Christopher Mohri

I am a fourth-year PhD student at Stanford, advised by John Duchi and Tatsu Hashimoto.

I am broadly interested in efficiency, both of compute and data: how do we minimize resources spent to reach a fixed goal, and how do we push the frontier when spending it all?

I was also a Student Researcher at Google working with Praneeth Kacham, where I developed new model architectures.

Pretraining Data

  1. NeurIPS 2026Spotlight
    A Bitter Lesson for Data Filteringpdf
    Christopher Mohri, John Duchi, Tatsunori Hashimoto

Language Models

  1. ICML 2024
    Language Models with Conformal Factuality Guaranteespdf
    Christopher Mohri, Tatsunori Hashimoto

Theory

  1. COLT 2026
    Algorithmic Thinking Theorypdf
    MohammadHossein Bateni, Vincent Cohen-Addad, Yuzhou Gu, Silvio Lattanzi, Simon Meierhans, Christopher Mohri
  2. ICML 2025
    Online Conformal Prediction via Online Optimization
    Felipe Areces, Christopher Mohri, Tatsunori Hashimoto, John Duchi
  3. NeurIPS 2024
    Cardinality-Aware Set Prediction and Top-k Classificationpdf
    Corinna Cortes, Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong
  4. ICLR 2024
    Learning to Reject with a Fixed Predictor: Application to Decontextualizationpdf
    Christopher Mohri, Daniel Andor, Eunsol Choi, Michael Collins, Anqi Mao, Yutao Zhong
  5. NeurIPS 2023
    Two-Stage Learning to Defer with Multiple Experts
    Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong
  6. AISTATS 2023
    Theory and Algorithm for Batch Distribution Drift Problems
    Pranjal Awasthi, Corinna Cortes, Christopher Mohri