Baojian Zhou (周宝健)

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I am an assistant professor of the School of Data Science at Fudan University. My research interests are data mining and machine learning, especially mining and learning from large-scale graph data. I am also interested in mathematical optimization such as stochastic online optimization and online decision making. My research goal is to find algorithms for solving different kinds of graph problems. I am also affiliated with the Shanghai Key Laboratory of Data Science and Knowledge Works Research Laboratory.

I was previously a postdoc at Stony Brook University where I worked with Steven Skiena from 2020 to 2021. I obtained my PhD degree in Computer Science and master's degree in Mathematics at University at Albany, SUNY. During my PhD study, I fortunately advised by Feng Chen and Yiming Ying.

Recent Publications

  • Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh, Xingzhi Guo, Deqing Yang, Yanghua Xiao, Iterative Methods via Locally Evolving Set Process, NeurIPS, 2024.

  • Jiahe Bai, Baojian Zhou, Deqing Yang, Yanghua Xiao, Faster Local Solvers for Graph Diffusion Equations, NeurIPS, 2024.

Current Teaching

Contact Information

  • Email: bjzhou AT fudan DOT edu DOT cn

  • Address:
    North 106 Zibin Building,
    School of Data Science, Fudan University,
    220 Handan Rd, Shanghai, China.

  • Phone: (+86) 191-0218-0506