Dr. Roth is the Eduardo D. Glandt Distinguished Professor at the Department of Computer and Information Science, University of Pennsylvania. He was a Founder Professor of Engineering at the Computer Science Department at the University of Illinois at Urbana-Champaign, with positions at the Beckman Institute, the Statistics, Linguistics and ECE Departments, and at the Graduate School of Library and Information Science.
Dr. 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), for his contributions to Machine Learning and to Natural Language Processing. Dr. Roth was awarded the John McCarthy Award (2017).
He was recognized for major conceptual and theoretical advances in modeling natural language understanding, machine learning, and reasoning. Until February 2017 Roth was the Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR). Dr. Roth is also a co-founder and the chief scientist at NexLP, Inc., a startup that leverages the latest advances in Natural Language Processing (NLP), Cognitive Analytics, and Machine Learning in the legal and compliance domains.
More on Dr. Dan Roth at https://www.cis.upenn.edu/~danroth/
Research Interests:
- Natural Language Processing
- Artificial Intelligence
- Global Inference in NLP
- Integer Linear Programming
- Machine Learning in NLP
- Doctor of Philosophy (PhD) in Computer Science, Harvard University, USA
- Master of Science in Computer Science, Harvard University, USA
- Bachelors (Summa Cum Laude) in Mathematics, Technion (Israel Institute of Technology), Israel
- The 2020 Heilmeier Award for Excellence in Faculty Research, University of Pennsylvania, School of Engineering and Applied Science.
- The International Joint Conference on AI (IJCAI) John McCarthy Award, 2017.
- Eduardo D. Glandt Distinguished Professor, University of Pennsylvania.
- Founder Professor of Engineering, University of Illinois at Urbana-Champaign.
- David F. Linowes Faculty Fellow, Cline center for Democracy, University of Illinois, 2015,2016.
- Fellow, the American Association for the Advancement of Science (AAAS), 2014.
- S. Agarwal, A. Awan and D. Roth, (2004) “Learning to Detect Objects in Images via a Sparse, Part-Based Representation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20 (11).
- R. Braz, E. Amir and D. Roth, (2005) “Lifted First-Order Probabilistic Inference”, IJCAI'05.
- M. Chang and L. Ratinov and D. Roth, (2007) “Guiding Semi-Supervision with Constraint-Driven Learning”, ACL.
- M. Chang and V. Srikumar and D. Goldwasser and D. Roth, (2010) “Structured Output Learning with Indirect Supervision”, ICML.
- M. Chang and D. Goldwasser and D. Roth and V. Srikumar, (2010) “Discriminative Learning over Constrained Latent Representations”, NAACL.
- M. Chang, L. Ratinov and D. Roth, (2012) “Structured Learning with Constrained Conditional Models”, Machine Learning Journal, vol. 88 (3).
- M. Connor, C. Fisher and D. Roth (2012) “Starting from Scratch in Semantic Role Labeling: Early Indirect Supervision”, A Chapter invited to ”Cognitive Aspects of Computational Language Acquisition”, Afra Alishahi, Thierry Poibeau, Anna Korhonen, Editors. Springer.
- J. Clarke, D. Goldwasser, M. Chang and D. Roth, (2010) “Driving Semantic Parsing from the World’s Response”, CoNLL'10, The Annual Conference on Computational Natural Language Learning.
- A. R. Golding and D. Roth, (1999) “A Winnow-Based Approach to Spelling Correction”, Machine Learning, Special issue on Machine Learning and Natural Language Processing, Vol. 34 (1/3).
- P. Jindal and D. Roth, (2013) “Using Domain Knowledge and Domain-Inspired Discourse Model for Co-reference Resolution for Clinical Narratives”, JAMIA, J. of American Medical Informatics Association, Vol. 20 (2).
- R. Khardon and D. Roth, (1997) “Learning to Reason”, Journal of the Association for Computing Machinery, Vol. 44 (5).
- P. Kordjamshidi and D. Roth and H. Wu, (2015) “Saul: Towards Declarative Learning Based Programming” IJCAI’15.
- G. Kundu and V. Srikumar and D. Roth, (2013) “Margin-based Decomposed Amortized Inference”, ACL.
- J. Pasternack and D. Roth, “Latent Credibility Analysis”, WWW'13, 2013.
- D. Roth, (1996) “On the Hardness of Approximate Reasoning”, Artificial Intelligence, Vol. 82.
- D. Roth, (1999) “Learning in Natural Language”, IJCAI'99
- D. Roth, (1998) “Learning to Resolve Natural Language Ambiguities: A Unified Approach” AAAI'98.
- D. Roth and R. Samdani, (2009) “Learning Multi-Linear Representations”, Machine Learning, Volume 76 (2).
- D. Roth and W. Yih, (2004) “A Linear Programming Formulation for Global Inference in Natural Language Tasks”, CoNLL'04: The 8th Conference on Natural Language Learning.
- A. Rozovskaya ad D. Roth, (2014) “Building a State-of-the-Art Grammatical Error Correction System”, Transactionsof the Association for Computational Linguistics, Vol 2.