CSEE Distinguished Speaker Series

Open Issues in Open World Learning

Walter J. Scheirer
Dennis O. Doughty Collegiate Professor of Engineering
University of Notre Dame

11:30-12:30 ET, Monday, March 30, 2026, UMBC ITE 459 and online

Meaningful progress has been made in open world learning (OWL), enhancing the ability of agents to detect, characterize, and incrementally learn novelty in dynamic environments. However, novelty remains a persistent challenge for agents relying on state-of-the-art learning algorithms. This talk considers the current state of OWL, drawing on insights from a recent DARPA research program on this topic. I identify open issues that impede further advancements spanning theory, design, and evaluation. In particular, I emphasize the challenges posed by dynamic scenarios that are crucial to understand for ensuring the viability of agents designed for real-world environments. The talk provides suggestions for setting a new research agenda that effectively addresses these open issues.

Dr. Scheirer's research interests within computer science include artificial intelligence, computer vision, machine learning, and digital humanities. His research has helped establish the areas of open set recognition & open world learning in computer vision.  He serves on the IEEE CS Board of Governors, CTO of the Computer Vision Foundation, and Chair Emeritus of IEEE PAMI-TC. He received his Ph.D. from the University of Colorado and his M.S. and B.A. degrees from Lehigh University. Prof. Scheirer is also a recognized cultural critic and historian, commenting on the social context of emerging technologies, such as his most recent book: A History of Fake Things on the Internet.