Ted Pedersen

Ted Pedersen is a Professor in the Department of Computer Science at the University of Minnesota Duluth, where he is part of the Swenson College of Science and Engineering. He serves as the Study Abroad Advisor for the CS Department and was a member of the UMN AI Task Force from January 2025 to August 2025, where he addressed questions regarding AI use at the University of Minnesota.

Dr. Pedersen's research focuses on computational linguistics and natural language processing, with particular expertise in word sense disambiguation, semantic similarity measurement, and biomedical text analysis. His work bridges theoretical computational linguistics with practical applications in healthcare informatics and social media analysis. He has developed several widely-used open-source tools including SenseClusters, WordNet::Similarity, and WordNet::SenseRelate that have become standard resources in the NLP community.

His publication record shows a clear evolution from foundational work in semantic similarity and word sense disambiguation toward contemporary applications in social media analysis, bias detection, and multilingual processing. Recent work demonstrates increasing focus on ethical AI considerations, particularly in sentiment analysis, offensive language detection, and news credibility assessment. His research maintains strong connections between theoretical linguistic frameworks and practical computational implementations.

• Multiple publications in AMIA Annual Symposium Proceedings
• Extensive work on semantic similarity measures in biomedical contexts
• Development of open-source NLP tools adopted by the research community
• Active participation in SemEval shared tasks since 2017

Dr. Pedersen actively mentors students through research opportunities in natural language processing, with current opportunities available for both undergraduate and graduate students. His teaching portfolio includes courses on Computer Ethics, Algorithms, Race and Computing, and advanced Natural Language Processing topics. He has taught consistently since at least 1999, demonstrating a long-standing commitment to computer science education.

His laboratory work focuses on developing computational approaches to linguistic problems, with particular emphasis on unsupervised and semi-supervised methods for semantic analysis. Current projects appear to focus on multilingual processing, social media analysis, and ethical considerations in AI systems.