Bio

I am a fourth-year Computer Science Ph.D. student in the Big Data and Social Computing (BDSC) Lab at the University of Illinois Chicago (UIC), advised by Prof. Philip S. Yu. Before joining UIC in Spring 2023, I obtained my Master’s degree in Operations Research from Columbia University in Fall 2022, and my Bachelor’s degree in Industrial Engineering from Nanjing University in Spring 2021.

Driven by the goal of building trustworthy models, my research specializes in uncertainty quantification and data selection to produce reliable predictions for text and structured data. In my recent industry research, I am actively exploring topics like agentic feature discovery and text world model.

I am actively seeking Fall 2026 research internship and full-time research scientist position starting in 2027. Please feel free to reach out at fwang51@uic.edu.

Selected Publications

• Topology-Aware Conformal Prediction for Stream Networks
  Fangxin Wang^*, Jifan Zhang^*, Zihe Song, Philip S. Yu, Kaize Ding, Woody Zhu.
  Neural Information Processing Systems (NeurIPS), 2025. [Paper]

• BANGS: Game-Theoretic Node Selection for Graph Self-Training
  Fangxin Wang, Kay Liu, Sourav Medya, Philip S. Yu.
  International Conference on Learning Representations (ICLR), 2025. [Paper]

• Uncertainty in Graph Neural Networks: A Survey
  Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu.
  Transactions on Machine Learning Research (TMLR), 2024. [Paper]

• Equal Opportunity of Coverage in Fair Regression
  Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu.
  Neural Information Processing Systems (NeurIPS), 2023. [Paper] [Code] [Poster]

^* denotes equal contribution.

Internships

• Intuit, Research Intern, AI Research. May 2026 – Aug 2026.

• TikTok, Machine Learning Intern, E-commerce. Feb 2026 – May 2026.

• Ant Group, Research Intern, Ling Foundation Model. Jun 2025 – Aug 2025.

• Walmart Global Tech, Data Scientist Intern, Marketing and Advertising Technology. May 2022 – Aug 2022.