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George H. Chen

Associate 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)


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. I am supported in part by an NSF CAREER award.

Survival analysis tutorial: Much of what I work on is survival analysis. I developed and taught a survival analysis tutorial at CHIL 2020 (co-taught with Jeremy Weiss) and at SIGMETRICS 2021. [tutorial webpage]

CoolCrop: I occasionally also work on machine learning for the developing world. I co-founded and now am 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. We currently serve over 9000 farmers across 7 states in India at over 40 sites.

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 News

Neural Information Processing Systems (Dec 2024): I'm serving as an area chair. [website]

Conference on Health, Inference, and Learning (June 2024): I co-organized research roundtables on the second day of the conference. [website]

Survival analysis symposium (Oct 2023): I co-organized a AAAI 2023 fall symposium on survival analysis/time-to-event prediction. [webpage]

MEET Summer 2023: I returned to Jerusalem to teach computer science to Israeli and Palestinian high school students as part of MIT's Middle East Entrepreneurs of Tomorrow (MEET) program. I previously taught for this program in the summers of 2015 and 2016.

Teaching (Spring 2024, mini 4)

95-865 "Unstructured Data Analytics" (Sections A4/B4/Z4)

Research Supervision

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.

Current PhD student collaborators:

Current master's student:

  • Shaopeng Zhang

Past students and where they went after graduating:

  • Helen S. Zeng (PhD 2024), Assistant Professor at UC Davis Graduate School of Management
  • Yue Zhao (PhD 2023), Assistant Professor at USC Department of Computer Science
  • Emaad Manzoor (PhD 2021), Assistant Professor at Cornell University SC Johnson Graduate School of Management
  • 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
  • Thomas Tam (MSPPM 2023), Sunstella Foundation/Jewish Healthcare Foundation
  • Brenda Palma (MISM 2022), Markaaz
  • Xiaotong (Maggie) Lu (MISM 2020), Uber
  • Runtong (Fred) Yang (MISM 2019), Indeed
  • 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)

Past postdoc:

  • Shu Hu (postdoc from Fall 2022 to Summer 2023), Assistant Professor at Purdue University in Indianapolis, Department of Computer and Information Technology


You can also find my papers listed on Google Scholar.

Some Working Papers
















Last updated 7/1/2024.