Dr. Deepayan Chakrabarti

Biography

Deepayan Chakrabarti is an Associate Professor in the Information, Risk, Operations Management (IROM) at the McCombs School of Business, University of Texas at Austin. His research encompasses a broad range of problems in Machine Learning and Data Mining, with a recent focus on analyzing large graphs, social networks, and robust optimization. His work involves model-building, statistical inference, the design of algorithms, and providing theoretical proofs of consistency. Deepayan has developed robust methods that provide high risk-adjusted returns, focusing on optimization techniques that enhance portfolio management. He has extensively researched network community detection and financial analysis, utilizing advanced algorithms such as Nonnegative Matrix Factorization and low-rank methods to uncover hidden factors in data. His studies aim to address the challenges posed by local changes leading to global effects in financial contracts, as well as the difficulties associated with stock-picking based on past performance. Through his innovative approaches, Deepayan has contributed significantly to the understanding and advancement of reliable data-driven methodologies in finance and machine learning.

Research Interests

Experience