating Biological Data*
Wednesday, October 9th, 2013
2:00pm
Research Hall, Room 163
Dr. Huzefa Rangwala
Department of Computer Science, George Mason University
/Abstract/
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 biological 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
also describe an approach for modeling of sequential data. I will
provide a highlight of how these developed approaches are integrated
within computational pipelines to solve biological problems as they
relate to the fields of metagenomics (or community genomics), protein
function prediction and drug discovery.
/Speaker Bio/
Huzefa Rangwala is an Assistant 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 2013 Volgenau Outstanding Teaching
Faculty Award, 2012 Computer Science Department Outstanding Teaching
Faculty Award and 2011 Computer Science Department Outstanding
Junior Researcher Award. He is Mason's 2014 SCHEV Outstanding Faculty
Award, Rising Star nominee. His research is funded by NSF, NIH,
DARPA, USDA and nVidia Corporation.
Nooshi Mohebi
MSN- 4A5
4400 University Dr
Fairfax, VA 22030
703-993-1585
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