Praneeth Vepakomma is a PhD at Massachusetts Institute of Technology from the Camera Culture group on distributed and private computation for machine learning, statistical inference and data science at large. This includes a major focus on responsible/trustworthy AI.

I previously spent some time at Apple (intern), Meta (intern), Amazon (AWS), Motorola Solutions and several startups after completing my MS in Mathematical & Applied Statistics at Dept. of Statistics, Rutgers, New Brunswick. I lived/worked in Visakhapatnam, New Brunswick, New York City, Atlanta, Salt Lake City and Seattle before moving to Boston. I won a Meta (previously FB) 2022 Phd Research Fellowship. If you are looking for an official Bio, scroll all the way to the end. Twitter: @ proneat.

Current Research: The “overarching problem” that my research wants to solve is motivated by this question: How do we enable shared prosperity through population-scale orchestrations of siloed data while preserving privacy? My technical focus within this context is on algorithms for distributed scientific computation in statistics & machine learning under constraints of privacy, communication & computational efficiency. My work is inspired by foundations of non-asymptotic statistics, randomized algorithms, learning augmented algorithms, combinatorics, and at times just by systems design.Praneeth Vepakomma is Praneeth Vepakomma