[AI Seminar Series] REMINDER: Seminar by Prof. Zhe Xu, Friday May 15th, 12-1pm, MRB Seminar Room

[Vassilis Tsotras]

Reminder for the AI Seminar this Friday at noon; please use the link below
to register.
Sincerely,
V. Tsotras
--------------------------------------

On Sat, May 9, 2026 at 9:17 PM Vassilis Tsotras <vassilis.tsotras at ucr.edu>
wrote:

> The next AI Seminar will be on Friday May 15th, 12-1pm, in the MRB Seminar
> Room (1st floor).
>
> *** Pizza and refreshments will be provided ****
>
> To keep track of the number of attendees, please *register* at:
> https://www.eventbrite.com/e/ai-seminar-series-tickets-1989124134833
>
> The talk will be given by *Prof. Zhe Xu*, Arizona State University
>
> TITLE: Integrating Logic and Causal Reasoning for Learning and Control in
> Autonomous Systems
>
> ABSTRACT:
> Artificial intelligence, powered by data-driven methods, has surpassed
> human-level performance in many tasks. Yet deploying AI in autonomous
> systems remains fundamentally challenging due to limited interpretability,
> high data demands, and insufficient logical and causal reasoning in
> decision-making. To address these challenges, this talk presents
> interpretable and data-efficient learning approaches that integrate
> theories and techniques from machine learning, formal methods, and control
> theory. Unlike traditional learning approaches, these methods enable agents
> to reason over their learning processes, coordinate effectively with other
> agents, efficiently enhance operational capabilities to complete complex
> tasks in the presence of competitors or adversaries, and swiftly adapt to
> novel tasks and environments.
>
> The first part of the talk focuses on learning high-level logical and
> causal knowledge from data and its application to physical systems. I
> present state-of-the-art methods for learning temporal logic (TL) formulas
> and TL-based causal diagrams directly from data.The second part addresses
> improving the sample efficiency of reinforcement learning (RL) using
> high-level knowledge. I introduce a neuro-symbolic RL framework based on
> offline training followed by online fine-tuning, which enables an agent to
> reason about its exploration process and distill high-level knowledge from
> both offline datasets and online interactions to guide future exploration.
> I also present approaches that leverage large language models and
> counterfactual reasoning to further accelerate RL. The final part of the
> talk focuses on learning and control in multi-agent systems operating in
> cooperative, non-cooperative, and incomplete-information stochastic games,
> where logical and causal knowledge is discovered in a distributed manner.
>
>
> Bio:
>
> Zhe Xu is an Assistant Professor in the School for Engineering of Matter,
> Transport, and Energy at Arizona State University. Prior to joining ASU, he
> was a postdoctoral researcher at the Oden Institute for Computational
> Engineering and Sciences at The University of Texas at Austin. He received
> his Ph.D. in Electrical Engineering from Rensselaer Polytechnic Institute
> in 2018. Dr. Xu is a recipient of the NSF CAREER Award, the Howard Kaufman
> ’62 Memorial Fellowship, and the ASU Fulton Schools of Engineering Teaching
> Recognition Awards (2023–2025). His research interests include formal
> methods, autonomous systems, control systems, and reinforcement learning.
> He has developed learning, control, and verification methods with
> applications in robotics, power systems, smart buildings, and biological
> systems.
> ------------------------------------
> Sponsored by the RAISE at UCR Institute, the AI Seminar Series presents
> speakers working on cutting edge Foundational AI or applying AI in their
> research. The goal of these seminars is to inform the UCR community about
> current trends in AI research and promote collaborations between faculty
> in this emerging field. These seminars are open to interested faculty and
> graduate/undergraduate students. Please forward this email to other
> colleagues or students in your lab that may be interested. After the
> seminar a discussion will follow for questions, open problems, ideas for
> possible collaborations etc.
>
> Sincerely,
> Vassilis Tsotras
> Professor, CSE Department
> co-Director, RAISE at UCR Institute
>
> Amit Roy-Chowdhury
> Professor, ECE Department
> co-Director, RAISE at UCR Institute
>
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