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baojian/README.md

Hi, I'm Baojian Zhou (周宝健)

Assistant Professor, School of Data Science, Fudan University.

My research is in machine learning and mathematical optimization. Much of my work concerns fast algorithms for large-scale graphs: locally evolving set processes, personalized PageRank, online node labeling, and graph-structured sparse optimization. I also work on the mathematical foundations of large language models, including in-context learning and the training dynamics of diffusion language models.

Teaching

Code

  • LocalCH: iterative methods via locally evolving set processes
  • FastONL: fast online node labeling
  • dmo-fw: code for the ICML 2022 paper
  • Graph-GHTP: Graph-IHT and Graph-GHTP

Links

Homepage · Google Scholar · DBLP · bjzhou [at] fudan [dot] edu [dot] cn

Pinned Loading

  1. llm-26 llm-26 Public

    CS40008.01 - NLP and LLMs, Spring 2026. (Fudan University)

    HTML 56 27

  2. diff-course diff-course Public

    Jupyter Notebook 7

  3. LocalCH LocalCH Public

    Code for Iterative Methods via Locally Evolving Set Process

    Jupyter Notebook 1

  4. llm-26-fall llm-26-fall Public

    Fudan University Natural Language Processing and Large Language Models, Fall 2026

    Jupyter Notebook 42 61

  5. terminal-bench-science terminal-bench-science Public

    Forked from harbor-framework/terminal-bench-science

    Terminal-Bench Science: Evaluating AI Agents on Complex Real-World Scientific Workflows in the Terminal

    Python

  6. harbor-framework/terminal-bench-science harbor-framework/terminal-bench-science Public

    Terminal-Bench-Science: Evaluating AI agents on research workflows across scientific domains

    Python 574 329