Soumya Ghosh, PhD, is a scientist at IBM Research and an investigator at the MIT-IBM Watson AI lab. His research focuses on the design of flexible statistical models and scalable, efficient inference algorithms for reasoning about noisy, high-dimensional data. His recent work has examined approaches for combining the complementary strengths of Bayesian methods, graphical models, and deep neural networks. His research is exploring use of these tools for better understanding the multi-faceted progression of neurodegenerative diseases and for providing well calibrated estimates of predictive uncertainties.
Dr. Ghosh graduated from Brown University in 2015 with a doctoral degree in computer science and joined IBM research in 2016 after a postdoctoral stint at Disney Research.