About me

Hello, my name is Xinyu (Rachel) Li (李昕雨) and I am a Ph.D. student at the Auton Lab in the School of Computer Science at Carnegie Mellon University, advised by Prof. Artur Dubrawski. Prior to pursuing my Ph.D., I obtained a B.S. in Computer Science (Information Security) from Shanghai Jiao Tong University, China and a Master of Information Systems Management (MISM) from Carnegie Mellon University.

My research interests lie in building trustworthy AI agents that interact with humans and learn from various types of human feedback such as demonstrations and preferences. Specifically, my recent research focuses on personalizing language models to accommodate diverse human preferences and foundation modeling for clinical applications.

Feel free to reach out to me at xinyul2 [at] andrew [dot] cmu [dot] edu if you are interested in my research and would like to collaborate!

Publications

Automated Assessment of Cardiovascular Sufficiency Using Non-Invasive Physiological Data

Xinyu Li, Michael R. Pinsky, and Artur Dubrawski. Sensors 22, no. 3 (2022): 1024. [Paper]

Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks

Chirag Nagpal, Xinyu Li, and Artur Dubrawski. IEEE Journal of Biomedical and Health Informatics 25, no. 8 (2021): 3163–75. [Paper]

Dynamically Personalized Detection of Hemorrhage

Chirag Nagpal, Xinyu Li, Michael R. Pinsky, and Artur Dubrawski. Machine Learning for Healthcare Conference (MLHC), 2019. [Paper]

Leveraging Routine Pre-Operative Blood Draws to Predict Hemorrhagic Shock During Surgery

Xinyu Li, Michael R. Pinsky, Gilles Clermont, and Artur Dubrawski. NeurIPS Machine Learning for Health (ML4H) Workshop, 2018.