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.
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Recent Publications
Binbin Huang, Baojian Zhou, et. al., Accelerated Evolving Set Processes for Local PageRank Computation, NeurIPS, 2025
Ziyang Ma, Baojian Zhou, et. al., From Text to Trajectories: GPT-2 as an ODE Solver via In-Context, 2025
Current Teaching
Contact Information
Address: South 401 Computing Center, School of Data Science, Fudan University, 220 Handan Rd, Shanghai, China.
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