Department of Computer Science, University of Massachusetts, Amherst, MA 01003
http://www.cs.umass.edu/~xuerui   email: xuerui@cs.umass.edu Phone: (413)204-1286

OBJECTIVE TOP

To obtain a researcher position at research labs after my Ph.D.

EDUCATION TOP

University of Massachusetts, Amherst, Massachusetts                                          In Progress
Doctor of Philosophy in Computer Science 

Carnegie Mellon University, Pittsburgh, Pennsylvania                                             May 2003
Master of Science in Knowledge Discovery and Data Mining 

Tsinghua University, Beijing, P. R. China                                                                   Jul. 2001
Master of Engineering in Control Theory and Its Applications 

Tsinghua University, Beijing, P. R. China                                                                   Jul. 1999
Bachelor of Engineering in Automation

EXPERIENCE TOP

University of Massachusetts, Amherst, Massachusetts                        Jun. 2004 – Present
Research Assistant, Topic Modeling and its Applications to SNA and IR
· Inventing novel undirected topic models with both fast inference and clear interpretability. Incorporating information from multiple, heterogeneous modalities is much more convenient than their directed counterparts.
· Designing new probabilistic, generative models to improve role discovery and group discovery in social networks by taking (textual) attributes of interactions into account. Applications include email messages, political voting records and academic literatures.
· Studying dynamic topic trends in large text collections in a probabilistic, generative manner with timestamps as observed random variables. Interesting difference from traditional Markov transition based dynamic models.
· Designing new topical n-gram models that discover topical phrases in context, significantly increased interpretability compared to the bag-of-words models. Better performance in IR experiments on large TREC collections.
· Inventing efficient multi-conditional learning methods combining generative and discriminative models, and applying them to various classification, clustering, and information retrieval tasks.

Synthesis Project: Inferring Gene Annotations in Gene Ontology
· Developing new generative models to predict Gene Ontology annotations from massive gene expression data.

UtopiaCompression Corporation, Los Angeles, California                       Jun. 2003 – Jun. 2004
Research Scientist, Pattern-Driven Image/Video/Text Compression/Mining
· Designed and developed an intelligence-based, pattern-driven image compressor that comprehends an image as a unified and interrelated entity, instead of unrelated blocks of data.
· Developed efficient statistical machine learning algorithms to extract features from images and to deal with missing values in image data.
· Conducted research on XML compression using machine learning methods, and co-wrote accepted proposals for research funding from governmental organizations such as DoD, NASA and NSF.

Carnegie Mellon University, Pittsburgh, Pennsylvania                        Aug. 2001 – May 2003
Master Thesis: Scientific Data Mining to Understand Human Brain Function
· Developed machine learning methods that can be used to discover the spatial-temporal fMRI patterns that support probabilistic predictions about the cognitive state of the human subject.
· Discovered representations that are intermediate between high level cognitive states and the raw fMRI voxel activities, and designed classifiers that could be efficiently trained across subjects and across contexts.

Research Assistant, Multi-Agent Learning
· Conducted research on multi-agent reinforcement learning using profit sharing plan that allows agents to learn a behavior progressively without any instruction and only with delayed rewards.

Co-Designer, Fly Through The Universe
· Designed an R-tree-based algorithm to index terabyte astronomical data sets and digitally simulated a craft exploring the universe made up of millions of galaxies.

Tsinghua University, Beijing, P. R. China                        Jun. 1998 – Jul. 2001
Master Thesis: Research and Design for Knowledge Management System
· Formulated a new architecture of knowledge management systems and designed a web-based knowledge management system facing multi-source data.

Research Assistant, HY-CIMS Project
· Conducted research on new decision support technologies with data mining / data warehousing. Studied the experimental infrastructure for distributed database system based on MySQL. Developed the undergraduate major-choosing expert system.

Research Assistant, Web-based Decision Support Systems
· Designed and implemented a web-based decision support system using Oracle, Lotus Notes and MS Visual Basic.

RECENT HONORS TOP

· The Graduate School Fellowship, University of Massachusetts, May 2007
· Finalist, the Microsoft Research/Live Labs Graduate Fellowship, Dec. 2006
· Passed the Ph.D. Portfolio with distinction at University of Massachusetts, May 2006
· The Best Foundational Paper Award, American Medical Informatics Association, Nov. 2003
· The Graduate Fellowship, CALD, SCS, Carnegie Mellon University, Aug. 2001 & Aug. 2002
· Rockwell Automation Scholarship, Rockwell International Corporation, Dec. 2000
· Graduated with honor from Tsinghua University, Jul. 1999
· Sequent-Chen Daren Outstanding Student Scholarship, Hong Kong Sequent Ltd., Dec. 1998
· Student Social Work Scholarship, Excellent Student Cadre, Tsinghua University, May 1998
· Outstanding Student Scholarship, Tsinghua University, Nov. 1996 & Nov. 1997
· Social Practice Scholarship (Golden Prize), Tsinghua University, Oct. 1996

SERVICES TOP

· Reviewer, Journal of Machine Learning Research (JMLR)
· Reviewer, Association for Computational Linguistics (ACL)
· Reviewer, International Conference on Machine Learning (ICML)
· Reviewer, Uncertainty in Articificial Intelligence (UAI)
· Reviewer, American Association for Artificial Intelligence (AAAI)
· Reviewer, Neural Information Processing Systems (NIPS)
· Reviewer, ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD)
· Graduate Representative, Department of Computer Science, University of Massachusetts
· Librarian of Graduate Student Library, Department of Computer Science, University of Massachusetts

SKILLS TOP

· Programming languages: C/C++, Java, SQL, Matlab, Perl, Python, Mathematica, Splus, R, Assembly Language (Intel X86 series), Fortran 77, Pascal, Visual Basic, CLISP, Prolog, HTML, etc.
· Systems: Windows 95/98/NT/ME/2000/XP/Vista, Macintosh, Unix (Linux especially).
· Languages: Chinese (native), English (fluent), Japanese (fair) and German (basic).

COURSES TOP

· Machine Learning, Statistical Approaches to Learning and Discovery, Multimedia Databases and Data Mining, Graduate Algorithms, Computational Analyses of Brain Imaging, Information Retrieval, Advanced Software Engineering, Theory of Computation, Bioinformatics, etc.
· Probability and Statistics, Intermediate Statistics, Statistical Computing, Time Series Analysis, Nonparametric Methods, etc.