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Eric P. Xing, PhD, PhD8101 Gates-Hillman Center (GHC), 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 | My Group | CV |
Associate 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 solving problems involving automated learning,
reasoning, and decision-making in high-dimensional, multimodal, and
dynamic possible worlds in social and biological systems.
Currently the following themes are studied in my group:
Recent Activities: Teaching: I am teaching Probabilistic Graphical Models (10708) in Spring 2013. Previously I co-taught Machine Learning (10701) with Prof. Aarti Singh in Fall 2012; and I taught Computational Genomics (10810) in Spring 2009. The Dragon Star Lectures: Advanced Machine Learning, @ Peking/Tsinghua Univ., Beijing, Summer 2009. Services: I am a member of the DARPA Information Science and Technology (ISAT) Advisory Group. And I serve on the NIH Bio-Data Management and Analysis (BDMA) Study Section. Sabbatical: I was on sabbatical from 2010 to 2011 as a visiting professor at Department of Statistics, Stanford University. I was also a visiting professor during 2010-2011 at Facebook, working on a variety of projects on social media. Talks: I gave an invited talk on "On Learning Sparse Structured Input-Output Models" [slides] at the Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP 2012). I gave a tutorial on "Topic Models, Latent Space Models, Sparse Coding, and All That: A systematic understanding of probabilistic semantic extraction in large corpus" [slides] at the 50th Annual Meeting of the Association for Computational Linguistics (ACL 2012). With Dr. Seyoung Kim, we gave a tutorial on " Modern Statistical Methods for Genetic Association Study: Structured Genome-Transcriptome-Phenome Association Analysis" [slides] at the Nineteenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2011). I gave a keynote talk on "Sparsity and Learning Large Scale Models" [slides] at the 2011 CVPR Workshop on Large Scale Learning for Vision. I gave a keynote talk on "Dynamic Network Analysis: Model, Algorithm, Theory, and Application" [slides] at the Eighth Workshop on Mining and Learning with Graphs, 2010. I gave a keynote talk on "Genome-Phenome Association Analysis of Complex Diseases - a Structured Sparse Regression Approach" [slides] at the Tenth Annual International Workshop on Bioinformatics and Systems Biology, 2010. I gave a keynote talk on "Jointly Maximum Margin and Maximum Entropy Learning of Graphical Models" [slides] at the NIPS 2009 Workshop on "APPROXIMATE LEARNING OF LARGE SCALE GRAPHICAL MODELS: THEORY AND APPLICATIONS". I gave a keynote talk on "Time Varying Graphical Models: reverse engineering and analyzing rewiring networks" [slides] at the NIPS 2009 Mini-Symposium on Machine Learning in Computational Biology. 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 2008 RECOMB Regulatory Genomics workshop. I co-organized NIPS 2012 Workshop on "Spectral Learning". I co-organized ICML 2011 Workshop on "Structured Sparsity: Learning and Inference". 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. |