Current News

Upcoming events and recent announcements. 

Past Outreach

Previous ceremonies, news, and announcements. 

What to Expect

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Open Events

Showcases, Seminars, & Panels

CADS host various forms of research presentations that will be of interest to our networks. These scheduled presentations are open to faculty and the broader TXST community. 

In 2026 so far, we have held various interdisciplinary seminars, two research showcases, and faculty panels aimed at advancing the CADS mission and highlight the research and work being done throughout Texas State.

Faculty & Collaboration Focused

Research Discussions

CADS supports researchers and faculty through targeted events, workshops, and info sessions focused on data science, AI, and high-performance computing. CADS connects faculty with tools, collaborators, funding opportunities, and industry expertise to strengthen research innovation across campus. Through the CADS Network, the center also fosters academic-industry partnerships and welcomes collaborative research ideas that benefit from interdisciplinary expertise.

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CADS Calendar

Expand Event List

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From HOW to learn to WHAT to learn in Multiagent Systems and Robotics
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Location:
Alkek Library; Alkek 441 Conference Room
Cost:
Free
Contact:
Destinee Leyva cads@txstate.edu or dal117@txstate.edu
Campus Sponsor:
Center for Analytics and Data Science
The Center is proud to host Dr. Peter Stone, Truchard Foundation Chair in Computer Science and Head of UT Austin’s School of Computing, Founding Director of Texas Robotics, and Chief Scientist at Sony AI.

Join us for a distinguished speaker event!

There has been a lot of exciting recent progress on new and powerful machine learning algorithms and architectures: how to learn. But for autonomous agents acting in the dynamic, uncertain world, it is at least as important to be able to identify which concepts and subproblems to focus on: what to learn.


Led by Dr. Stone, this talk presents methods for identifying what to learn within the framework of reinforcement learning, focusing especially on applications in multiagent systems and robotics. Click here for more information
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