Event
Future Leaders in Robotics and AI Seminar: Ran (Thomas) Tian
Friday, April 25, 2025
2:30 p.m.-3:00 p.m.
https://go.umd.edu/FutureLeaders
Yancy Diaz-Mercado
301 405 6506
yancy@umd.edu
Towards Safe and Aligned Embodied AI in the Era of Robotics Foundation Models
Ran (Thomas) Tian
PhD Student
University of California Berkeley
Abstract
Robotics foundation models have revolutionized how robots perceive environments, learn from people, and interact with them. By seeing massive amounts of data, these models can learn implicit representations of the world and complex daily tasks. Despite the remarkable progress, robots relying on these models don’t inherently become better at doing what humans prefer. Often, they become less inclined to act in accordance with human preferences because the objectives suitable for training these large-scale paradigms are only proxies for what we—the users and stakeholders—care about. By optimizing an incomplete or misspecified objective, these robotics models lead to undesirable behaviors at best and safety hazards at worst. In this talk, I will introduce our efforts to bring the success of preference alignment, widely adopted in non-embodied foundation models (e.g., large language models), to embodied contexts such as robot manipulation and autonomous driving, enabling robots to align their behavior with human preferences in the open world.
Biography
Ran (Thomas) is a final-year PhD student at UC Berkeley. His research lies at the intersection of robotics and AI, with a focus on enabling robotics foundation models to serve humans at scale and in real-world environments. Throughout his PhD, he has developed new algorithms and practical solutions for addressing safety and alignment challenges that arise throughout the entire “life-cycle” of robotics foundation models, from pre-training to post-training alignment to deployment. He also spent two years at Waymo working on foundation models for autonomous driving while pursuing his PhD. His work has been recognized with several prestigious awards, including the World AI Conference Rising Star (2024), Qualcomm Innovation Fellowship (2024), Baidu AI Fellowship (2024), ICRA Best Paper Award (2024), and Robotics: Science and Systems Pioneer (2024).
About the Seminar Series
The Maryland Robotics Center's Future Leaders in Robotics and AI Seminar Series at the University of Maryland is a nationwide online seminar series for PhD students, postdoctoral researchers, and early-career professionals. The seminar series highlights the latest research and innovation in the field of robotics and AI. The series is intended to provide exposure and mentorship opportunities to the speakers, build a network of innovators across the country, and support the speakers’ career planning.
The seminars are held on select dates during spring. There are two speakers per seminar. Each speaker gives a 20-minute research presentation followed by a Q&A segment. Immediately after the second seminar, the speakers participate in a discussion with faculty. For more information, please visit: https://robotics.umd.edu/FutureLeaders
