Oct 14 - Advances in AI at SDSU

Join our virtual meetup to hear talks from AI researchers at San Diego State University.

Date, Time Location

Oct 14, 2026
9:00 AM - 11:00 AM PST
Online. Register for the Zoom!

Agent as Policy for Robotic Manipulation

This talk will introduces how a general-purpose agent can directly drive a physical robot throughout task execution without any task-specific or environment-specific training. We introduce Agent as Policy (AGP), which places task planning and execution under the agent’s control.

About the Speaker

Xiaobai Liu is a Professor of Computer Science at San Diego State University (SDSU), where he directs the Machine Vision and Perception Lab. Prior to joining SDSU in 2015, he conducted research and taught at UCLA.

Grounding Multimodal Open-World Learning for Physical AI

Physical AI systems such as robots, unmanned vehicles, and embodied agents must perceive and reason about a world that is dynamic, unstructured, and rarely matches their training distribution. Yet most multimodal models remain brittle when confronted with novel objects, unseen conditions, and a messy unstructured environment.

This talk develops how grounding perception across modalities and environments can make open-world learning more robust for physically situated systems. Drawing on our recent work, I will highlight the core challenges of multimodal open-world learning including out-of-distribution detection, distribution shift generalization, and cascaded semantic grounding and point toward multimodal systems that stay reliable when deployed in the unpredictable open world.

About the Speakers

Salimeh Sekeh is an Associate Professor of Computer Science at San Diego State University (SDSU), where she directs the Sekeh Laboratory. Her recognition includes an NSF CAREER Award and a Cisco research gift (both 2022), and the Maine College of Engineering and Computing Early Career Research Award (2023), along with multiple industry and federal research awards.

Mary Wisell is a second-year PhD student in the Sekeh Lab and leads the lab's work on environment-aware OOD detection and cascaded failure analysis for multimodal intelligence with several publications in top-tier Machine Learning and computer vision conferences.