I am a Distinguished Postdoctoral Fellow at the Department of Statistics at Columbia University. I received my PhD in Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), where I was very fortunate to be advised by Prof. David Gamarnik. At MIT, I was affiliated with the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS). You can find my CV here.
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.
April 2022: I presented a poster on symmetric binary perceptron model at MIT Statistics and Data Science Conference (SDSCon)
March 2022: I gave two talks at MIT SIAM Student Seminar and University of Illinois at Chicago, Combinatorics and Probability Seminar on our work on algorithmic barriers in the symmetric binary perceptron model. Slides are available here.
February 2022: I gave a talk at MIT LIDS and Statistics Tea Talk on Overlap Gap Property in symmetric binary perceptron.
January 2022: I gave talks at Stanford CS Theory Lunch, Stanford Information Theory Forum, MIT LIDS Student Conference, and Bilkent University, Electrical and Electronics Engineering Department. Two of these talks were based on our forhcoming work on algorithmic barriers in the symmetric binary perceptron model, and slides are available here.
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.
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.