I am a fourth-year Ph.D. student in Computer Science at the University of Michigan, working in the MLD3 lab under Jenna Wiens. My research focuses on the development of novel machine learning algorithms for leveraging clinical time-series data. I am particularly focused on novel architectures that can learn temporal invariances, time series alignment, as well as adapt to time varying tasks. Our work has applications in healthcare. We focus on clinically relevant tasks that utilize the electronic health record (EHR) to improve patient care.
I received my Bachelors degree from the University of California, Los Angeles in Economics and Mathematics.
2260 Hayward Street
Ann Arbor, MI
Jeeheh Oh, Jiaxuan Wang, Jenna Wiens, Learning to Exploit Invariances from Clinical Time-Series Data using Sequence Transformer Networks, Machine Learning for Healthcare Conference (MLHC), August 2018. Link
Jiaxuan Wang, Jeeheh Oh, Haozhu Wang, Jenna Wiens, Learning Credible Models, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 2018.Link
Jeeheh Oh, Maggie Makar et al., A Generalizable, Data-Driven Approach to Predict Daily Risk of Clostridium difficile Infection at Two Large Academic Health Centers, Infection Control and Hospital Epidemiology (ICHE), March 2018. Link
Jeeheh Oh, Evan Snitkin, Vincent Young, Data-Driven Tools to Curb the Spread of Healthcare-Associated Infections, MCubed Symposium, November 2017. Video