Biography:Dan Roth
Dan Roth | |
|---|---|
.jpg) Dan Roth, 2011 | |
| Born | Haifa, Israel |
| Alma mater | Harvard University |
| Known for | Joint Learning and Inference: ILP formulations of NLP tasks...,[1] Machine Learning for NLP, Probabilistic Reasoning |
| Awards | ACM Fellow; IJCAI John McCarthy Award [2] [3] |
| Scientific career | |
| Fields | Computer Science, Machine Learning, Natural Language Processing, Automated reasoning, Information Extraction. |
| Institutions | University of Illinois at Urbana-Champaign, University of Pennsylvania |
| Doctoral advisor | Leslie Valiant |
| Website | www |
Dan Roth is the Eduardo D. Glandt Distinguished Professor of Computer and Information Science at the University of Pennsylvania.[4]
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.[5] He taught at the University of Illinois at Urbana-Champaign from 1998 to 2017 before moving to the University of Pennsylvania.[6]
Professional career
Roth is a Fellow of the American Association for the Advancement of Science (AAAS),[7] the Association for Computing Machinery (ACM),[8] the Association for the Advancement of Artificial Intelligence (AAAI),[9] and the Association of Computational Linguistics (ACL).[10]
Roth’s research[11] 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,[12] to the study of a range of natural language processing (NLP) problems and developing advanced machine learning based tools for natural language applications.[13]
Roth has made seminal contribution to the fusion of Learning and Reasoning,[14] Machine Learning with weak, incidental supervision,[15] and to machine learning and inference approaches to natural language understanding. Roth has worked 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] He has developed NLP and Information extraction tools that are being used broadly by researchers and commercially, including NER, coreference resolution, wikification, SRL, and ESL text correction.[13]
Roth is a co-founder of NexLP, Inc., a startup that applies natural language processing and machine learning in the legal and compliance domains. In 2020, NexLP was acquired by Reveal, Inc., an e-discovery software company.[22] He is currently on the scientific advisory board of the Allen Institute for AI.[23]
References
- ↑ Constrained Conditional Models
- ↑ "Welcome to IJCAI 2017!". https://ijcai-17.org/awards.html.
- ↑ "Roth honored with the IJCAI John McCarthy Award". https://cs.illinois.edu/news/roth-honored-ijcai-john-mccarthy-award.
- ↑ "Penn Engineering - Research Directory Profile". http://www.seas.upenn.edu/directory/profile.php?ID=233.
- ↑ "Dan Roth's Webpage". http://l2r.cs.uiuc.edu/.
- ↑ "Dan Roth - Main Page". http://l2r.cs.uiuc.edu/.
- ↑ AAAS List of Fellows
- ↑ "ACM Fellows". http://awards.acm.org/fellow/all.cfm.
- ↑ AAAI List of Fellows
- ↑ ACL Fellows
- ↑ Dan Roth's Publication Page
- ↑ R. Khardon and D. Roth,Learning to Reason, Journal of the ACM (1997)
- ↑ 13.0 13.1 Cognitive Computation Group Demo Page
- ↑ D. Roth,Learning to Reason: The Approach, (1996)
- ↑ D. Roth,Incidental Supervision, AAAI (2017)
- ↑ D. Roth, D. Roth, On the hardness of approximate reasoning, Artificial Intelligence (1996)
- ↑ R. de Salvo 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)
- ↑ "Reveal Acquires NexLP to become the leading AI-powered eDiscovery Solution" (Press release).
- ↑ "Scientific Advisory Board — Allen Institute for AI" (in en). https://allenai.org/scientific-advisory-board.
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