• Manuel Soler has a PhD in Aerospace Engineering. He is currently Associate Professor at UC3M, Department of Bioengineering and Aerospace Engineering, where he leads the Air Navigation and Control research line and teaches undergraduate and graduate courses in air navigation, flight mechanics and control, air transport, and unmanned aerial vehicles. He has been a visiting scholar at ETH Zurich, Switzerland, and UC Berkeley, USA. His research interests focus on optimal control, stochastic hybrid systems, trajectory optimisation under meteorological uncertainty in ATM. He has participated in several research projects, e.g., POTRA (Clean-SKY), SESEAR WP-E HALA! PhD project [PI], TBO-Met [PI] (SESAR H2020 ER-1), STORMY [PI] (Engage’s PhD project, started in February 2019), and Spanish National Science Project OPTMET [PI] and MetATS (Started in Jan. 2019) ; and R&D contracts with Airbus R&D [PI] (started in Jan. 2019), Boeing [PI], CRIDA En-AIRE [PI], Innaxis [PI], and SENASA [PI]. Manuel Soler has a total of 48 scientific publications: 14 JCR publications (9 are in Q1 journals); 2 book chapters with Springer; 12 SCOPUS articles; 18 articles in international conference proceedings (e.g., SIDs, ICRAT, ATM Seminar, organized/co-organized by Eurocontrol), and 2 books. In Google Scholar, Dr. Soler has an index h = 11 and 407 cites. Dr. Soler has supervised 1 PhD thesis and is currently supervising 5 Phd Thesis (2 of them to be defended in Sept.-Oct 2019). Dr. Soler was recognized with the SESAR Young Scientist Award 2013 and the Luis Azcarraga Award in 2016 and 2019. Dr. Soler is leading the Challenge “Efficient provision and use of meteorological information in ATM” of the SESAR network Engage http://www.engagektn.com/. He is part of organizing panel of the “Meteorology and ATM· workshops series (started under OptMet and TBOMet umbrella) and has organized the “Workshop on Uncertainty and ATM. Detailed vitae information can be found @ http://www.aerospaceengineering.es.

 

  • Javier García-Heras: He is Assistant Professor at UC3M. He studied Aerospace Engineering at the Polytechnic University of Madrid, in 2014 he received a PhD in Aeronautical Engineering from the Polytechnic University of Madrid and began working for Lockheed Martin Commercial Flight Training (LMCFT) as a Software Engineer where he was designing, developing and integrating navigation, including autopilot and flight management system (FMS in its acronym in English). Most recently, he worked for CRIDA A.I.E. (Reference center for research, development and innovation in ATMs), as an ATM R & D Engineer, where he participated in tasks of validation and uncertainty of aircraft. His research has focused mainly on the paradigm of 4D trajectory management for future air traffic management. In addition to these, it also has a great interest in all activities related to ATM, navigation and avionics systems.

 

  • Daniel González Arribas: He began his degree in Industrial Electronics and Automation at UC3M in 2008, during his studies he was awarded two Scholarships of Excellence by the regional government of Madrid. He obtained his degree in 2012 having specialized in Theory of Control and Applications. From 2012 to 2014, he studied for a Master’s degree in Mathematical Engineering at UC3M and also collaborated in the Department of Bioengineering and Aerospace Engineering in research and teaching activities. He also participated in  a joint R & D project between UC3M and Boeing Research and Technology Europe. He has just finished his PhD in optimization of the  robust trajectory under uncertain winds in UC3M.

 

  • Aniel Jardines attended the Georgia Institute of Technology where he earned his B.S and M.S. in Aerospace Engineering. Following his Masters, Aniel spent five years working in the Federal Aviation Administration’s Office of Environment and Energy where he managed federally funded research and development projects related to aircraft technology and alternative jet fuels. Aniel is currently pursuing his PhD at Universidad Carlos III de Madrid, his research is focused on using machine learning algorithms to improve Air Traffic Management during convective weather events.

 

  • Eduardo Andres got a Bachelor and a Master in Aerospace Engineering at Universidad Polotécnica de Madrid, and then a Master on Aircraft dynamics and control at Cranfield University. He is currently pursing his Ph. D. on stochastic optimal control methods to aircraft trajectory planning. His Ph D. is supported by STORMY grant, funded byt ENGAGE KTN network.