Speakers:
Yogesh Rathi
Harvard University
Yogesh Rathi received his Ph.D. in Electrical and Computer Engineering in 2006 from Georgia Institute of Technology, Atlanta. His research interests lie in developing smart imaging techniques to understand brain structure and function. He has developed several compressed sensing algorithms for fast imaging of diffusion MRI — a technology that is now being used to obtain advanced MRI scans of children with ADHD (Attention-deficit Hyperactivity Disorder). His current research focus is on 1). Ultra-high resolution diffusion imaging combining acquisition and reconstruction, 2). estimating tissue microstructure from biophysical and stochastic models of diffusion, and 3). time-series analysis for understanding functional connectivity using fMRI, EEG or MEG data. His clinical research focus includes using and developing sophisticated tractography algorithms for precise targeting of deep-brain stimulation (DBS) and transcranial magnetic stimulation (TMS) in obsessive compulsive disorder (OCD), Parkinson’s and major depressive disorder (MDD). His broad research focus is in the areas of signal and image-processing, statistics, control theory, machine learning, computer vision and related applications to solve inverse problems in medical imaging.
Justin Romberg
Professor and Associate Chair
Georgia Institute of Technology
Dr. Justin Romberg is the Schlumberger Professor and the Associate Chair for Research in the School of Electrical and Computer Engineering and the Director of the Machine Learning PhD program at at Georgia Tech.
Dr. Romberg received his Ph.D. in 2004 from Rice University. He was a postdoc in Applied and Computational Mathematics at Caltech, and then joined the Georgia Tech faculty in Fall 2006. He is currently on the editorial board for the SIAM Journal on the Mathematics of Data Science, and is a Fellow of the IEEE.
His research interests lie on the intersection of signal processing, machine learning, optimization, and applied probability.
Sertac Karaman
Associate Professor
Massachusetts Institute of Technology
Sertac Karaman is an Associate Professor at the Massachusetts Institute of Technology. His research interests lie in the broad areas of robotics and control theory. In particular, he studies the foundations and applications of high-performance safety-critical cyber-physical systems. The application areas of his research include driverless cars, unmanned aerial vehicles, distributed aerial surveillance systems, air traffic control, certification and verification of control systems software, and many others.
Alex Dimakis
Associate Professor
University of Texas, Austin
Alex Dimakis is an Associate Professor at the Electrical and Computer Engineering department at UT Austin. He received his Ph.D. in 2008 in EECS from UC Berkeley and a Diploma from NTU Athens in 2003. He received several awards including the James Massey award, NSF Career, a Google faculty award and the Eli Jury dissertation award. His research interests include information theory and machine learning.