I am a final year PhD student in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), where I am very fortunate to be advised by Prof. David Gamarnik. I am affiliated with the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS).
I am currently looking for postdoctoral positions beginning Summer/Fall 2022.
My research revolves around problems in high-dimensional statistics, theory of machine learning, and applied probability with an emphasis on computational aspects. In particular, I would like to understand the fundamental computational limits of such problems by studying the regimes of apparent hardness where efficient algorithms cease to exist. This is often guided by the insights provided by statistical physics and spin glass theory.
Fall 2021: I am a long-term participant at the semester program Computational Complexity of Statistical Inference in Simons Institute for the Theory of Computing at the University of California, Berkeley. There, I am co-organizing a reading group on the Overlap Gap Property (OGP) with Brice Huang.
October 2021: David gave a talk on our ongoing work on algorithms and barriers in symmetric perceptron model with Will Perkins and Changji Xu in Simons Institute workshop. A recording is available here.
October 2021: I presented a poster in Cornell ORIE Young Researchers Workshop.
Fall 2020: I was a long-term participant at the semester program Probability, Geometry, and Computation in High Dimensions in Simons Institute for the Theory of Computing at the University of California, Berkeley.