I have broad research interest in Theoretical Computer Science and worked in design and analysis of streaming algorithms, the theory of error-correcting codes, algorithms related to machine learning, differential privacy and compressed sensing. In my dissertation, I described my research in streaming algorithms and error correction, featuring applications of high dimensional probability in these two areas.
In the recent series of project my research focused on mathematical aspects of the notion of calibration for a machine learning predictor — which is a quality of a predictor to assess its own uncertainty.