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Abhishek Shetty

Ph.D. Student
UC Berkeley
shetty@berkeley.edu

About Me

I am currently a PhD student in the Department of Computer Science at the University of California at Berkeley (previously at Cornell) advised by Nika Haghtalab. I am also fortunate to have worked with Lester Mackey at MSR New England during the summer of 2021, Akshay Krishnamurthy and Cyril Zhang at MSR NYC during the summer of 2022 and Parikshit Gopalan at Apple during the summer of 2023. I am honored to be amongst the 2023 cohort of the Apple AI/ML fellowship.

Prior to starting grad school, I was a Research Fellow at Microsoft Research India working with Navin Goyal. Before that, I was an undergraduate majoring in Mathematics at the Indian Institute of Science and worked with Bhavana Kanukurthi on cryptography.

My research focuses on designing mathematical frameworks bringing together the theory and practice of machine learning and using these to developing simple algorithms with provable guarantees on real-world data. Importantly, these frameworks come with design principles that can be used to incorporate important desiderata such as robustness, privacy and fairness into existing pipelines without significant computational and statistical overhead. Some focus areas of my research have been:

I am on the 2023/24 job market. Here is a link to my CV.

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Selected Publications

All Publications

Oracle-Efficient Differentially Private Learning with Public Data
with Adam Block, Mark Bun, Rathin Desai and Steven Wu
Under submission
[Arxiv]

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