Dr. Eric Xing is a professor in the School of Computer Science at Carnegie Mellon University. His principal research interests lie in the development of machine learning and statistical methodology, and large-scale computational system and architecture, for solving problems involving automated learning, reasoning, and decision-making in high-dimensional, multimodal, and dynamic possible worlds in complex systems. Professor Xing received a Ph.D. in Molecular Biology from Rutgers University, and another Ph.D. in Computer Science from UC Berkeley. His current work involves, 1) foundations of statistical learning, including theory and algorithms for estimating time/space varying-coefficient models, sparse structured input/output models, and nonparametric Bayesian models; 2) framework for parallel machine learning on big data with big model in distributed systems or in the cloud; 3) computational and statistical analysis of gene regulation, genetic variation, and disease associations; and 4) application of statistical learning in social networks, data mining, and vision. Professor Xing has published over 200 peer-reviewed papers, and is an associate editor of the Journal of the American Statistical Association, Annals of Applied Statistics, the IEEE Transactions of Pattern Analysis and Machine Intelligence, the PLoS Journal of Computational Biology, and an Action Editor of the Machine Learning journal, and the Journal of Machine Learning Research. He is a member of the DARPA Information Science and Technology (ISAT) Advisory Group, a recipient of the NSF Career Award, the Alfred P. Sloan Research Fellowship, the United States Air Force Young Investigator Award, and the IBM Open Collaborative Research Faculty Award.
I was born in Shanghai, China and spent my childhood there.
After completing a B.S. degree major in Physics and minor in Biology in
Beijing, I came to the United States and studied the genetic mechanisms of
human carcinogenesis at Rutgers
Jersey, under Professor Chung S. Yang and obtained my first Ph.D. in
and Biochemistry. Not totally satisfied with the extend and nature of
understanding of biological phenomena I could reach via pure
experimental approaches, I moved on and turned to statistical machine
learning, and completed a second Ph.D. in Computer Science at U.C. Berkeley, under Professors Michael
Karp, and Stuart
Russell. I joined the faculty of CS@CMU in 2004, where I have been
directing the SAILING Lab
whose research spans a broad spectrum of topics ranging from
theoretical foundations to real-world applications in machine
learning, statistics, and computational biology. I was awarded early-tenure in
2011 (two years ahead of clock), and was named a full professor in
In my spare time I enjoy classical music, reading, and sports. My wife Wei Wu is a faculty member in the Lane Center of Computational Biology of the School of Computer Science at Carnegie Mellon. Our son Andrew was born in 2009. Amazingly he loves playing music and building things, and has already traveled to 5 countries.
|Last updated 06/01/14|