Doctoral advisor Leslie Valiant Academic advisor Leslie Valiant | Alma mater Harvard University | |
 | ||
Institutions University of Illinois at Urbana-Champaign Known for Joint Learning and Inference: ILP formulations of NLP tasks..., Machine Learning for NLP, Probabilistic Reasoning Fields Computer Science, Machine learning, Natural language processing Institution University of Illinois at Urbana–Champaign | ||
Learning and inference for natural language understanding dan roth
Dan Roth is a Founder Professor of Engineering at the University of Illinois at Urbana-Champaign. He is a professor in the Department of Computer Science and the Beckman Institute at the University of Illinois at Urbana-Champaign and holds faculty positions also at the Statistics, Linguistics and ECE Departments and at the graduate School of Library and Information Science, and is an adjoint professor at the Toyota Technological Institute at Chicago.
Contents
Dan roth breathe
Biography
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.
Professional career
Roth is a Fellow of the American Association for the Advancement of Science (AAAS), the Association of Computing Machinery (ACM), the Association for the Advancement of Artificial Intelligence (AAAI), and the Association of Computational Linguistics (ACL).
Roth’s research 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, to the study of a range of natural language processing (NLP) problems and developing advanced machine learning based tools for natural language applications.
Roth has worked on probabilistic reasoning (including its complexity and probabilistic lifted inference ), Constrained Conditional Models (ILP formulations of NLP problems) and constraints driven learning, part-based (constellation) methods in object recognition, response based Learning, 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.
Roth is the Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR).