I am a 4th year Ph.D. student in the Statistics Department at the University of Michigan advised by Ambuj Tewari. Previously, I studied Computer Science and Chemical Engineering also at UM where I worked with Mahdi Cheraghchi, Sindhu Kutty, and Andrej Lenert. This past summer (2024), I interned at Apple with Kunal Talwar and Hilal Asi, where I worked on online learning and differential privacy!
My research interests broadly lie in statistical learning theory and algorithm design. Some specific areas of interest include: online learning theory, bandits, differential privacy, adversarial robustness, and algorithms with predictions. Currently, I am interested in bridging learning theory and generative machine learning with applications to Transformers and Large Language Models (LLMs). I am also working on empirical research aimed at understanding the abilities and limitations of Transformers and other modern sequence-to-sequence models.
Publications
Design of thermophotovoltaics for tolerance of parasitic absorption.
Vinod Raman, T. Burger, A. Lenert
Optics Express 2019
