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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)


I work on forecasting problems in healthcare and in sustainable development, such as predicting how long a patient will stay in a hospital, or how produce prices will change in a week at over a thousand Indian markets. To produce forecasts, I typically use nonparametric methods that make very few assumptions on the underlying data. Since these methods inform interventions that can be costly and affect people's well-being, ensuring that predictions are reliable is essential. To this end, in addition to developing nonparametric predictors, I also produce theory to understand when and why they work, and I identify forecast evidence to help practitioners make decisions.

Research areas: nonparametric prediction, survival analysis, time series forecasting, missing data, healthcare, sustainable development

Pre-historic: I obtained my Ph.D. in Electrical Engineering and Computer Science at MIT, advised by Polina Golland and Devavrat Shah. 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 at a program MEET that brings together Israeli and Palestinian high school students to learn computer science and entrepreneurship. Between grad school and becoming faculty, I helped develop the recommendation engine at a predictive analytics startup Celect (since acquired by Nike) and then was a teaching postdoc in MIT's Digital Learning Lab, where I was the primary instructor and course developer for an edX course on computational probability and inference. I completed my undergraduate studies at UC Berkeley, dual majoring in Electrical Engineering and Computer Sciences, and Engineering Mathematics and Statistics.

My CV can be found here.

Teaching (academic year 2019-2020)

95-865 "Unstructured Data Analytics" (minis 2 and 3)

94-775 "Unstructured Data Analytics for Policy" (mini 3)


You can also find my papers listed on Google Scholar.

Working Papers












Last updated 6/30/2020.