Oct 14 - Advances in AI at SDSU

AI Professionals San Francisco Machine Learning & Agentic AI 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! (https://voxel51.com/events/advances-in-ai-at-sdsu-october-14-2026) 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 (https://www.linkedin.com/in/xiaobai-liu-33598336/) 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 (https://www.linkedin.com/in/salimeh-sekeh-65473344/) 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 (https://www.linkedin.com/in/mary-isabelle-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. Model-Free, Position-Free Signal Source Seeking Using Unmanned Maritime Systems Long-range signal source detection in open-world environments presents a significant challenge, mainly due to the detrimental effects of the environment on signals propagation paths and presence of extraneous signal sources. While distributed static sensing systems are often employed, achieving scalability and comprehensive coverage across expansive areas is cost-prohibitive. One affordable solution involves using low-cost autonomous unmanned vehicles (AUVs) that can leverage their mobility and actively explore the environment using extremum seeking control (ESC) algorithms. This talk presents novel ESC approaches to steer AUVs to sources of interest in an a priori unknown, highly non-convex map. About the Speaker Zahra Nili Ahmadabadi (https://www.linkedin.com/in/zahra-nili-ahmadabadi-phd-29113171) is Associate Professor with the Mechanical Engineering Department at San Diego State University (SDSU). She is a recipient of the ASME rising star award and ARO Early career award.