Sourish Chakravarty

Sourish is currently a Translational Disease Modeling scientist working in pharmaceutical industry. His work involves developing/applying quantitative pharmacology and disease progression models to inform the drug development process. He is passionate about contributing towards improving patient care using maths, computers and principles from engineering, biology, and pharmacology. Some topics that he is interested in are: closed-loop therapeutics, statistical signal processing, multiscale modeling and uncertainty quantification.

Sourish completed his postdoctoral training at MIT under the mentorship of Emery N. Brown. He received his doctoral degree in Mechanical Engineering from The State University of New York at Buffalo and his undergraduate education from the Indian Institute of Technology (IIT), Kharagpur.

Sourish's translational neuroengineering postdoc research focus was on (1) Closed-loop control of anesthesia with experimental validation in non-human primates (collaboration with Earl Miller@MIT), and (2) State-space modeling of neural signals with emphasis on dynamic functional connectivity analysis of multimodal functional neuroimaging data (co-mentored by Brian Edlow@MGH). His closed-loop control of anesthesia work received a 2nd place poster award in the 2020 Quantitative Systems Pharmacology summit.

Sourish's mechanical engineering PhD research focus was primarily on multiscale mechanical analyses of elastic composite solids (Dissertation: "Multiscale material modeling using variational principles and random matrix theory"). His PhD research also yielded computational tools to analyze mechanical response in couple-stress continua, and parsimonious models of solitary wave train dynamics in granular chains. His PhD research advisors were Gary Dargush, Sonjoy Das, and Surajit Sen. He is a two-time finalist of the Robert J. Melosh Medal competition for best student paper on finite element analysis.