Rishit Chatterjee

ml systems · ml theory · ai safety

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Dartmouth College
Hanover, NH
Colby College
Waterville, ME

I’m Rish, an AI researcher at Dartmouth! 👋

I study CS and math at Colby College and computer engineering at Dartmouth College.

During the summer of 2026, I am in the UK as an AI Safety Intern at the University of Birmingham.

I am also working in Dartmouth’s Department of CS on AI interpretability.

Previously, I was a Research Fellow at SPAR Research, where I studied zero-knowledge proofs for privacy-preserving model authentication.

At Colby, I worked as a Research Assistant at OWLab and HUMANE Lab, applying ML methods to driving behavior, environmental time series, and multimodal speech processing.

research interests

  • efficient ml systems
  • algorithmic and theoretical ml
  • secure & verifiable ml
  • nlp and vision

news

Jul 11, 2026 Three papers on model equivalence testing accepted to the ICML Hypothesis Testing Workshop!
Feb 01, 2026 Started as a Research Fellow at SPAR Research, focusing on zero-knowledge proofs for model equality verification.
Jan 25, 2026 Lake water quality forecasting paper accepted to IEEE SusTech 2026 for oral presentation.
Jul 15, 2024 Published machine learning work on Creutzfeldt-Jakob disease diagnosis at IEEE EMBC 2024.

selected publications

  1. ICML Workshop
    Equivalence Testing of Parametric Models via the Effective Dimension
    M. Kaufmann, Rishit Chatterjee, A. Dang, and 2 more authors
    In The ICML 2026 Workshop on Hypothesis Testing, 2026
    Workshop paper
  2. ICML Workshop
    Detecting 4-Bit Adversaries at the Token Level
    M. Kaufmann, Rishit Chatterjee, A. Dang, and 2 more authors
    In The ICML 2026 Workshop on Hypothesis Testing, 2026
    Workshop paper
  3. ICML Workshop
    Trust from afar: Evaluating remote model instances
    Rishit Chatterjee, A. Dang, M. Kaufmann, and 2 more authors
    In The ICML 2026 Workshop on Hypothesis Testing, 2026
    Workshop paper