Lei BAI is a second year PhD candidate at School of Computer Science and Engineering, the University of New South Wales, Australia. He is currently supervised by Dr Lina Yao and Prof. Salil Kanhere. Lei’s research interests lay in Deep Learning and Spatial-temporal Data Mining with focusing applications on Smart Cities, Human Pattern Recognition (e.g. EEG, Activity) and IoT Analytics.
Before joining UNSW, Lei received both his Master Degree (June 2017) and Bachelor Degree (July 2014) from Xidian University (China), supervised by Prof. Qingqi Pei.
1. L. Bai, L. Yao, S.S. Kanhere, X. Wang, M. Sheng. “STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting”, The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. (Accepted, CORE Rank A*);
2. L. Bai, L. Yao, S.S. Kanhere, Z. Yang, J. Chu & X. Wang. “Passenger Demand Forecasting with Multi-Task Convolutional Recurrent Neural Networks”, The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2019. (Accepted, CORE Rank A);
3. L. Bai, L. Yao, S.S. Kanhere, “AI Creates Better City Life: Human Mobility Prediction for Smart Transportation System”, UNSW Engineering Postgraduate Research Symposium, 2018, ISBN: 978-0-9953910-2-4.
4. L. Bai, L. Yao, S.S. Kanhere, X. Wang & Z. Yang “Automatic Device Classification from Network Traffic Streams of Internet of Things”, in Proceedings of 43nd IEEE conference on Local Networks (LCN), 2018. (Accepted, CORE Rank A);
5. Z. Li, Q. Pei, Y. Liu, L. Bai, “Spoofing Attacks against FM Indoor Localization”, in 2016 International Conference on Networking and Network Applications (NaNA). IEEE. (Accepted).