About Me

Hi there! I’m Shuyi Chen, a first-year Ph.D. student at Heinz College, Carnegie Mellon University, where I’m advised by Woody Zhu. My research lies at the intersection of Machine Learning (ML) and Operations Research (OR), focusing on leveraging statistical methods to solve real-world problems. I hold a Master’s degree in Information Systems Management from CMU and a B.B.A in Supply Chain and Logistics Management from the Chinese University of Hong Kong (Shenzhen).

You can view my CV here.

News

• October 2024: Two papers [1] [2] (link coming soon) accepted for presentation at INFORMS Workshop on Data Science and Workshop on Data Mining and Design Analysis.
• August 2024: Awarded the INFORMS Student Scholarship by the INFORMS Workshop on Data Science 2024 Program Committee.
• October 2023: Our paper was accepted at EMNLP 2023.

Conferences and Workshops

• Shuyi Chen and Shixiang Zhu. 2024. Counterfactual Fairness through Transforming Data Orthogonal to Bias. Preprint.
• Shuyi Chen, Kaize Ding, and Shixiang Zhu. 2023. Uncertainty-Aware Robust Learning on Noisy Graphs. In New Frontiers in Graph Learning (GLFrontiers), NeurIPS 2023, US.
• Yihan Cao, Shuyi Chen, Ryan Liu, Zhiruo Wang, and Daniel Fried. 2023. API-Assisted Code Generation for Question Answering on Varied Table Structures. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Singapore.