J. Tang, et al., “$π$-Hub: Large-scale video learning, storage, and retrieval on heterogeneous hardware platforms,” Future Generation Computer Systems, vol. 102, pp. 514–523, 2020.

H. Zhao, Y. Rao, D. Li, J. Tang, and S. Liu, “A DAG Refactor Based Automatic Execution Optimization Mechanism for Spark,” in IFIP International Conference on Network and Parallel Computing, 2019, pp. 338–344.

S. Liu, L. Liu, J. Tang, B. Yu, Y. Wang, and W. Shi, “Edge Computing for Autonomous Driving: Opportunities and Challenges,” Proceedings of the IEEE, vol. 107, no. 8, pp. 1697–1716, 2019.

T. Y. Li and S. Liu, “Enabling Commercial Autonomous Space Robotic Explorers,” arXiv preprint arXiv:1908.04149, 2019.

S. Qin, Q. Liu, B. Yu, and S. Liu, “$π$-BA: Bundle Adjustment Acceleration on Embedded FPGAs with Co-observation Optimization,” in 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2019, pp. 100–108.

Y. Wang, S. Liu, X. Wu, and W. Shi, “CAVBench: A benchmark suite for connected and autonomous vehicles,” in 2018 IEEE/ACM Symposium on Edge Computing (SEC), 2018, pp. 30–42.

S. Akiki, Z. Yang, C. Liu, J. Tang, and S. Liu, “Energy-Aware Automatic Tuning of Many-Core Platform via Gradient Descent,” in 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2018, pp. 1199–1203.

J. Tang, S. Liu, B. Yu, and W. Shi, “PI-Edge: A Low-Power Edge Computing System for Real-Time Autonomous Driving Services,” arXiv preprint arXiv:1901.04978, 2018.

L. Liu, S. Liu, Z. Zhang, B. Yu, J. Tang, and Y. Xie, “Pirt: A runtime framework to enable energy-efficient real-time robotic applications on heterogeneous architectures,” arXiv preprint arXiv:1802.08359, 2018.

Z. Zhang, S. Liu, G. Tsai, H. Hu, C. - C. Chu, and F. Zheng, “Pirvs: An advanced visual-inertial slam system with flexible sensor fusion and hardware co-design,” in 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, pp. 1–7.

S. Wu, L. Li, S. Liu, and J. Peng, “System and method for providing content in autonomous vehicles based on real-time traffic information”. 2018.

L. Li, S. Liu, S. Wu, J. Peng, and J. Wang, “System and method for providing content in autonomous vehicles based on perception dynamically determined at real-time”. 2018.

L. Li, S. Liu, S. Wu, J. Peng, and J. Wang, “System and method for providing content in autonomous vehicles based on perception dynamically determined at real-time”. Google Patents, 2018.

Q. Wang, B. Ma, S. Liu, and J. Peng, “System and method for providing inter-vehicle communications amongst autonomous vehicles”. 2018.

Q. Wang, B. Ma, S. Liu, and J. Peng, “System and method for providing inter-vehicle communications amongst autonomous vehicles”. 2018.

J. Tang, et al., “Teaching autonomous driving using a modular and integrated approach,” in 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), 2018, vol. 1, pp. 361–366.

F. Zheng, G. Tsai, Z. Zhang, S. Liu, C. - C. Chu, and H. Hu, “Trifo-VIO: Robust and Efficient Stereo Visual Inertial Odometry using Points and Lines,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pp. 3686–3693.

J. Tang, B. Yu, S. Liu, Z. Zhang, W. Fang, and Y. Zhang, “$π$-SoC: Heterogeneous SoC Architecture for Visual Inertial SLAM Applications,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pp. 8302–8307.

J. Tang, S. Liu, C. Liu, C. Eisenbeis, and J. - L. Gaudiot, “Accelerating Lattice Chromodynamics (LQCD) Simulations with Value Prediction,” 2017.

J. Tang, S. Liu, C. Liu, C. Eisenbeis, and J. - L. Gaudiot, “Accelerating Lattice Quantum Chromodynamics Simulations with Value Prediction,” in 2017 IEEE 7th International Symposium on Cloud and Service Computing (SC2), 2017, pp. 209–216.