◎研究方向 智慧城市、智能交通系统、深度学习、大语言模型
◎教育经历 2017.09-2022.06 中国科公司自动化研究所 控制理论与控制工程 2013.09-2017.06 BB贝博艾弗森自动化
◎工作经历 2022.07-2024.09 商汤科技
◎学术兼职 IEEE TNNLS、IEEE TITS、IEEE ITSM、IEEE TCSS等期刊审稿人 中国自动化学会（综合智能交通专委会）会员
◎主讲课程 无
◎指导研究生及博士后 无
◎承担项目 山东省自然科学基金青年基金项目（C类） BB贝博艾弗森自主创新科研计划项目（理工科）
◎获奖情况 国家资助博士后研究人员计划（C档） 中国·山东博士（后）创新创业大赛铜奖
◎荣誉称号 无
◎著作 无
◎论文 [1] Li Z, Xiong G, Lv Y, et al. An Urban Trajectory Data-Driven Approach for COVID-19 Simulation[J]. IEEE Transactions on Computational Social Systems, 2024. [2] Li Z, Xiong G, Wei Z, et al. Trip purposes mining from mobile signaling data[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 23(8): 13190-13202. [3] Li Z, Xiong G, Wei Z, et al. A semisupervised end-to-end framework for transportation mode detection by using gps-enabled sensing devices[J]. IEEE Internet of Things Journal, 2021, 9(10): 7842-7852. [4] Li Z, Xiong G, Tian Y, et al. A multi-stream feature fusion approach for traffic prediction[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 23(2): 1456-1466. [5]. X. Yan, Li Z, et al. Traffic-aware cloud-edge collaborative offloading for vehicular tasks at complex intersections[J]. IEEE Transactions on Vehicular Technology, 2025. [6] Li B, Li Z, Chen J, et al. MAST-GNN: A multimodal adaptive spatio-temporal graph neural network for airspace complexity prediction[J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104521. [7] Zhishuai Li, Ziyue Li, Xiaoru Hu, et al. VisionTraj: A noise-robust trajectory recovery framework based on large-scale camera network[J]. IEEE Transactions on Intelligent Transportation Systems, 2025. [8] Xuezhe Yan, Zhishuai Li (通信作者), Zhichen Ni, et al. Traffic-aware cloud-edge collaborative offloading for vehicular tasks at complex intersections[J]. IEEE Transactions on Vehicular Technology, 2025. [9] Zhishuai Li, Gang Xiong, Yisheng Lv, et al. An urban trajectory data-driven approach for COVID-19 simulation[J]. IEEE Transactions on Computational Social Systems, 2024, 3(11): 4290-4299. [10] Zhishuai Li, Gang Xiong, Zebing Wei, et al. A semi-supervised end-to-end framework for transportation mode detection by using GPS-enabled sensing devices[J]. IEEE Internet of Things Journal, 2022, 9(10): 7842-7852. [11] Zhishuai Li, Gang Xiong, Zebing Wei, et al. Trip purposes mining from mobile signaling data[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(8): 13190-13202. [12] Zhishuai Li, Gang Xiong, Yonglin Tian, et al. A multi-stream feature fusion approach for traffic prediction[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(2): 1456-1466. [13] Zhishuai Li, Yunhao Nie, Ziyue Li, et al. Non-Neighbors also matter to Kriging: A new contrastive-prototypical learning[C]//International Conference on Artificial Intelligence and Statistics. PMLR, 2024: 46-54. [14] Zhishuai Li, Gang Xiong, Xipeng Zhang, et al. A GPU based parallel genetic algorithm for the orientation optimization problem in 3D printing[C]//2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019: 2786-2792. [15] Zhishuai Li, Gang Xiong, Yuanyuan Chen, et al. A hybrid deep learning approach with GCN and LSTM for traffic flow prediction[C]//IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2019: 1929-1933. [16] Zhishuai Li, Gang Xiong, Yu Zhang, et al. Urban trip generation forecasting based on gradient boosting algorithm[C]//2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI). IEEE, 2021: 50-53. [17] Biyue Li, Zhishuai Li, Jun Chen, et al. MAST-GNN: A multimodal adaptive spatio-temporal graph neural network for airspace complexity prediction[J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104521. [18] Gang Xiong, Zhishuai Li, Meihua Zhao, et al. TrajSGAN: A semantic-guiding adversarial network for urban trajectory generation[J]. IEEE Transactions on Computational Social Systems, 2023, 11(2): 1733-1743. [19] Xueliang Zhao, Zhishuai Li, Yu Zhang, Yisheng Lv. Discover trip purposes from cellular network data with topic modeling[J]. IEEE Intelligent Transportation Systems Magazine, 2020, 14(4): 37-46. [20] Zebing Wei, Zhishuai Li, Chunxiang Wang, et al. Recurrent attention unit: A simple and effective method for traffic prediction[C]//IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021: 1272-1277.
◎专利 [1] 熊刚, 李志帅, 吕宜生, 陈圆圆, 等. 基于混合深度学习的短时交通流量预测方法、系统、装置，专利号：ZL201910842242.8, 2020. [2]吕宜生, 魏泽兵, 李志帅, 刘皓, 等. 基于内嵌注意力机制的循环神经网络的交通流量预测方法，专利号：ZL202011119621.3, 2021. [3]沈震, 熊刚, 李志帅, 彭泓力, 等. 基于机器视觉的三维特征提取方法及装置，专利号：ZL201811474153.4, 2021.
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