Research Topics

Knowledge representation, natural language understanding, automated reasoning, declarative problem solving. We are particularly interested in applying automated reasoning techniques for solving inference problems stemming from natural language understanding domain. Also, our work spans theoretic foundations as well as practical implementations of methods for automated reasoning based on model generation.

Current Lab Members Dr. Yuliya Lierler Dr. Jorge Fandinno Daniel Bresnahan Zachary Hansen Joel Sare Nicholas Wilson
2019 ICLP  Academic Family Reunion

Research Projects

• Automated optimization of programs and processing tools in answer set programming
• Modularity for modeling and solving in declarative programming
• Answer set programming and solving
• Constraint answer set programming
• What lexical wide coverage resources can do for parsing
• Textual inference
• Causality in natural language understanding
• Syntactic parsing by means of declarative programming