Liangkai Liu (刘良凯)

I am an assistant professor in Department of Computer Science at Texas Tech University and the director of the Safe and Efficient Autonomy Laboratory (SEAL Lab). Previously, I’m a postdoc research fellow in the Real-Time Computing Laboratory at the University of Michigan, working with Prof. Kang G. Shin. I received my Ph.D. in Computer Science from Wayne State University in May 2023, where I was supervised by Prof. Weisong Shi.

Research Focus

My research focuses on building safe, predictable, and energy-efficient ML systems for safety-critical cyber-physical systems (CPS) — from autonomous driving to robotics and beyond. I develop novel cross-layer systems (model/algorithms, middleware system, operating system, etc.) to achieve these goals. I’m particularly interested in:

Foundation Models for Autonomy
Computing Systems for Robotics
Physics Intelligence

I am actively recruiting PhD students and interns — see the Openings page for details.

Research Overview

news

August 2026	Invited to join the IEEE Embedded Systems Letters (ESL) Editorial Board as an Associate Editor!
June 2026	Invited to join the Program Committee of RTSS 2026!
September 2025	Invited to give a talk at the DSL Seminar at University of Pennsylvania!
September 2025	Invited to give a lightning talk at NSF CSR PI meeting!
August 2025	We release pPerf — A Multi-Granularity Profiling Tool for Multi-Tenant & Multi-Modality DNNs!
July 2025	Invited to serve as TPC for DSC 2025, MOST 2025.
February 2025	Invited to serve as the Publication Chair for SEC 2025.
August 2024	NSF CNS has awarded our project “Predictable Multi-Tenant DNN Inference for Autonomous Driving (CNS-2343601)”. Thanks, NSF!
December 2023	Congratulations to Sanjith Udupa, my summer intern student, for being admitted to the class of 2028 at MIT!
December 2023	Invited to serve as the the Web Chair for MobiCom 2024.

selected publications

(* represents co-first author)

[RTSS '24] RT-BEV: Enhancing Real-Time BEV Perception for Autonomous Vehicles

Liangkai Liu, Jinkyu Lee, Kang G. Shin

45th IEEE Real-Time Systems Symposium

[Paper] [Code] [Bib]

@inproceedings{liu2024bev,
  title = {RT-BEV: Enhancing Real-Time BEV Perception for Autonomous Vehicles},
  author = {Liu, Liangkai and Lee, Jinkyu and Shin, Kang G.},
  booktitle = {45th IEEE Real-Time Systems Symposium},
  year = {2024}
}

[ICCAD '24] AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge

Chao Wu^*, Yifan Gong^*, Liangkai Liu^*, Mengquan Li, Yushu Wu, Xuan Shen, Zhimin Li, Geng Yuan, Weisong Shi, Yanzhi Wang

International Conference on Computer-Aided Design (ICCAD)

[Paper] [Bib]

@inproceedings{wu2024aye,
  title = {AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge},
  author = {Wu, Chao and Gong, Yifan and Liu, Liangkai and Li, Mengquan and Wu, Yushu and Shen, Xuan and Li, Zhimin and Yuan, Geng and Shi, Weisong and Wang, Yanzhi},
  booktitle = {International Conference on Computer-Aided Design (ICCAD)},
  year = {2024}
}

[ICRA '23] An Open Approach to Energy-Efficient Autonomous Mobile Robots

Liangkai Liu, Ren Zhong, Aaron Willcock, Nathan Fisher, Weisong Shi

IEEE International Conference on Robotics and Automation (ICRA)

[Paper] [Bib]

@inproceedings{liu2023open,
  title = {An Open Approach to Energy-Efficient Autonomous Mobile Robots},
  author = {Liu, Liangkai and Zhong, Ren and Willcock, Aaron and Fisher, Nathan and Shi, Weisong},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  year = {2023}
}

[IEEE TITS '23] Fuel Rate Prediction for Heavy-Duty Trucks

Liangkai Liu, Wei Li, Dawei Wang, Yi Wu, Ruigang Yang, Weisong Shi

IEEE Transactions on Intelligent Transportation Systems

[Paper] [Code] [Bib]

@article{liu2023fuel,
  title = {Fuel Rate Prediction for Heavy-Duty Trucks},
  author = {Liu, Liangkai and Li, Wei and Wang, Dawei and Wu, Yi and Yang, Ruigang and Shi, Weisong},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
  volume = {24},
  number = {8},
  pages = {8222--8235},
  year = {2023},
  publisher = {IEEE}
}

[RTSS '22] Prophet: Realizing a Predictable Real-Time Perception Pipeline for Autonomous Vehicles

Liangkai Liu, Zheng Dong, Yanzhi Wang, Weisong Shi

IEEE Real-Time Systems Symposium (RTSS)

[Paper] [Bib]

@inproceedings{liu2022prophet,
  title = {Prophet: Realizing a Predictable Real-Time Perception Pipeline for Autonomous Vehicles},
  author = {Liu, Liangkai and Dong, Zheng and Wang, Yanzhi and Shi, Weisong},
  booktitle = {IEEE Real-Time Systems Symposium (RTSS)},
  pages = {305--317},
  year = {2022},
  organization = {IEEE}
}

[Springer '21] Computing Systems for Autonomous Driving

Weisong Shi, Liangkai Liu

[Paper] [Bib]

[IoTJ '20] Computing Systems for Autonomous Driving: State of the Art and Challenges

Liangkai Liu, Sidi Lu, Ren Zhong, Baofu Wu, Yongtao Yao, Qingyang Zhang, Weisong Shi

IEEE Internet of Things Journal

[Paper] [Bib]

@article{liu2020computing,
  title = {Computing Systems for Autonomous Driving: State of the Art and Challenges},
  author = {Liu, Liangkai and Lu, Sidi and Zhong, Ren and Wu, Baofu and Yao, Yongtao and Zhang, Qingyang and Shi, Weisong},
  journal = {IEEE Internet of Things Journal},
  volume = {8},
  number = {8},
  pages = {6469--6486},
  year = {2020},
  publisher = {IEEE}
}

[PIEEE '19] Edge Computing for Autonomous Driving: Opportunities and Challenges

Shaoshan Liu, Liangkai Liu, Jie Tang, Bo Yu, Yifan Wang, Weisong Shi

Proceedings of the IEEE

[Paper] [Bib]

@article{liu2019edge,
  title = {Edge Computing for Autonomous Driving: Opportunities and Challenges},
  author = {Liu, Shaoshan and Liu, Liangkai and Tang, Jie and Yu, Bo and Wang, Yifan and Shi, Weisong},
  journal = {Proceedings of the IEEE},
  volume = {107},
  number = {8},
  pages = {1697--1716},
  year = {2019},
  publisher = {IEEE}
}

[SEC '19] E2M: An Energy-Efficient Middleware for Computer Vision Applications on Autonomous Mobile Robots

Liangkai Liu, Jiamin Chen, Marco Brocanelli, Weisong Shi

Proceedings of the 4th ACM/IEEE Symposium on Edge Computing

[Paper] [Bib]

@inproceedings{liu2019e2m,
  title = {E2M: An Energy-Efficient Middleware for Computer Vision Applications on Autonomous Mobile Robots},
  author = {Liu, Liangkai and Chen, Jiamin and Brocanelli, Marco and Shi, Weisong},
  booktitle = {Proceedings of the 4th ACM/IEEE Symposium on Edge Computing},
  pages = {59--73},
  year = {2019}
}

[SEC '18] SafeShareRide: Edge-based Attack Detection in Ridesharing Services

Liangkai Liu, Xingzhou Zhang, Mu Qiao, Weisong Shi

IEEE/ACM Symposium on Edge Computing (SEC)

[Paper] [Bib]

@inproceedings{liu2018safeshareride,
  title = {SafeShareRide: Edge-based Attack Detection in Ridesharing Services},
  author = {Liu, Liangkai and Zhang, Xingzhou and Qiao, Mu and Shi, Weisong},
  booktitle = {IEEE/ACM Symposium on Edge Computing (SEC)},
  pages = {17--29},
  year = {2018},
  organization = {IEEE}
}

[HotEdge '18] SafeShareRide: Edge-based Attack Detection in Ridesharing Services

Liangkai Liu, Xingzhou Zhang, Mu Qiao, Weisong Shi

USENIX Workshop on Hot Topics in Edge Computing (HotEdge 18)

[Paper] [Bib]

@inproceedings{liu2018hotedge,
  title = {{SafeShareRide}: Edge-based Attack Detection in Ridesharing Services},
  booktitle = {USENIX Workshop on Hot Topics in Edge Computing (HotEdge 18)},
  author = {Liu, Liangkai and Zhang, Xingzhou and Qiao, Mu and Shi, Weisong},
  year = {2018.},
  address = {Boston, MA},
  url = {https://www.usenix.org/conference/hotedge18/presentation/liu},
  publisher = {USENIX Association}
}