Raaz Dwivedi joined Department of Operations Research and Information Engineering and Cornell Tech at Cornell University as an Assistant Professor in Jan 2024. Prior to that, he visited Cornell ORIE in Fall 2023 and spent two years as a FODSI postdoc fellow at Harvard and MIT LIDS, and spent a summer at Microsoft Research New England. He did his Ph. D. In EECS at UC Berkeley in 2021 and bachelors in EE at IIT Bombay in 2014. His research builds statistically and computationally efficient strategies for personalized decision-making with theory and methods spanning the areas of causal inference, reinforcement learning, and distribution compression. He has won a best student paper award for work on optimal compression and teaching awards at UC Berkeley and Harvard.

Research Interests

His research involves a multi-disciplinary approach to data science and brings together ideas from computer science, electrical engineering, and statistics in collaboration with domain experts. His research develops statistical machine learning approaches for personalized decision-making and healthcare applications, with research across causal inference, reinforcement learning, Bayesian inference, random sampling, and high-dimensional statistics.

Selected Publications

Selected Awards and Honors

  • Best Student Paper Award, Statistical Computing & Graphics, American Statistical Association 2022
  • Best Presentation Award, Laboratory of Information & Decision Systems (LIDS) Conference, MIT 2022
  • Certificate of Distinction and Excellence in Teaching (Q Award), Harvard University 2022
  • Foundations of Data Science (FODSI) Postdoctoral Fellowship 2021
  • Outstanding Graduate Student Instructor Award, UC Berkeley 2020
  • Berkeley Fellowship, 2015
  • President of India Gold Medal, IIT Bombay 2014


Ph. D., UC Berkeley 2021
B. Tech. Honors, EE, IIT Bombay 2014