, Manual on Implementation of a 300 m (1000 ft) Vertical Separation Minimum Between FL 290 and FL 410 Inclusive, vol.9574, 2001.

M. Prandini, J. Hu, J. Lygeros, and S. Sastry, A probabilistic approach to aircraft conflict detection, IEEE Transactions on Intelligent Transportation Systems, vol.1, issue.4, pp.199-220, 2000.

D. G. Denery and H. Erzberger, The Center-Tracon Automation System: Simulation and Field Testing, 1997.

D. J. Brudnicki, K. S. Lindsay, and A. L. Mcfarland, Assessment of field trials, algorithmic performance, and benefits of the user request evaluation tool (uret) conflict probe, IEEE Digital Avionics Systems Conference, 1997.

P. Brooker, Stca, tcas, airproxes and collision risk, The Journal of Navigation, vol.58, issue.3, pp.389-404, 2005.

M. D. Ciletti and A. W. Merz, Collision avoidance maneuvers for ships, Navigation, vol.23, issue.2, pp.128-135, 1976.

E. M. Goodwin, A statistical study of ship domains, Journal of Navigation, vol.28, issue.3, pp.328-344, 1975.

P. Bauer, A. Hiba, J. Bokor, and A. Zarandy, Three dimensional intruder closest point of approach estimation based-on monocular image parameters in aircraft sense and avoid, Journal of Intelligent & Robotic Systems, pp.1-16, 2018.

J. Kucher and L. Yang, Survey of conflict detection and resolution modeling methods, AIAA Guidance, Navigation, and Control Conference, pp.1388-1397, 1997.

C. Munoz, A. Narkawicz, and J. Chamberlain, A tcas-ii resolution advisory detection algorithm, Aiaa Guidance, Navigation, & Control, 2013.

L. C. Yang and J. K. Kuchar, Prototype conflict alerting system for free flight, Journal of Guidance, Control, and Dynamics, vol.20, issue.4, pp.768-773, 1997.

Y. Huo, D. Delahaye, and Y. Wang, Sensitivity analysis of closest point of approach, ICRAT 2018, 8th International Conference for Research in Air Transportation, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01823194

S. Alam, H. Abbass, C. Lokan, M. Ellejmi, and S. Kirby, Computational red teaming to investigate failure patterns in medium term conflict detection, 8th Eurocontrol Innovation Research Workshop, 2009.

Q. Yang, A. Lim, K. Casey, and R. Neelisetti, An enhanced cpa algorithm for real-time target tracking in wireless sensor networks, International Journal of Distributed Sensor Networks, vol.5, issue.5, pp.619-643, 2009.

C. A. Munoz and A. J. Narkawicz, Time of closest approach in three-dimensional airspace, 2010.

G. Dowek and C. Munoz, Conflict detection and resolution for 1, 2,... n aircraft, 7th AIAA ATIO Conf, 2nd CEIAT Int'l Conf on Innov and Integr in Aero Sciences, 17th LTA Systems Tech Conf; followed by 2nd TEOS Forum, p.7737, 2007.

Z. Wang, M. Liang, and D. Delahaye, A hybrid machine learning model for short-term estimated time of arrival prediction in terminal manoeuvring area, Transportation Research Part C: Emerging Technologies, vol.95, pp.280-294, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01856677

Z. Wang, M. Liang, D. Delahaye, and W. Wu, Learning Real Trajectory Data to Enhance Conflict Detection Accuracy in Closest Point of Approach, ATM Seminar, p.13, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02138131

A. Usa/europe and . Seminar, , 2019.

S. Arumugam and C. Jermaine, Closest-point-of-approach join for moving object histories, Data Engineering, 2006. ICDE'06. Proceedings of the 22nd International Conference on. Citeseer, pp.86-86, 2006.

T. Fawcett, An introduction to roc analysis, Pattern recognition letters, vol.27, pp.861-874, 2006.

B. C. Csáji, Approximation with artificial neural networks, vol.24, p.48, 2001.

C. M. Bishop, Pattern recognition and machine learning (information science and statistics), p.49901, 2006.

N. S. Altman, An introduction to kernel and nearest-neighbor nonparametric regression, The American Statistician, vol.46, issue.3, pp.175-185, 1992.

J. H. Friedman, Greedy function approximation: a gradient boosting machine, pp.1189-1232, 2001.

K. Rashmi and R. Gilad-bachrach, Dart: Dropouts meet multiple additive regression trees, International Conference on Artificial Intelligence and Statistics, pp.489-497, 2015.

G. Ke, Q. Meng, T. Finley, T. Wang, W. Chen et al., Lightgbm: A highly efficient gradient boosting decision tree, Advances in Neural Information Processing Systems, pp.3146-3154, 2017.

L. Breiman, Random forests, Machine learning, vol.45, issue.1, pp.5-32, 2001.

J. Friedman, T. Hastie, and R. Tibshirani, The elements of statistical learning, Springer series in statistics, vol.1, 2001.

, CAUC) in 2016, the M.Sc. degree in Operational Research fromÉcole Nationale de l'Aviation Civile (ENAC) in 2018, the M.Eng. in Aviation Engineering and

, and did a post-doc at ENAC. During 2006-2014, she worked at the department of Air Traffic Management at CAUC as a lecturer and researcher, D in Applied Mathematics from EDAA, 2018.