上海市白玉兰人才计划（海外）获得者。曾任香港科技大学副研究员。
研究方向主要集中在智能交通领域，具体方向为多模式城市交通系统理解、推断、预测和管理。在交通工程和计算机领域知名学术SCI期刊和计算机领域顶级CCF推荐会议发表多篇论文。
教育经历
澳大利亚悉尼新南威尔士大学，计算机科学与工程学院，博士，2022.11
新泽西州罗格斯大学，电子与计算机工程学院，工学硕士，2018.5
电子科技大学，通信工程，工学学士，2017.6
工作经历
2023.1 – 2024.1香港科技大学土木与环境工程学院副研究员
发表刊物
Can Li, Wei Liu, “Multimodal Transport Demand Forecasting via Federated Learning”, IEEE Transactions on Intelligent Transportation Systems, 2023.
Can Li, Lei Bai, Wei Liu, Lina Yao, S Travis Waller, “A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applications”, Transportmetrica B: Transport Dynamics, 11(1), 2179461, 2023.
Can Li, Lei Bai, Wei Liu, Lina Yao, S Travis Waller, “A multi-task memory network with knowledge adaptation for multimodal demand forecasting”, Transportation Research Part C: Emerging Technologies, 131, 103352, 2021.
Can Li, Lei Bai, Wei Liu, Lina Yao, Travis Waller, "Urban Mobility Analytics: A Deep Temporal-Spatial Product Neural Network for Demographics Prediction", Transportation Research Part C: Emerging Technologies, 124, 102921, 2021.
Can Li, Lei Bai, Wei Liu, Lina Yao, Travis Waller, "Graph Neural Network for Robust Public Transit Demand Prediction", IEEE Transactions on Intelligent Transportation Systems, 23(5), 4086-4098 , 2020.
Can Li, Lei Bai, Wei Liu, Lina Yao, Travis Waller, “Knowledge Adaptation for Demand Prediction based on Multi-task Memory Neural Network”, 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020.
Can Li, Lei Bai, Wei Liu, Lina Yao, Travis Waller, "Passenger Demographic Attributes Prediction for Human-centered Public Transport", 26th International Conference on Neural Information Processing of the Asia-Pacific Neural Network (ICONIP), 2019.