Yulin Zhang
Postdoc
Email: yulin(at)cs.utexas.edu
Brief Bio
I am a Postdoc in LARG supervised by Dr. Peter Stone at the Department of Computer Science in UT Austin. I obtained my PhD from the Department of Computer Science and Engineering at Texas A&M University with Dr. Dylan A. Shell. My research studies reinforcement learning, planning and estimation techniques in autonomous driving, traffic management, automated robot design, and privacy-preserving applications. Previously, I was a visiting PhD student supervised by Dr. Antonio Franchi in the RIS team at LAAS-CNRS, and completed my master's and bachelor's degree at the University of Electronic Science and Technology of China.
I am a Postdoc in LARG supervised by Dr. Peter Stone at the Department of Computer Science in UT Austin. I obtained my PhD from the Department of Computer Science and Engineering at Texas A&M University with Dr. Dylan A. Shell. My research studies reinforcement learning, planning and estimation techniques in autonomous driving, traffic management, automated robot design, and privacy-preserving applications. Previously, I was a visiting PhD student supervised by Dr. Antonio Franchi in the RIS team at LAAS-CNRS, and completed my master's and bachelor's degree at the University of Electronic Science and Technology of China.
Research Overview
My dissertation involves a robot solving a planning problem, while being observed by an observer. It focuses on the design problems for both the robot and the observer. In particular, on the robot side, I am interested in searching for a plan and sensor design while constraining the information disclosed from the robot. On the observer side, I focus on the estimation process (including filtering and smoothing) and minimizing the internal representation of the observer's estimator.
My dissertation involves a robot solving a planning problem, while being observed by an observer. It focuses on the design problems for both the robot and the observer. In particular, on the robot side, I am interested in searching for a plan and sensor design while constraining the information disclosed from the robot. On the observer side, I focus on the estimation process (including filtering and smoothing) and minimizing the internal representation of the observer's estimator.
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Updates
- [03/2022]: Our paper "Nondeterminism subject to output commitment in combinatorial filters" is accepted by WAFR 2022.
- [02/2022]: Our paper "On nondeterminism in combinatorial filters" and "Camera-IMU Extrinsic Calibration Quality Monitoring" are accepted by ICRA 2022.
- [02/2021]: Our paper "Accelerating combinatorial filter reduction through constraints" is accepted by ICRA 2021.
- [05/2021]: I defened my dissertation !!! 👍
- [10/2020]: I presented my dissertation work at ICAPS Doctoral Consortium. See the video here.
- [4/2020]: Our paper "Cover combinatorial filters and their minimization problem" was accepted by WAFR 2020.
- [1/2020]: Our paper "Abstractions for computing all robotic sensors that suffice to solve a planning problem" was accepted by ICRA 2020.
- [12/2019]: Our paper "Plans that remain private even in hindsight" was accepted by PPAI20.
- [11/2019]: I was selected as a Graduate Teaching Fellow for spring 2020 semester.
- [11/2018]: I was selected as a WAFR Robot Guru Fellow to interact with a group of undergrads in WAFR 2018.
- [09/2018]: I passed my preliminary exam and dissertation proposal. Whoop!
- [09/2018]: Our paper "What does my knowing your plans tell me?" was accepted by IROS-CogRob 2018.
- [09/2018]: Our paper "Finding plans subject to stipulations on what information they divulge" was accepted by WAFR 2018.
- [09/2018]: I was supported by Tang Lixin Travel Scholarship and went for a cruise trip from Hong Kong to Singapore, via Vietnam and Thailand.
- [06/2018]: I was selected as a Chateaubriand Fellow to conduct a collaborative research at LAAS-CNRS in France.