Raymond J. Mooney

Professor of Computer Science, The University of Texas at Austin
Director of the UT Artificial Intelligence Laboratory

B.S. in Computer Engineering, University of Illinois at Urbana/Champaign, 1983
M.S. in Computer Science, University of Illinois at Urbana/Champaign, 1985
Ph.D. in Computer Science, University of Illinois at Urbana/Champaign, 1988

Research

Teaching

Personal

Contact

Note to Grad-Student Applicants

Research Interests and Publications

As a member of the Artificial Intelligence Laboratory I lead the Machine Learning Research Group which has explored a variety of areas:

Primary Research Areas (click on an area for related publications):

Natural Language Learning: Learning for syntactic and semantic parsing, lexicon acquisition, information extraction, language generation, machine translation, and word sense disambiguation.
Connecting Language and Perception: Learning language given only its perceptual context as supervision.
Statistical Relational Learning : Learning methods that combine the strengths of predicate logic and probability.
Abductive Reasoning : Producing the best explanation for observed evidence using both logical and probabilistic reasoning.
Information Extraction: Identifying specific pieces of structured data in web pages or natural-language documents.
Transfer Learning : Using previously acquired knowledge to aid learning on new related problems.
Text Categorization and Clustering : Supervised and unsupervised classification of documents and web pages.
Text Data Mining: Discovering knowledge from text using information extraction and rule induction.
Record Linkage & Duplicate Detection : Identifying textually similar but distinct database records that refer to the same entity.
Bioinformatics : Learning to extract knowledge from biomedical literature.
Semi-Supervised Learning : Learning from a mixture of labeled and unlabeled data.
Ensemble Learning : Learning effective committees of hypotheses.
Active Learning : Automated selection of good training examples for supervised or semi-supervised learning.
Learning for Recommender Systems: Content-based and collaborative recommending.
Inductive Logic Programming: Learning Prolog programs (rules in first-order predicate logic) from examples.
Knowledge-Base and Theory Refinement: Automatically modifying rule bases and Bayesian networks to fit empirical data.

For a complete list of areas and publications, see the UT Machine Learning Research Group home page. Also see my profile on Google Scholar.

Current Research Group Meetings:

NLL: Natural Language Learning
CLAMP: Connecting Language and Perception
DEFT: Statistical Relational Learning for Textual Inference

Additional Affiliations:

I am also a member of the UT Computational Linguistics Lab.
I am also affiliated with the UT Division of Statistics and Scientific Computation.
I am also affiliated with the UT Center for Computational Biology and Bioinformatics.
I was President of the International Machine Learning Society from 2008-2011.
I was program co-chair (with Yolanda Gil) of the Twenty-First National Conference on Artificial Intelligence (AAAI-06) in Boston, July 16-20, 2006.
I was general chair of the joint Human Language Technology Conference / Empirical Methods in Natural Language Processing Conference for 2005 (HLT/EMNLP-05).
I was elected a Fellow of the American Association for Artificial Intelligence (AAAI) in 2005 "For significant contributions to machine learning, particularly explanation-based learning, theory refinement, and learning for natural-language processing."
I was elected a Fellow of the Association for Computing Machinery (ACM) in 2010 "For contributions to machine learning and natural language processing."

Research Demos:

See a demo of our work on Learning to Sportscast.
See a demo of our work on Learning to Follow Navigation Instructions.

Vita:

See my complete vita (in PDF).

Research Talks:

See Powerpoint presentations for some of my recent talks.

Course Information

Personal History

I grew up in the 60's and 70's in the small town of O'Fallon Illinois where starting in 1967 I attended St. Clare grade school and, starting in 1975, O'Fallon Township Highschool. See a scanned version of a paper I wrote for a high-school English class when I was only 17 years old entitled "High-level Artificial Intelligence: An Imminent Possibility with an Enormous Potential for Good". My enthusiasm for AI started early and has not waned; however, my expections about AI's rate of progress and its positive social implications have matured and (hopefully) become more realistic.

In the fall of 1979, I went to the University of Illinois in Champaign-Urbana to obtain all of the degrees listed above. In December 1987, I completed my Ph.D. thesis under the direction of Prof. Gerald DeJong and then began as a faculty member here in the Department of Computer Science at the University of Texas at Austin where I am enjoying the third decade of a hopefully long academic career.

See more information on my academic genealogy, which traces my professorial lineage back through Danish Linguists to German Theologians.

Contact Information

Office:: 3.512 GDC , (512) 471-9558
Email address:: mooney@cs.utexas.edu
Fax:: (512) 471-8885
Postal address:: Department of Computer Science
The University of Texas at Austin
2317 Speedway, Stop D9500
Austin, Texas 78712-1757
U.S.A.
Home address:: 4707 Eby Lane
Austin, Texas 78731-4507
U.S.A.

Note to Potential Grad-Student and Internship Applicants

Unfortunately, I am unable to personally respond to email requests regarding application to our graduate program or other solicitations for positions in my research lab. I encourage potential graduate-student applicants to see the department information on applying to our graduate program. Graduate-student applicants interested in my research are encouraged to clearly state such interests in their "statement of purpose." I currently have no funding to support summer internships.

mooney@cs.utexas.edu