Dan Roth
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Comment: According to academic notability guidelines, individuals are notable if they are elected fellows of learned societies in which being a fellow is a high honor. The AAAS is such a society. Robert McClenon (talk) 00:01, 10 January 2016 (UTC)
- Comment: DGG Comments? As I'm not sure if this is notable and acceptable for the professors notability guidelines. SwisterTwister talk 23:15, 9 January 2016 (UTC)
- Comment: Add wikilinks, such as to American Association for the Advancement of Science and other organizations of which he is a fellow. These are needed to establish that being a fellow of the AAAS is a high honor that qualifies for academic notability guidelines. Robert McClenon (talk) 20:16, 9 January 2016 (UTC)
Dan Roth | |
|---|---|
.jpg?lang=en) Photo was taken in 2011 | |
| Born | |
| Alma mater | Harvard University |
| Known for | Joint Learning and Inference: ILP formulations of NLP tasks...[1] , Machine Learning for NLP, Probabilistic Reasoning |
| Scientific career | |
| Fields | Computer Science, Machine Learning, Natural Language Processing, Automated reasoning, Information Extraction. |
| Institutions | University of Illinois at Urbana-Champaign |
| Doctoral advisor | Leslie Valiant |
| Website | l2r |
Dan Roth is a professor in the Department of Computer Science and the Beckman Institute at the University of Illinois at Urbana-Champaign[2]. He holds faculty positions also at the Statistics [3], Linguistics [4] and ECE Departments [5] and at the graduate School of Library and Information Science [6], and is an adjoint professor at the Toyota Technological Institute at Chicago [7]
Roth is a Fellow of the American Association for the Advancement of Science (AAAS)[8], the Association of Computing Machinery (ACM)[9], the Association for the Advancement of Artificial Intelligence (AAAI) [10] , and the Association of Computational Linguistics (ACL) [11], for his contributions to Machine Learning and to Natural Language Processing.
Roth’s research[12] focuses on the computational foundations of intelligent behavior. He develops theories and systems pertaining to intelligent behavior using a unified methodology, at the heart of which is the idea that learning has a central role in intelligence. His work centers around the study of machine learning and inference methods to facilitate natural language understanding. In doing that he has pursued several interrelated lines of work that span multiple aspects of this problem - from fundamental questions in learning and inference and how they interact[13], to the study of a range of natural language processing (NLP) problems and developing advanced machine learning based tools for natural language applications [14] [15] that are being used widely by the research community and commercially.
Roth is known for his work on probabilistic reasoning (including its complexity[16] and probabilistic lifted inference [17]), Constrained Conditional Models (ILP formulations of NLP problems) and constraints driven learning [18][19], part-based (constellation) methods in object recognition [20], response based Learning [21], and for developing state-of-the-art NLP and Information extraction tools, including NER, Coreference Resolution, Wikification, SRL, ESL Text Correction and more[22]
Roth is the Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR) [23] and has served on the editorial board of several of the major journals in his research areas. He was the program chair of AAAI'11[24], ACL'03 [25] and CoNLL'02 [26] and serves regularly as an area chair and senior program committee member in the major conferences in his research areas. Roth got his B.A Summa cum laude in Mathematics from the Technion, Israel and his Ph.D in Computer Science from Harvard University in 1995[27]
References
- ^ Constrained Conditional Models
- ^ Dan Roth's Faculty Listing at UIUC
- ^ UIUC Statistics Department Faculty Listing
- ^ UIUC Linguistics Department Faculty Listing
- ^ UIUC ECE Department Faculty Listing
- ^ Affiliated Faculty at Library and Information Science at UIUC
- ^ Toyota Technical Institute Faculty Listing
- ^ AAAS List of Fellows
- ^ ACM Fellows
- ^ AAAI List of Fellows
- ^ ACL Fellows
- ^ Dan Roth's Publication Page
- ^ R. Khardon and D. Roth,Learning to Reason, Journal of the ACM (1997)
- ^ Illinois Cognitive Computation Group Demo Page
- ^ Illinois Cognitive Computation Group Software Page
- ^ D. Roth, D. Roth, On the hardness of approximate reasoning, Artificial Intelligence (1996)
- ^ R. Braz, E. Amir and D. Roth, Lifted First-Order Probabilistic Inference, IJCAI, 2005.
- ^ M. Chang and L. Ratinov and D. Roth, Structured Learning with Constrained Conditional Models, Machine Learning (2012)
- ^ D. Roth and W. Yih, A Linear Programming Formulation for Global Inference in Natural Language Tasks, CoNLL (2004)
- ^ S. Agarwal and A. Awan and D. Roth, Learning to Detect Objects in Images via a Sparse, Part-Based Representation, IEEE Transactions on PAMI (2004)
- ^ J. Clarke and D. Goldwasser and M. Chang and D. Roth, Driving Semantic Parsing from the World's Response, CoNLL (2010)
- ^ Illinois Cognitive Computation Group Demo Page
- ^ JAIR Masthead
- ^ AAAI-11
- ^ ACL 2003
- ^ ConLL 2002
- ^ Dan Roth's Webpage