Learning an Efficient and Safe Policy for Highway Driving using Supervised Learning and Reinforcement Learning. - Jingke Wang; Tong Yang 006; Li Tang 006; Yue Wang 020; Rong Xiong (RCAR, 2019)

Learning hierarchical behavior and motion planning for autonomous driving. - Jingke Wang; Yue Wang 020; Dongkun Zhang; Yezhou Yang; Rong Xiong (IROS, 2020)

Imitation Learning of Hierarchical Driving Model: from Continuous Intention to Continuous Trajectory. - Yunkai Wang; Dongkun Zhang; Jingke Wang; Zexi Chen; Yue Wang 020; Rong Xiong (CoRR, 2020)

KB-Tree: Learnable and Continuous Monte-Carlo Tree Search for Autonomous Driving Planning. - Lanxin Lei; Ruiming Luo; Renjie Zheng; Jingke Wang; Jianwei Zhang; Cong Qiu; Liulong Ma; Liyang Jin; Ping Zhang; Junbo Chen (IROS, 2021)

Imitation Learning of Hierarchical Driving Model: From Continuous Intention to Continuous Trajectory. - Yunkai Wang; Dongkun Zhang; Jingke Wang; Zexi Chen; Yuehua Li; Yue Wang 020; Rong Xiong (IEEE Robotics Autom. Lett., 2021)

LTP: Lane-based Trajectory Prediction for Autonomous Driving. - Jingke Wang; Tengju Ye; Ziqing Gu; Junbo Chen (CVPR, 2022)

FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving. - Tengju Ye; Wei Jing; Chunyong Hu; Shikun Huang; Lingping Gao; Fangzhen Li; Jingke Wang; Ke Guo; Wencong Xiao; Weibo Mao; Hang Zheng; Kun Li; et al. (CoRR, 2023)

Edge-Optimized AI Architecture: MRAM-based Near Memory Computing Core Balancing between Memory Capacity and Computation. - Xi Yang; Liang Chang 002; Yuanbo Wang; Jingke Wang; Chao Fan; Zhongmou Wu; Jun Zhou 017 (ICTA, 2024)

PIPECIM: Energy-Efficient Pipelined Computing-in-Memory Computation Engine With Sparsity-Aware Technique. - Yuanbo Wang; Liang Chang 002; Jingke Wang; Pan Zhao; Jiahao Zeng; Xin Zhao; Wuyang Hao; Liang Zhou; Haining Tan; Yinhe Han 001; Jun Zhou 017 (IEEE Trans. Very Large Scale Integr. Syst., 2025)