About Me

I am a graduate student pursuing a PhD's degree in the Department of Computer Science at the University of Wisconsin-Madison. I am advised by Prof. Kangwook Lee. My current research interests include large language models and machine learning fairness. I received my Master's degree in Statistics from UW-Madison in 2020, where I was advised by Prof. Miaoyan Wang. Prior to UW-Madison, I obtained my Bachelor's degree in Statistics from Nankai University in 2019.

I am looking for internship in summer 2024.

Publications

Large Language Models

LIFT: Language-Interfaced FineTuning for Non-Language Machine Learning Tasks (paper)(code)
Tuan Dinh*, Yuchen Zeng*, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee
Neural Information Processing Systems 2022 (NeurIPS)

Machine Learning Fairness

Federated Learning with Local Fairness Constraints (paper)(code)
Yuchen Zeng, Hongxu Chen, Kangwook Lee
2023 IEEE International Symposium on Information Theory (ISIT)

Equal Improvability: A New Fairness Notion Considering the Long-Term Impact (paper)(code)
Ozgur Guldogan*, Yuchen Zeng*, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee
2023 International Conference on Learning Representationy (ICLR)

Outlier-Robust Group Inference via Gradient Space Clustering (paper)(code)
Yuchen Zeng, Kristjan Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin

Improving fairness via federated learning (paper)(code)
Yuchen Zeng, Hongxu Chen, Kangwook Lee

Tensor Learning

Multiway clustering via tensor block models (paper)(code)
Miaoyan Wang, Yuchen Zeng
Neural Information Processing Systems 2019 (NeurIPS)

Services and leadership

Organizer of MLOPT Idea Seminar
Conference reviewer: NeurIPS, ICML, FAccT

Work experience

MIT-IBM Watson AI Lab, Summer 2022
Mentored by Dr. Mikhail Yurochkin and Prof. Justin Solomon