Liangkai Liu (刘良凯)

liangkai@umich.edu

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Liangkai Liu is currently a Research Fellow working with Prof. Kang G. Shin in the Real-Time Computing Laboratory in the Computer Science and Engineering Department at The University of Michigan. His research is primarily at the intersection of Autonomous Driving and Computing Systems, focusing on building safe, predictable, and energy-efficient machine learning systems for autonomous vehicles and autonomous mobile robots.

Before that, he received his Ph.D. degree in computer science from Wayne State University in May 2023, supervised by Prof. Weisong Shi. He has collaborated/worked with researchers from Argonne National Laboratory, IBM Research, MIT Lincoln Laboratory, Inceptio, and Autoware.

news

Aug 09, 2024 NSF CNS has awarded our project “Predictable Multi-Tenant DNN Inference for Autonomous Driving (CNS-2343601)”. Thanks, NSF!
Jul 31, 2024 RT-BEV gets accepted by RTSS 2024!
Jun 20, 2024 One co-first authored paper accepted by ICCAD 2024!
Feb 20, 2024 One paper accepted by DAC 2024!
Dec 15, 2023 Congratulations to Sanjith Udupa, my summer intern student, for being admitted to the class of 2028 at MIT!

selected publications

(* represents co-first author)

  1. RTSS
    RT-BEV: Enhancing Real-Time BEV Perception for Autonomous Vehicles
    Liangkai Liu, Jinkyu Lee, and Kang G. Shin
    In 45th IEEE Real-Time Systems Symposium , 2024.
  2. ICCAD
    AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge
    Chao Wu*, Yifan Gong*Liangkai Liu* , and 7 more authors
    In International Conference on Computer-Aided Design (ICCAD) , 2024.
  3. ICRA
    An Open Approach to Energy-Efficient Autonomous Mobile Robots
    Liangkai Liu, Ren Zhong, Aaron Willcock , and 2 more authors
    In IEEE International Conference on Robotics and Automation (ICRA) , 2023.
  4. IEEE TITS
    Fuel Rate Prediction for Heavy-Duty Trucks
    Liangkai Liu, Wei Li, Dawei Wang , and 3 more authors
    IEEE Transactions on Intelligent Transportation Systems, 2023.
  5. RTSS
    Prophet: Realizing a Predictable Real-Time Perception Pipeline for Autonomous Vehicles
    Liangkai Liu, Zheng Dong, Yanzhi Wang , and 1 more author
    In IEEE Real-Time Systems Symposium (RTSS) , 2022.
  6. MLBench
    Understanding Time Variations of DNN Inference in Autonomous Driving
    Liangkai Liu, Yanzhi Wang, and Weisong Shi
    arXiv preprint arXiv:2209.05487, 2022.
  7. IoTJ
    Computing Systems for Autonomous Driving: State of the Art and Challenges
    Liangkai Liu, Sidi Lu, Ren Zhong , and 4 more authors
    IEEE Internet of Things Journal, 2020.
  8. PIEEE
    Edge Computing for Autonomous Driving: Opportunities and Challenges
    Shaoshan Liu, Liangkai Liu, Jie Tang , and 3 more authors
    Proceedings of the IEEE, 2019.
  9. SEC
    E2M: An Energy-Efficient Middleware for Computer Vision Applications on Autonomous Mobile Robots
    Liangkai Liu, Jiamin Chen, Marco Brocanelli , and 1 more author
    In Proceedings of the 4th ACM/IEEE Symposium on Edge Computing , 2019.
  10. SEC
    SafeShareRide: Edge-based Attack Detection in Ridesharing Services
    Liangkai Liu, Xingzhou Zhang, Mu Qiao , and 1 more author
    In IEEE/ACM Symposium on Edge Computing (SEC) , 2018.