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I am a third-year PhD student at Boston University, jointly advised by ***Krzysztof Onak*** and Venkatesh Saligrama. I did my undergrad at Dartmouth College advised by Amit Chakrabarti, and spent two years in Seattle as a software engineer at the Microsoft Windows Base Kernel team.

In 2025, I completed an internship at the National Institute of Informatics in Tokyo, hosted by Yuichi Yoshida.

I am currently a student researcher at Google Research, kindly hosted by **Maryam Karimzadehgan.**


My research focuses on developing efficient and robust algorithms for Foundation Models. I am also interested in problems from different areas of theoretical computer science, including sublinear algorithms, learning theory and complexity.

Email: tharis at bu.edu

Publications

Foundation Models

  1. Layerwise Dynamics for In-Context Classification in Transformers: Lutz, TH, Chandra, Gangrade, Saligrama — ICML 2026 (Spotlight)
  2. Noise Stability of Transformer Models: TH, Zhang, Yoshida — ICLR 2026
  3. Compression Barriers for Autoregressive Transformers: TH, Onak — COLT 2025
  4. $k$NN Attention Demystified: A Theoretical Exploration for Scalable Transformers: TH — ICLR 2025

Sublinear Algorithms

  1. Fast-MWEM: Private Data Release in Sublinear Time: TH, Choi, Laksanawisit — TPDP 2026
  2. Estimating Hitting Times Locally At Scale: TH, Spaeh, Dragazis, Tsourakakis — NeurIPS 2025
  3. Efficient Algorithms for Adversarially Robust Approximate Nearest Neighbor Search: Andoni, TH, Kelman, Onak [Arxiv]
    1. NeurIPS 2025 Workshop: Reliable ML from Unreliable Data
    2. WoLA 2026 Poster
  4. Counting Simplices in Hypergraph Streams: Chakrabarti, TH — ESA 2022

Others

  1. Teaching American Sign Language in Mixed Reality: Shao, Sniffen, Blanchet, Hillis, Shi, H, Liu, Lamberton, Malzkuhn, Quandt, Mahoney, Kraemer, Zhou, Balcom — Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies