Assistant Research Professor of Computer Science

Research Interests:

• Machine learning
• Causal inference

Michael Oberst is an assistant research professor of computer science whose research focuses on reliable machine learning for decision-making in health care. His long-term goal is to ensure that machine learning systems are as reliable as any FDA-approved medication or diagnostic test. His work has been published in machine learning conferences such as the Conference on Neural Information Processing Systems, the International Conference on Machine Learning, and the Scoeity for Artificial Intelligence and Statistics; his research has additionally appeared in Science Translational Medicine.

Oberst received a BS in statistics from Harvard University and a PhD in computer science from the Massachusetts Institute of Technology. Prior to joining Johns Hopkins, he was a postdoctoral associate in the Machine Learning Department at Carnegie Mellon University.