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AI x Robotics Symposium Showcases Breakthrough Research at UT Austin
From March 4 to 6, the University of Texas at Austin hosted its dynamic three-day AI + Robotics Research Symposium, co-hosted by the Texas Robotics and Machine Learning Lab, with strong support from the UT Austin Amazon Science Hub.
The University of Texas at Austin hosted its inaugural AI x Robotics Research Symposium, a three-day event that brought together leading voices from academia and industry to explore the intersection of robotics, artificial intelligence, and machine learning.
Co-organized by Texas Robotics and the Machine Learning Lab, with support from the UT Austin Amazon Science Hub, the event featured keynote addresses, panel discussions, faculty talks, graduate student presentations, live demonstrations, and lab tours. The symposium welcomed more than 200 attendees, including representatives from Amazon, NVIDIA, Robust.AI, Booster Robotics, and XTX Markets.
Day 1: Robotics Research and General-Purpose Autonomy
The symposium opened with a keynote by Rodney Brooks, co-founder of Robust.AI and iRobot, who delivered “Hype-ospheric Disturbance of Robotics Research/Startup Balance.” Brooks reflected on the evolution of robotics innovation and emphasized the long-term development needed to build impactful, reliable systems.
Texas Robotics faculty members presented research highlights including:
Dr. Yuke Zhu, director of the Robot Perception and Learning Lab, on “Building Generalist Robot Autonomy with the Data Pyramid.”
Dr. Nick Fey, director of the Systems for Augmenting Human Mechanics Lab, on wearable robotics and assistive mobility.
In a panel on General-Purpose Robotics, Professors Peter Stone, David Fridovich-Keil, and Roberto Martín-Martín discussed the challenges of designing robots that can adapt to unstructured, human-centered environments.
Industry guest Chaoyi Li, Head of Globalization at Booster Robotics, demonstrated the capabilities of their latest humanoid robot and spoke on the emerging ecosystem of embodied AI.
The day concluded with a panel on Academia vs. Industry featuring Kyle Lilly, Farshid Alambeigi, and José del R. Millán, who explored how each sector contributes to the progress of robotics innovation.
Attendees also heard from Texas Robotics graduate students during a lightning talk session and poster showcase, followed by lab tours and live robot demos throughout the Anna Hiss Gymnasium.
Day 2: AI in the Real World
Day two highlighted applied AI and its growing presence in everyday life.
Amazon senior engineers Adam Fineberg and James Ballantyne introduced Amazon Rufus, a shopping assistant powered by large language models. In a follow-up panel, they joined Professors Roberto Martín-Martín and Peter Stone to discuss the technical challenges of integrating robots into home environments.
UT faculty members Ann Majewicz Fey, Jon Tamir, Alex Huth, and Vagheesh Narasimhan led a panel on AI and Machine Learning in Healthcare, sharing how data-driven tools are shaping personalized medicine, imaging, and neurotechnology.
The day concluded with an exclusive networking reception hosted by the UT Austin Amazon Science Hub.
Day 3: AI at Scale and Industry Collaboration
The final day focused on scaling AI and strengthening industry-academia partnerships.
Dr. Atlas Wang, Research Director at XTX Markets, delivered a keynote on building scalable AI systems for high-impact use cases, encouraging deeper collaboration between academic researchers and commercial innovators.
The Machine Learning Lab hosted its own poster session featuring graduate research in computer vision, model robustness, and learning theory.
Mike Hollinger, Director of Product Management at NVIDIA, closed the symposium with a talk on turning AI-driven robotics concepts into real-world solutions, detailing how NVIDIA is deploying models across logistics, manufacturing, and consumer robotics.