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Dr. LI Lishuai (李立帥博士)

PhD(MIT), MSc(MIT), BEng(Fudan University)

Assistant Professor

Contact Information

Office: Y6616 AC1
Phone: 34424726
Email: lishuai.li@cityu.edu.hk
Web: https://lishuaili.com/

Research Interests

  • Air transportation systems: airline safety, air traffic network, air traffic management
  • Data analytics, machine learning and data visualization
Lishuai Li is an Assistant Professor in the Department of Systems Engineering and Engineering Management at City University of Hong Kong (CityU). Her research interest is the development of analytical methods for the design, management, and operations of transportation systems, focusing on air transport. Her current projects include air traffic network analysis, flight delay modeling, air traffic management, flight operations monitoring, airline safety management, health monitoring of high-speed train components, and the impact of urban transport systems on public sentiment, etc. Her work has an emphasis on the use of large-scale data generated from the actual operations of transport systems, applying methods and technologies of artificial intelligence, data mining, and text mining.

She received a Ph.D. and a M.Sc. in Air Transportation Systems from the Department of Aeronautics and Astronautics at Massachusetts Institute of Technology (MIT). She received a B.Eng. in Aircraft Design and Engineering from Fudan University. She was a consultant at McKinsey & Company with the Operations Practice in San Francisco, and she is a pilot.


Publication Show All Publications Show Prominent Publications


Journal

  • Wang, Yongqiao. , Li, Lishuai. & Dang, Chuangyin. (Jan 2019). Calibrating Classification Probabilities with Shape-restricted Polynomial Regression. IEEE Transactions on Pattern Analysis and Machine Intelligence. doi:10.1109/TPAMI.2019.2895794
  • Condé Rocha Murça, Mayara. , Hansman, R John. , Li, Lishuai. & Pan, Ren. (Dec 2018). Flight trajectory data analytics for characterization of air traffic flows: A comparative analysis of terminal area operations between New York, Hong Kong and Sao Paulo. Transportation Research Part C: Emerging Technologies. 97. 324 - 347. doi:10.1016/j.trc.2018.10.021
  • Wang, Xiaolin. , Li, Lishuai. & Xie, Min. (Nov 2018). Optimal preventive maintenance strategy for leased equipment under successive usage-based contracts. International Journal of Production Research. doi:10.1080/00207543.2018.1542181
  • Wang, Xiaolin. , Min, Xie. & Li, Lishuai. (Jul 2018). On optimal upgrade strategy for second-hand multi-component systems sold with warranty. International Journal of Production Research. doi:10.1080/00207543.2018.1488087
  • Ren, Pan. & Li, Lishuai. (Mar 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. (Mar 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
  • Pei, Yang. , Wang, Wei. & Li, Lishuai. (Mar 2016). Ranking the Vulnerable Components of Aircraft by Considering Performance Degradations. Journal of Aircraft. doi:10.2514/1.C033683
  • Li, Lishuai. , Das, Santanu. , Hansman, R. John. , Palacios, Rafael. & Srivastava, Ashok. N. (Sep 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
  • Charruaud, Florent. & Li, Lishuai. (2015). Flight Operations Monitoring through Cluster Analysis: A Case Study. Intelligent Systems, IEEE. Vol. 30, No. 6. 24 - 29. doi:10.1109/MIS.2015.111

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). London. UK: AIAA/IEEE. doi:10.1109/DASC.2018.8569564
  • He, Fang. , Li, Lishuai. , Zhao, Weizun. & Xiao, Gang. (Sep 2018). Aircraft Weight Estimation Using Quick Access Recorder Data. 37th IEEE/AIAA Digital Avionics Systems Conference (DASC). London. UK: AIAA/IEEE. doi:10.1109/DASC.2018.8569866
  • Zhao, Weizun. , Li, Lishuai. , He, Fang. & Gang, Xiao. (Sep 2018). An Adaptive Online Learning Model for Flight Data Cluster Analysis. 37th IEEE/AIAA Digital Avionics Systems Conference (DASC). London. UK: AIAA/IEEE. doi:10.1109/DASC.2018.8569600
  • Xu, Peiwen. , Yao, Weiran. , Zhao, Yang. , Yi, Cai. , Li, Lishuai. , Lin, Jianhui. & Tsui, Kwok Leung. (Jun 2018). Condition monitoring of wheel wear for high speed trains: A data-driven approach. 2018 IEEE International Conference on Prognostics and Health Management (ICPHM). Seattle, WA. USA: IEEE. doi:10.1109/ICPHM.2018.8448864
  • Huang, Jianxiang. , Zhang, Qingpeng. , Li, Lishuai. , Yang, Yiyang. , CHIARADIA, Alain. , Pryor, Matthew. & Webster, Chris. (Sep 2016). Happiness and High-rise Living: Sentiment Analysis of Geo-Located Twitter Data in Hong Kong’s Housing Estates. 52nd ISOCARP Congress. (pp. 380 - 387). Durban. South Africa: .
  • Das, Santanu. , Li, Lishuai. , Srivastava, Ashok. N. & Hansman, R. John. (Sep 2012). Comparison of Algorithms for Anomaly Detection in Flight Recorder Data of Airline Operations. 12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference. Indianapolis, Indiana. USA: AIAA.
  • 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.
  • Histon, Jonathan. , Li, Lishuai. & Hansman, R. John. (Oct 2010). Airspace structure, future ATC systems, and controller complexity reduction. Digital Avionics Systems Conference (DASC), 2010 IEEE/AIAA 29th. Dulles, Virginia. USA: IEEE/AIAA.
  • Li, Lishuai. , Cho, HongSeok. , Hansman, R. John. & Palacios, Rafael. (Sep 2010). Aircraft-Based Complexity Assessment for Radar Controllers in the Multi-Sector Planner Experiment. 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference. Fot Worth, Texas. USA: AIAA.


Personal Website



Grants

  • PI: “A Data-Driven Framework for Airspace Congestion Analysis Using Aircraft Tracking Data”, General Research Fund, Hong Kong Research Grant Council, 2017
  • PI: “Cluster-Based Flight Data Analysis and Visualization Software”, Innovation and Technology Fund, Hong Kong Innovation and Technology Commission, 2016
  • PI: “Proactive Flight Operations Monitoring and Safety Management: a System Informatics Approach”, Early Career Scheme, Hong Kong Research Grant Council, 2016
  • PI: “Aviation Safety Management and Risk Identification Based on Operational Big Data”, Young Scientists Fund, National Natural Science Foundation of China, 2016


Last update date : 27 Feb 2019