CyLab Seminar: Praneeth Vepakomma

About this event

Speaker:Praneeth Vepakomma Visiting Professor MITTalk Title:Talk title coming soonAbstract:Abstract coming soonBio:Praneeth Vepakomma is currently a Visiting Assistant Professor at MIT in IDSS and is an Assistant Professor at MBZUAI. He previously obtained his PhD at MIT in and works on trustworthy/responsible computation that includes a sub-focus on distributed (resource-efficient) and private computation in statistics, ML and data science at large. He has extensive industrial experience across Meta, Apple, Amazon, Motorola Solutions, Corning and several sta rtups. His research focuses on developing algorithms for distributed computation in statistics and machine learning under constraints of privacy, and efficiency. He won the Meta PhD research fellowship in Applied Statistics, two SERC Scholarships (for Social and Ethical Responsibilities of Computing) from MIT's Schwarzman college of computing. He co-founded a research based non-profit (Integrity Distributed) that won the Financial Times Digital Innovation Award. He won a Best Student Paper Award at FL-IJCAI, a Baidu Best Paper Award at NeurIPS-SpicyFL and a Best Paper Runner Up Award at FG-2021. His technical work is inspired by foundations of non-asymptotic statistics, randomized algorithms, learning augmented algorithms, combinatorics, and at times just by systems design. He was Interviewed in the book, 'Data Scientist: The Definitive Guide to Becoming a Data Scientist' and has organized several workshops at ICLR, ICML, IJCAI, CVPR and NeurIPS.epakomma

Visiting Professor

MIT

Talk Title:

Talk title coming soon

Abstract:

Abstract coming soon

Bio:

Praneeth Vepakomma is currently a Visiting Assistant Professor at MIT in IDSS and is an Assistant Professor at MBZUAI. He previously obtained his PhD at MIT in and works on trustworthy/responsible computation that includes a sub-focus on distributed (resource-efficient) and private computation in statistics, ML and data science at large. He has extensive industrial experience across Meta, Apple, Amazon, Motorola Solutions, Corning and several star tups. His research focuses on developing algorithms for distributed computation in statistics and machine learning under constraints of privacy, and efficiency.

He won the Meta PhD research fellowship in Applied Statistics, two SERC Scholarships (for Social and Ethical Responsibilities of Computing) from MIT's Schwarzman college of computing. He co-founded a research based non-profit (Integrity Distributed) that won the Financial Times Digital Innovation Award. He won a Best Student Paper Award at FL-IJCAI, a Baidu Best Paper Award at NeurIPS-SpicyFL and a Best Paper Runner Up Award at FG-2021. His technical work is inspired by foundations of non-asymptotic statistics, randomized algorithms, learning augmented algorithms, combinatorics, and at t imes just by systems design. He was Interviewed in the book, 'Data Scientist: The Definitive Guide to Becoming a Data Scientist' and has organized several workshops at ICLR, ICML, IJCAI, CVPR and NeurIPS.