Knowledge Representation and Natural Language Understanding Lab

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 Zachary Hansen Eleuterio Juan Lillo Portero Keeran Dhakal Josh Gryzen
2019 ICLP Academic Family Reunion

Research Projects

• Tools and Methodologies for Verifying Answer Set Programs
• 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
• Semantic-based Information Extraction System from Textual Input

ZOOM-based Seminars

Seminars on Answer Set Programming hosted by the lab are linked here. If your are interested joining this ZOOM-based seminar send an email to aspseminar-join@lists.unomaha.edu with the word "subscribe" in the subject line.