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David Choi is an Associate Professor at Carnegie Mellon University's Heinz College of Information Systems and Public Policy, where he also holds a courtesy appointment in the Department of Statistics. His current research primarily focuses on statistics, machine learning, and network data. He specializes in exploratory data analysis, community detection, and network models involving latent variables, as well as unsupervised learning and causal inference with an emphasis on social network effects. Prior to his position at Carnegie Mellon, Professor Choi was a research scientist at MIT Lincoln Laboratory, and he completed his postdoctoral fellowship at the School of Engineering at Harvard University. He also has experience as a visiting scholar at the Department of Statistics at the University of California, Berkeley. He earned his Ph.D. in Electrical Engineering from Stanford University in 2004, where he also received his Master’s and Bachelor’s degrees in the same field.
Carnegie Mellon University • Pittsburgh, PA
Teaching and academic research in Statistics and Information Systems.
MIT Lincoln Laboratory •
Conducting research in advanced statistical methods and machine learning.
Harvard University, School of Engineering •
Postdoctoral fellowship focusing on statistical models and network data.
UC Berkeley, Department of Statistics •
Engaging in collaborative research in statistical theory and application.
Admission is extremely competitive with no strict GPA cut-offs; holistic review is used.