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Eric P. Xing,  PhD, PhD

8101 Gates-Hillman Center (GHC), SCS
Carnegie Mellon University
Pittsburgh, PA 15213
Phone: (412) 268-2559
Fax: (412) 268-3431
Email: epxing AT cs.cmu.edu

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Biography Publications Research Teaching My Group CV Job Openning
 

Associate Professor

Machine Learning Department & Language Technology Institute & Computer Science Department
School of Computer Science
Carnegie Mellon University


Position Available: Lane Fellowship of Computational Biology
If you are interested in doing a postdoc in my group through this program, please write to me, or ask your advisor to nominate you.


Research synopsis: My 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, multimodal, and dynamic possible worlds; and for building quantitative models and predictive understandings of the evolutionary mechanism, regulatory circuitry, and developmental processes of biological systems. Currently the following themes are studied in my group:
  • Foundations of Statistical Learning, including : 1) Theory and algorithms for estimating time/space varying-coefficient models with evolving strcutures; 2) Learning sparse structured input/output models in very high-dimensional space; 3) Nonparametric techniques for infinite-dimensional models; 4) Active learning.
  • Computational Biology, including: 1) Comparative genomic analysis of regulatory evolution; 2) Systems biology investigation of time-varying gene regulation circuity; 3) Statistical genetic analysis of population variation, demography and evolution; 4) Structured inference of genome-transcriptome-phenome association in complex diseases.
  • Applications of Statistical Learning, in social/bio network analysis, text/image data mining, computer vision, and machine translation.

Rescent Activities:

I am teaching Probabilistic Graphical Models (10708) in Fall 2009.
Previously I taught Machine Learning (10701) in Fall 2008;
and I taught Computational Genomics (10810) in Spring 2009.
The Dragon Star Lectures: Advanced Machine Learning, @ Peking/Tsinghua Univ., Beijing, Summer 2009.

I gave a keynote talk on "Recent Advances in Learning Sparse Structured Input/Output Model: Models, Algorithms, and Applications" at the NIPS 2008 Workshop on "Structured Input, Structured Output".
I gave a talk on "Time-Varying Networks: Reconstructing Temporally/Spatially Rewiring Gene Interactions" at the RECOMB Regulatory Genomics workshop.
I co-organized NIPS 2008 Workshop on "Analyzing Graphs: Theories and Applications".
I co-organized ICML 2007 Workshop on Learning in Structured Output Spaces.
I co-organized NIPS 2007 Workshop on Statistical Models of Networks.
I gave a keynote talk on "Graphical models and algorithms for integrative bioinformatics at the 6th annual Graybill Conference.
I gave a keynote talk on "Probabilistic graphical models --- theory, algorithm, and application" at ICMLA'07.
Last updated 08/29/2004