Baojian

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.

Recent Publications

• Baojian Zhou and Steven Skiena.
  Does it pay to optimize AUC? AAAI, arXiv, Code, 2023.

• Baojian Zhou, Yifan Sun, and Reza Bahanezhad.
  Fast Online Labeling for Very Large Graphs. ICML, arXiv, Code, 2023.

• Zhen Chen, Xingzhi Guo, Baojian Zhou, Deqing Yang, and Steven Skiena.
  Accelerating Personalized PageRank Vector Computation. KDD, arXiv, Code, 2023.

• Chi Zhang, Wenkai Xiang, Xingzhi Guo, Baojian Zhou, Deqing Yang.
  SubAnom: Efficient Subgraph Anomaly Detection Framework over Dynamic Graphs.
  IEEE International Conference on Data Mining Workshops (ICDMW) arXiv, Code, 2023.