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