Prénom
Josué
Nom
Rivera
Fonction
Chargé de recherche
Profil
Chercheur
Direction
Implantation
Site de Toulouse (siège de la Direction Occitanie) 
Service
DT/STI
E-mail
josue.rivera@erema.fr
Domaine de recherche

Josué Manuel Rivera Velázquez received the B.Eng. degree in Communications and Electronics Engineering from the National Polytechnic Institute of Mexico (IPN) in 2011, the M.Sc. degree in Computer Science from the National Autonomous University of Mexico (UNAM) in 2013, and the Ph.D. degree in Automatic and Microelectronic Systems from the University of Montpellier (LIRMM) in France in 2020.

After obtaining his Ph.D., he completed two postdoctoral studies at the Centre d'Études et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (CEREMA) in the STI (Systèmes de Transports Intelligents) research team in Toulouse. The first postdoc was on multisensor data fusion, the design of functional specifications and requirements, and the in-situ validation of multisensor perception architectures for heavy vehicle automation. The second postdoc was on the study of the behaviour of different road users (pedestrians, cyclists and light vehicles) in the presence of automated vehicles. The aim of this work was to understand the new hazardous situations created by automation.

Since 2021, he has been working as a researcher for the STI research team at Cerema in Toulouse. His topics of interest are the use of digital infrastructure for the protection of vulnerable road users (VRU), the analysis of interactions between VRU and other road users (light vehicles, heavy vehicles), the impact of the presence of automated vehicles on the behaviour of other road users, as well as new accident and near-accident situations caused by the automation of vehicles. On technical issues, his research interests include the design, implementation and testing of data fusion algorithms in embedded multi-sensor systems, embedded systems in automated vehicles and intelligent transport systems, image processing, and object recognition and tracking using deep learning methods.