معرفی
George Chen is an Assistant Professor of Information Systems at Carnegie Mellon University's Heinz College and an affiliated faculty member of the Machine Learning Department. His research focuses on machine learning applications in healthcare and developing countries, particularly in time series analysis and forecasting. He holds a PhD in Electrical Engineering and Computer Science from MIT, where he received the George Sprowls Award for his thesis on nonparametric methods. He also advises the AgriTech startup CoolCrop, providing farmers in India with market forecasts and cold storage solutions.
Education:
- PhD, Electrical Engineering and Computer Science, MIT (2015)
- SM, Electrical Engineering and Computer Science, MIT (2012)
- BS, Electrical Engineering and Computer Sciences & Engineering Mathematics and Statistics, UC Berkeley (2010)
Research: Chen develops nonparametric machine learning methods for healthcare (e.g., predicting patient outcomes) and agricultural forecasting (e.g., crop pricing for farmers). His work emphasizes interpretable models and statistical guarantees. He recently authored a monograph on deep learning for survival analysis and co-organized the 2023 AAAI Survival Analysis Symposium.
Awards:
- NSF Fellowship, NDSEG Fellowship, Siebel Scholarship (PhD)
- MIT Goodwin Medal (2015, top teaching award)
- George Sprowls Award for Best Computer Science Thesis (MIT)
Teaching: Teaches courses on unstructured data analytics at CMU, including graduate-level machine learning and time series analysis. Previously taught at MIT and UC Berkeley, winning teaching awards at both institutions.
Professional Service: Area chair for ICML, NeurIPS, and MLHC (2025). Active in organizing conferences and workshops related to survival analysis and healthcare ML.
Labs/Teams: Leads research collaborations in healthcare analytics and developing-world technology through the Heinz College and CMU's Machine Learning Department.
