Dr. Lishuai Li focuses on interdisciplinary research of intelligent transportation systems and data science. She has developed analytical methods using large-scale operational data for airline safety management and operations improvement, air traffic management, and health monitoring of train systems. She has recently developed path-finding methods for drone delivery networks to overcome infrastructural challenges in urban air mobility.
Dr. Li received a Ph.D. and an M.Sc. in Air Transportation Systems from the Department of Aeronautics and Astronautics at Massachusetts Institute of Technology (MIT). She obtained a B.Eng. in Aircraft Design and Engineering from Fudan University.
Journal
- Lin, Yu. , Li, Lishuai*. , Ren, Pan. , Wang, Yanjun. & Szeto, W. Y. (in press). From Aircraft Tracking Data to Network Delay Model: A Data-Driven Approach Considering En-Route Congestion. Transportation Research Part C: Emerging Technologies.
- Zhu, Xitning. & Li, Lishuai*. (2021). Flight Time Prediction for Fuel Loading Decisions with a Deep Learning Approach. Transportation Research Part C: Emerging Technologies. 128. doi:https://doi.org/10.1016/j.trc.2021.103179
- Hong, Ning. , Li, Lishuai*. , Yao, Weiran. , Zhao, Yang. , Yi, Cai. , Lin, Jianhui. & Tsui, Kwok Leung. (2019). High-Speed Rail Suspension System Health Monitoring Using Multi-Location Vibration Data. IEEE Transactions on Intelligent Transportation Systems. 21/7. 2943 - 2955. doi:10.1109/TITS.2019.2921785
- Ren, Pan. & Li, Lishuai*. (2018). Characterizing air traffic networks via large-scale aircraft tracking data: A comparison between China and the US networks. Journal of Air Transport Management. 67. 181 - 196. doi:10.1016/j.jairtraman.2017.12.005
- Li, Lishuai*. , Hansman, John. R. , Palacios, Rafael. & Welsch, Roy. (2016). Anomaly Detection via a Gaussian Mixture Model for Flight Operation and Safety Monitoring. Transportation Research Part C: Emerging Technologies. 64. 45 - 57. doi:10.1016/j.trc.2016.01.007
- Li, Lishuai*. , Das, Santanu. , Hansman, R. John. , Palacios, Rafael. & Srivastava, Ashok. N. (2015). Analysis of Flight Data Using Clustering Techniques for Detecting Abnormal Operations. Journal of Aerospace Information Systems. Vol. 12, No. 9. 587 - 598. doi:10.2514/1.I010329
Conference Paper
- Hong, Ning. & Li, Lishuai. (Sep 2018). A Data-Driven Fuel Consumption Estimation Model for Airspace Redesign Analysis. 37th IEEE/AIAA Digital Avionics Systems Conference (DASC). Best Paper Award of Session: ATM Analytics. London. UK: AIAA/IEEE. doi:10.1109/DASC.2018.8569564
- Li, Lishuai. , Gariel, Maxime. , Hansman, R. John. & Palacios, Rafael. (Oct 2011). Anomaly Detection in Onboard-Recorded Flight Data Using Cluster Analysis. Digital Avionics Systems Conference (DASC), 2011 IEEE/AIAA 30th. Seattle, WA. USA: IEEE/AIAA.
External Services
Public Service
- 2021 - Now, Editorial Advisory Board Member, Transportation Research Part C: Emerging Technologies.
Last update date :
28 Jul 2021
