I am a Research Staff Member (RSM) at IBM T.J. Watson Research Center. I received MS in Applied Mathematics from Moscow Gubkin Institute, Russia, and PhD in Computer Science from the University of California, Irvine. My primary research interests are in the areas of probabilistic inference, machine learning, and information theory. Particularly, I have done work on approximate inference in graphical models, information-theoretic experiment design and active learning, with applications are in the area of autonomic computing - automated management of complex distributed systems, which includes various diagnosis, prediction and online decision-making problems. My current research is in the area of machine-learning applications to computational biology and neuroscience, with a particular focus on statistical analysis of brain imaging data such as fMRI. In the past years, I taught several graduate courses at Columbia University as an adjunct professor at the Department of Electrical Engineering: Statistical Pattern Recognition (ELEN E6880) in Spring of 2002 and 2003, and Sparse Signal Modeling (ELEN E6898) in Spring of 2011. In Spring 2007, I also taught a machine-learning class on Learning and Empirical Inference (COMS 6998-4) at the Computer Science Department of Columbia. I co-organized several workshops at various machine-learning conferences. I am currently serving on the editorial board of the Artificial Intelligence Journal (AIJ).
Here is my personal webpage.
Recent Press coverage:
- IBM THINK Blog on our recent NPJ Schizophrenia paper: AI Schizophrenia Research
- How Machine Learning Can Improve Treatment of Psychiatric Disorders - Techvibes (2017.07.21)
- IBM and University of Alberta publish new data on machine learning algorithms to help predict schizophrenia -- Amii website (Media Release) (2017.07.21)
- Artificial intelligence can help better diagnose schizophrenia, says U of A and IBM researchers - Edmonton Journal (2017.07.20)
- Machine learning enables new insight into schizophrenia - UofAlberta Science News (2017.07.21)
- U of A research shows faster, more accurate schizophrenia diagnosis possible with artificial intelligence - CBC News (2017.07.21)
- IBM's AI Is Improving Healthcare By Advancing Cancer, Schizophrenia Research - International Business Times (2017.07.21)
- IBM 5 in 5: With AI, our words will be a window into our mental health
- Forget me not: US Patent 9177257
- Collaboration with U. of Alberta: IBM News Release (24 June 2015)
- Computational Psychiatry – Eliminating the Guesswork of Treating Mental Illness, Moods Magazine, Fall 2015 issue
- Mental State Recognition via Wearable EEG: The Stack (3/2/16), Fudzilla.com (2/4/16), Hackaday.com (2/16/16)
7/18/2017 Brain and AI. Pleanry talk at SAI conference.
3/28/2017 Learning About the Brain and Brain-Inspired Learning. Invited talk at MLconf NYC.
12/8/2016 Learning About the Brain: Neuroimaging and Beyond. Plenary talk at NIPS-2016, Barcelona, Spain (talk slides)
11/2015 MLconf @ San Francisco