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Eric P. Xing, PhD, PhD4127 Wean Hall, SCSCarnegie 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 | Students | CV |
Assistant Professor
Machine Learning Department & Language Technology Institute & Computer Science DepartmentSchool of Computer Science
Carnegie Mellon University
| Research
synopsis: My principal research interests lie
in the development of machine learning and statistical methodology;
especially for building quantitative models and predictive
understandings of the evolutionary mechanism, regulatory circuitry, and
developmental processes of biological systems, and for problems
involving automated learning, reasoning, and decision-making in open,
evolving possible worlds. Currently the following major themes are studied in my group: 1) graphical models, Bayesian approaches, inference algorithms, and learning theories for analyzing and mining high-dimensional, longitudinal, and relational data; 2) computational and comparative genomic analysis of biological sequences, systems biology investigation of gene regulation, and statistical analysis of genetic variation, demography and linkage (to diseases); and 3) application of statistical learning in text/image mining, vision, and machine translation. Recent Adtivities: I am teaching Machine Learning (10701) this semester. I organized the 6th Annual Carnegie Mellon Computational Biology Symposium this year. I gave a lecture series on graphical models in the Inst. of Theoretical Computer Sci., Tsinghua University. Here are the slides of the lectures. I gave a keynote talk on "Graphical models and algorithms for integrative bioinformatics at the 6th annual Graybill Conference. 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 "Probabilistic graphical models --- theory, algorithm, and application" at ICMLA'07. |