Publications

Journal publications

  1. Wang, Y., Li, L., & Dang, C. (2019). Calibrating Classification Probabilities with Shape-restricted Polynomial Regression. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-14. https://doi.org/10.1109/TPAMI.2019.2895794 [PDF]
  2. Murça, MCR., Hansman, R. J., Li, L. & Ren, P., (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. https://doi.org/10.1016/j.trc.2018.10.021 [PDF]
  3. Ren, P., & Li, L. (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. https://doi.org/10.1016/j.jairtraman.2017.12.005 [PDF]
  4. Wang, X., Li, L., & Xie, M. (2018). Optimal preventive maintenance strategy for leased equipment under successive usage-based contracts. International Journal of Production Research, 1–20. https://doi.org/10.1080/00207543.2018.1542181 [PDF]
  5. Wang, X., Xie, M., & Li, L. (2018). On optimal upgrade strategy for second-hand multi-component systems sold with warranty. International Journal of Production Research, 1–18. https://doi.org/10.1080/00207543.2018.1488087 [PDF]
  6. Pei, Y., Wang, W., & Li, L. (2016). Ranking the Vulnerable Components of Aircraft by Considering Performance Degradations. Journal of Aircraft, 53(5), 1400–1410. https://doi.org/10.2514/1.C033683 [PDF]
  7. Li, L., Hansman, R. J., Palacios, R., & Welsch, R. (2016). Anomaly detection via a Gaussian Mixture Model for flight operation and safety monitoring. Transportation Research Part C: Emerging Technologies, 64, 45–57. https://doi.org/10.1016/j.trc.2016.01.007 [PDF]
  8. Charruaud, F., & Li, L. (2015). Flight Operations Monitoring through Cluster Analysis: A Case Study. IEEE Intelligent Systems, 30(6), 24–29. https://doi.org/10.1109/MIS.2015.111 [PDF]
  9. Li, L., Das, S., John Hansman, R., Palacios, R., & Srivastava, A. N. (2015). Analysis of Flight Data Using Clustering Techniques for Detecting Abnormal Operations. Journal of Aerospace Information Systems, 12(9), 587–598. https://doi.org/10.2514/1.I010329 [PDF]

Peer-reviewed conference publications

  1. Zhao, W., Li, L., He, F., & Xiao, G. (2018). An Adaptive Online Learning Model for Flight Data Cluster Analysis. In the 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC), London, United Kingdom, 2018, pp. 1-7. https://doi.org/10.1109/DASC.2018.8569600  [PDF]
  2. He, F., Li, L., Zhao, W., & Xiao, G. (2018). Aircraft Weight Estimation Using Quick Access Recorder Data. In the 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC), London, United Kingdom, 2018, pp. 1-5. https://doi.org/10.1109/DASC.2018.8569866 [PDF]
  3. Hong, N., & Li, L. (2018). A Data-Driven Fuel Consumption Estimation Model for Airspace Redesign Analysis. In the 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC), London, United Kingdom, 2018, pp. 1-8. https://doi.org/10.1109/DASC.2018.8569564 [PDF] Best of Session (ATM-D: Analytics) Award
  4. Xu, P., Yao, W., Zhao, Y., Yi, C., Li, L., Lin, J., & Tsui, K. L. (2018). Condition monitoring of wheel wear for high-speed trains: A data-driven approach. In 2018 IEEE International Conference on Prognostics and Health Management (ICPHM) (pp. 1–8). Seattle, WA. https://doi.org/10.1109/ICPHM.2018.8448864
  5. Huang, J., Zhang, Q., Li, L., Yang, Y., Chiaradia, A., Pryor, M., & Webster C. (2016). Happiness and High-rise Living: Sentiment Analysis of Geo-Located Twitter Data in Hong Kong’s Housing Estates. In the 52nd ISOCARP Congress. (pp. 380 – 387). Durban. South Africa.
  6. Das, S., Li, L., Srivastava, A. N. A., John Hansman, R., & Hansman, R. J. (2012). Comparison of Algorithms for Anomaly Detection in Flight Recorder Data of Airline Operation. In the 12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Indianapolis, IN. https://doi.org/10.2514/6.2012-5593 [PDF]
  7. Li, L., Gariel, M., Hansman, R. J., & Palacios, R. (2011). Anomaly Detection in Onboard-Recorded Flight Data Using Cluster Analysis. In the 30th IEEE/AIAA Digital Avionics Systems Conference (DASC). Seattle, WA. https://doi.org/10.1109/DASC.2011.6096068 [PDF]
  8. Li, L., Cho, H., Hansman, R. J., & Palacios, R. (2010). Aircraft-based complexity assessment for radar controllers in the multi-sector planner experiment. In 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference (pp. 1–9). Fort Worth, TX. https://doi.org/978-1-60086-749-1 [PDF]
  9. Histon, J., Li, L., & Hansman, R. J. (2010). Airspace structure, future ATC systems, and controller complexity reduction. In the 29th AIAA/IEEE Digital Avionics Systems Conference (DASC). Seattle, WA. https://doi.org/10.1109/DASC.2010.5655354 [PDF]
  10. De Albuquerque Filho, E. A. F., Trabasso, L., Scarpel, Hansman, R. J., Li, L., (2010). Combining ATC Subjective Cognitive Complexity Evaluation Metrics in a Single Indicator. In the 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference (Vol. 1, AIAA-2010-9006). Fort Worth, TX. https://doi.org/10.2514/6.2010-9006 [Link]
  11. Donaldson, A. D., Dorbian, C. S., He, C., Li, L., Lovegren, J. A., Pyrgiotis, N., & Simaiakis, I. (2010). Parametric Design of Low Emission Hybrid-lift Cargo Aircraft. In the 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition (AIAA-2010-1395). Orlando, Florida. [PDF]