Dr. Eric Xing is an associate 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; especially for solving problems involving automated learning, reasoning, and decision-making in high-dimensional and dynamic possible worlds; and for building quantitative models and predictive understandings of biological 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) computational and statistical analysis of gene regulation, genetic variation, and disease associations; and 3) application of statistical learning in social networks, data mining, vision. Professor Xing has published over 150 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. He is a recipient of the NSF Career Award, the Alfred P. Sloan Research Fellowship in Computer Science, 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 phenomina I could reach via pure
experimental approaches, I moved on and turned to statistical machine learning and computational biology, 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.
In my spare time I enjoy classical music, reading, and athletics. My wife Wei Wu is a facuty member in the School of Medicine, University of Pittsburgh. Our son Andrew was born in 2009; he likes to greet his mommy and daddy with a big smile everyday after seeing them back from work.
|Last updated 11/28/09|