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Gail Rosen is a Professor of Electrical and Computer Engineering in the College of Engineering at Drexel University. She earned her B.S. in 1999, M.S. in 2002, and Ph.D. in 2006, all in Electrical and Computer Engineering from the Georgia Institute of Technology. As a graduate student, she held an NSF Graduate Research Fellowship from 2000 to 2005 and an NSF GK-12 Teaching Fellowship from 2003 to 2004. Prior to her faculty position, she interned at AT&T Research Laboratories in 2000 and MIT Lincoln Laboratories in 2004, served as an associate engineer at Scientific-Atlanta Inc., and co-opped at the Georgia Tech Research Institute. Rosen joined Drexel University in 2006 as an Assistant Professor, advancing to Associate Professor in 2013. She heads the Ecological and Evolutionary Signal-processing and Informatics (EESI) Laboratory, directs the Center for Biological Discovery from Big Data (BD²), and serves as chair of the board of the University Research Computing Facility. She co-organizes the AIME Scholarship program to promote diversity in electrical and mechanical engineering.
Rosen's research interests include machine learning for metagenomics and microbiome studies, prokaryotic evolution and interactions, digital signal processing for biological modeling, chemical source localization and tracking, and bio-inspired designs. Her EESI lab develops methods to analyze metagenomic data from human microbiomes and environmental samples, alongside databases investigating evolutionary mechanisms. Major awards include the NSF CAREER Award (2009-2014), Drexel University Faculty Career Development Award (2011-2012), Drexel Bridge Gap Funding Award, Drexel Equipment Award, and Louis and Bessie Stein Family Fellowship. In 2019, she received an NSF MRI grant for Proteus++, enabling data-intensive computing. Key publications are 'Opportunities and obstacles for deep learning in biology and medicine' (Ching et al., Journal of the Royal Society Interface, 2018; 2845 citations), 'Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis' (Sullam et al., 2012; 1149 citations), 'Comprehensive benchmarking and ensemble approaches for metagenomic classifiers' (McIntyre et al., Genome Biology, 2017; 381 citations), and 'A Sequential Learning Approach for Scaling Up Filter-Based Feature Subset Selection' (Ditzler et al., IEEE Transactions on Neural Networks and Learning Systems, 2018). With over 7900 citations, her work influences computational biology and metagenomics. She serves on the editorial board of BMC Microbiome (2012-present), was associate editor for EURASIP Journal on Bioinformatics and Systems Biology (2015-2017) and IEEE Signal Processing Magazine (2013-2015), chairs the IEEE Philadelphia Section Signal Processing Chapter, and served on the NAIRR Task Force panel in 2022.
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