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George H. Chen

Assistant Professor of Information Systems, Heinz College
Affiliated Faculty, Machine Learning Department
Carnegie Mellon University

Email: georgechen [at symbol]

Office: HBH 2216 (the west wing of Hamburg Hall, second floor)

Postdoc opening: I'm currently looking to hire a postdoc with a background in machine learning for healthcare. The research involved is on building trustworthy machine learning models for time-to-event prediction (survival analysis) and applying these models in medical resource management tasks. This is a 1 year position with the possibility of extending to 2 years, starting as early as January 2022 (the starting time is flexible). More information including the application link can be found here. Feel free to email me if you have questions.


I primarily work on building trustworthy machine learning models for time-to-event prediction (survival analysis) and for time series analysis. I often use nonparametric prediction models that work well under very few assumptions on the data. My main application area is in healthcare.

CoolCrop: I occasionally also work on machine learning for the developing world. I co-founded and now serve as an advisor for CoolCrop, an AgriTech startup based in India that works on providing farmers with cold storage units (such as a refrigerator shared by a village) and market forecasts.

Pre-historic: I obtained my Ph.D. in Electrical Engineering and Computer Science at MIT. My thesis was on nonparametric machine learning methods. At MIT, I also worked on satellite image analysis to help bring electricity to rural India, and taught twice in Jerusalem for MEET, a program that brings together Israeli and Palestinian high school students to learn computer science and entrepreneurship. I completed my B.S. at UC Berkeley, majoring in Electrical Engineering and Computer Sciences, and Engineering Mathematics and Statistics.

My CV can be found here.

Some Recent News

Conference on Health, Inference, and Learning (CHIL) (April 7-8, 2022): I am a proceedings chair (with Gerardo Flores and Tom Pollard) for CHIL 2022. The paper deadline is Jan 14, 2022 11:59pm AoE. For details, see the call for papers here: [CHIL 2022 CFP]

KDD workshop on Machine Learning for Consumers and Markets (August 15, 2021): I co-organized a workshop with Wen Wang, Dokyun Lee, and Han Zhao that brings the machine learning and business communities together (a heavy emphasis is on how machine learning translates into actual impact in terms of managerial implications) [workshop website]

NSF CAREER award (June 24, 2021): I received an NSF CAREER award for my proposed project on developing real-time nonparametric machine learning models for healthcare with guarantees

Survival analysis tutorial (June 18, 2021): I taught a survival analysis tutorial at the SIGMETRICS conference (this tutorial is based on a previous tutorial with more of a healthcare focus that I co-taught with Jeremy Weiss at CHIL 2020) [tutorial webpage]

Best paper award at AAAI Workshop on AI for Behavior Change 2021 (Feb 8, 2021): research led by my PhD student Emaad Manzoor examines how reputation affects persuasiveness in online debates [arXiv]

Teaching (Fall 2021)

95-865 "Unstructured Data Analytics" (mini 2)

Research Group

I've had the fortune of working with many wonderful students over the years (listed below). If you're interested in working with me and you already are a CMU student, then feel free to shoot me an email telling me what you're particularly excited about working on, why it overlaps with my research interests, and what skills you've already cultivated. I do not take on students who are not already admitted to CMU.

Current PhD students:

Current master's students:

Past students and where they went after graduating:

  • Emaad Manzoor (PhD 2021), Assistant Professor at UW Madison School of Business
  • Mi Zhou (PhD 2020), Assistant Professor at UBC Sauder School of Business
  • Wei Ma (master's in ML 2018/PhD 2019), Assistant Professor at Hong Kong Polytechnic University in the Department of Civil and Environmental Engineering
  • Lynn H. Kaack (master's in ML 2018/PhD 2019), Assistant Professor at the Hertie School
  • Xiaotong (Maggie) Lu (MISM 2020), McKinsey
  • Runtong (Fred) Yang (MISM 2019), Capitol One
  • Ren Zuo (MISM 2018), Cornerstone Research
  • Linhong (Lexie) Li (B.S. 2020), McKinsey
  • Junyan Pu (B.S. 2020), CMU master's degree program in CS
♣ indicates a PhD student who worked with me on a secondary master's in ML (I was their master's research advisor but not their PhD research advisor)


You can also find my papers listed on Google Scholar.

Some Working Papers













Last updated 10/23/2021.