Hi there! I am a final-year PhD candidate in computer science & engineering at University of Michigan. I'm a member of the Machine Learning for Data-Driven Decisions (MLD3) research group led by Prof. Jenna Wiens, under the Michigan AI Lab. I also collaborated with Prof. Maggie Makar at UMich, Prof. Sonali Parbhoo at Imperial, and Prof. Finale Doshi-Velez and Harvard.

My research focuses on developing and applying artificial intelligence methods to enhance decision making in healthcare, with a particular emphasis on reinforcement learning. While motivated by specific use cases, my work identifies technical challenges and proposes novel solutions that are broadly relevant to fundamental AI/ML research. My past contributions span the technical areas of reinforcement learning (NeurIPS'23, ICML'23 workshops, NeurIPS'22 oral, NeurIPS'22 workshop, MLHC'21, ICML'20), time-series and sequence data modeling (MLHC'19), dataset bias (HealthAffairs'21), as well as translating AI solutions to advance precision medicine (AJS'21, JAMIA'20, JCO-CCI'20), with some work specifically addressing the COVID-19 pandemic (BMJ'22, AnnalsATS'20). I hope to apply my knowledge and expertise to interdisciplinary problems in healthcare and beyond.

I served as a main organizer for the ML4H Symposium in 2022 and 2023, and as an area chair for CHIL 2024. I also regularly review for top-tier ML venues, including NeurIPS, ICML, ICLR, AAAI, AISTATS, KDD, MLHC, CHIL, TMLR, TKDD.

Update Fall 2023: I am on the academic job market for faculty positions starting Summer/Fall 2024. Please feel free to reach out (tangsp [at] umich.edu) if you think I would be a good fit!