Qin Lin, 林勤

Assistant Professor. University of Houston

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Technology Building, T2 304C, 4230 MLK Blvd.,

Houston, TX 77204-4021

I am a tenure-track assistant professor and the director of the Assured and Intelligent Robotics (AIR) Lab at the Cullen College of Engineering, University of Houston. I completed my postdoctoral training at the Robotics Institute of Carnegie Mellon University, where my advisor was Prof. John M. Dolan. I earned my Ph.D. degree from Delft University of Technology, the Netherlands under the supervision of Prof. Sicco Verwer and Prof. Jan van den Berg. My research interests lie at the intersection of machine learning, control theory, and formal verification, with the goal of enhancing the reliability of autonomous systems.

This website will no longer be updated. Please visit our group’s new website at UH.

news

Sep 1, 2024 My team has moved to the University of Houston to start a new chapter.
Jun 4, 2024 One paper accepted to IEEE CASE 2024.
May 10, 2024 Received CSU Faculty Merit Recognition Award, AY 2023-2024.
May 3, 2024 After the triumph of our first senior design team last year, my second supervised senior design team secured second place in this year’s engineering school’s annual competition. Their project is building an autonomous delivery cart from scratch.
May 1, 2024 One paper accepted to the IEEE Control Systems Letters (L-CSS).
Apr 8, 2024 I’m serving as an Associate Editor for IROS 2024.
Jan 29, 2024 One paper accepted to ICRA 2024.
Jan 10, 2024 I have been invited to serve on an NSF panel.
Nov 27, 2023 One paper accepted to IEEE Trans. on Intelligent Transportation Systems.
Sep 14, 2023 I will serve as an Associate Editor for IEEE Transactions on Vehicular Technology (TVT).
Jul 12, 2023 One paper accepted to CDC 2023.
May 26, 2023 I have received a grant award from NSF (“ERI: Operator-Automation Shared Protection for Security and Safety Assured Industrial Control Systems: Learning, Detection, and Recovery Control”, sole-PI, $200,000, 2023-2025, link).
May 5, 2023 My very first supervised senior design team secured the top spot in our engineering school’s annual competition. Their project is “Autonomous Nursery Cart”. You will enjoy watching their inspiring story unfold!
Mar 3, 2023 One paper accepted to IFAC 2023.
Jan 24, 2023 Received a $10,000 subaward from Ohio Cyber Range Institute for cybersecurity research of industrial control systems.
Jan 21, 2023 I will serve as an Associate Editor for IROS2023.
Jan 19, 2023 One paper accepted to ACC.
Dec 28, 2022 I will serve as an Associate Editor for IEEE Robotics and Automation Letters (RA-L).
Dec 13, 2022 Our team (PI: Dr. Yongxin Tao, co-PIs: Dr. Qin Lin, Dr. Wenbing Zhao, Dr. Navid Goudarzi) received a grant award ($1M, 2023-2025) from the Department of Education (ED).
Jun 30, 2022 Two papers accepted to IROS. :robot:
Apr 10, 2022 One paper accepted to IV, oral presentation, selection rate: ~10%.
Sep 19, 2021 Our team (Shivesh Khaitan, John M. Dolan, and myself) is the winner in the Competition for Motion Planning of Autonomous Vehicles (ITSC 2021), see the announcement and the leaderboard. :sparkles:

selected publications

  1. Adaptive Planning and Control with Time-Varying Tire Models for Autonomous Racing Using Extreme Learning Machine Dvij Kalaria*, Qin Lin, and John M. Dolan IEEE International Conference on Robotics and Automation, ICRA 2024 [abstract] [video] [link]
  2. Towards Safety Assured End-to-End Vision-Based Control for Autonomous Racing Dvij Kalaria*, Qin Lin, and John M. Dolan IFAC World Congress 2023 [abstract] [video]
  3. Delay-aware Robust Control for Safe Autonomous Driving and Racing Dvij Kalaria*, Qin Lin, and John M. Dolan IEEE Transactions on Intelligent Transportation Systems 2023 [abstract] [video] [link]
  4. Motion Planning by Search in Derivative Space and Convex Optimization with Enlarged Solution Space Jialun Li*, Xiaojia Xie, Qin Lin, Jianping He, and John M. Dolan IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022 [abstract] [video] [link]
  5. Online Adaptive Compensation for Model Uncertainty Using Extreme Learning Machine-based Control Barrier Functions Emanuel Munoz Panduro*, Dvij Kalaria, Qin Lin, and John M. Dolan IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022 [abstract] [video] [link]