Daniel P. Jeong

danielje [at] cs.cmu.edu

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I'm a Ph.D. student in the Machine Learning Department at Carnegie Mellon University, where I am advised by Profs. Zachary C. Lipton and Pradeep Ravikumar. I also collaborate closely with Prof. Michael Oberst and serve as a Managing Editor for the Journal of Machine Learning Research (JMLR). My research focuses on developing machine learning methods inspired by the unique challenges of healthcare and creating rigorous evaluation strategies to ensure their relevance and impact in clinical practice. My work has been supported by the ARCS Foundation.

Previously, I earned my B.S. degree in Computer Science from Columbia University, where I was advised by Profs. Itsik Pe'er, David A. Knowles, David M. Blei, and Kriste Krstovski. I also spent wonderful summers interning in the Real-World Evidence Group at Microsoft Research (Health Futures) and the Machine Learning Groups (398J, 393K) at NASA Jet Propulsion Laboratory (JPL).