Peizhao (Percy) Li

AI Research Scientist at GE HealthCare

peizhaoli [AT]


My name is Peizhao Li, pronounced as 'Pay-Jow Lee' and written as '李沛钊' in Chinese. I am an AI Research Scientist at GE HealthCare, working on LLMs & Foundation Models for healthcare applications. I am based in Bellevue, WA. Prior to this, I received my Ph.D. from Brandeis University in 2024. Throughout my Ph.D. studies, I had the opportunity to work as a research intern at Google Research, Amazon Alexa AI, Adobe Research, Mitsubishi Electric Research Laboratories (MERL), NEC Laboratories America, and also as a research fellow at Harvard University.

I research Artificial Intelligence and Machine Learning. I have worked on several topics such as Responsible AI, Multimodal Learning, Computer Vision, and Natural Language Processing. The title of my thesis proposal is 'Harmonizing Fairness with Utility in Data and Learning.' In my dissertation research, I develop methods from both computational and data-centric perspectives to make machine learning models fair and non-discriminatory, and simultaneously have no or minimal side effects on utility performance. My dissertation research was recognized by a NIJ Graduate Research Fellowship and a Meta Ph.D. Research Fellowship Finalist.

I am very fortunate to have Prof. Hongfu Liu as my Ph.D. advisor.

Recent Publications

My five most recent papers. For full publications, please refer to my Google Scholar profile.

Rich Human Feedback for Text-to-Image Generation

Youwei Liang, Junfeng He, Gang Li, Peizhao Li, Arseniy Klimovskiy, Nicholas Carolan, Jiao Sun, Jordi Pont-Tuset, Sarah Young, Feng Yang, Junjie Ke, Krishnamurthy Dj Dvijotham, Katie Collins, Yiwen Luo, Yang Li, Kai J Kohlhoff, Deepak Ramachandran, Vidhya Navalpakkam

CVPR'24: IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection

Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu

ICLR'24: International Conference on Learning Representations, 2024 (Oral)

Learning Antidote Data to Individual Unfairness

Peizhao Li, Ethan Xia, Hongfu Liu

ICML'23: International Conference on Machine Learning, 2023

Characterizing the Influence of Graph Elements

Zizhang Chen, Peizhao Li, Hongfu Liu, Pengyu Hong

ICLR'23: International Conference on Learning Representations, 2023

Robust Fair Clustering: A Novel Fairness Attack and Defense Framework

Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu

ICLR'23: International Conference on Learning Representations, 2023