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SEQUENCE:1
X-APPLE-TRAVEL-ADVISORY-BEHAVIOR:AUTOMATIC
204566
20250218T114903Z
DTSTART;TZID=America/New_York:20250226T140000
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 0250226T150000
URL;TYPE=URI:/news/calendar/events/robot
 ics-engineering-colloquium-speaking-series-dr-chen-tang
Robotics Engineering Colloquium Speaking Series: Dr. Chen Tang
Learning and Control for Human-Centered Autonomy\n\n\n\n      \n      \n\n\n\nAbstract:
  Robots have been successfully deployed in controlled, robot-centered envi
 ronments. The next frontier lies in developing intelligent robots capable 
 of operating in open-world, human-centered environments, where they can as
 sist and serve humans, generating broad societal benefits. Achieving this 
 vision requires a paradigm shift in control design鈥攆rom focusing solely 
 on robots to modeling and controlling the complex mix-autonomy system. It 
 remains challenging to create robots that can safely operate around humans
  and effectively serve every individual鈥檚 utility. In this talk, I will 
 present my research to addressing these challenges, with an emphasis on ap
 plication in autonomous driving. First, I will introduce our approaches fo
 r synthesizing controllers catering to every individual user鈥檚 requireme
 nt, leveraging the synergies of human data, reinforcement learning, and mo
 del predictive control. Second, I will briefly summarize my efforts on imp
 roving the robustness of data-driven human traffic models by improving the
 ir representations of human interactions. I will conclude by outlining nex
 t steps toward the widespread adoption of robots in open-world, human-cent
 ered environments, including transportation systems and beyond.\nBio: Chen
  Tang is a Postdoctoral Fellow in Computer Science at UT Austin. Prior to 
 that, he was a Postdoctoral scholar in Mechanical Engineering at UC Berkel
 ey. He received his Ph.D. in Mechanical Engineering from UC Berkeley in 20
 22 and his bachelor鈥檚 degree in mechanical engineering from HKUST in 201
 6. He received the ASME DSCD Rising Star Awards in 2022 and was selected a
 s an RSS Pioneer (in Robotics) in 2023. His research interest lies at the 
 interaction of control, robotics, and learning, with applications in auton
 omous driving and social robot navigation.\nZoom link: https://wpi.zoom.us
 /j/93413349160\n
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