Product manager for the development of high-performance drones. Coordination between technical teams and business needs. Customer project monitoring and continuous product improvement.

Tracking and Motion planning team Product Owner for autonomous industrial vehicles.10+ engineers team working to improve detection and navigation topicsBacklog management and priorization Create and share future vision with the team and stakeholdersResponsible for perception component, focus on bringing R&D features toward production vehicles

Product Owner for moving object information system and camera calibration (GSR 2024)Project Goal: Detect vulnerable road users to predict and alert collisions at low speeds maneuvering.Accomplishments:Refine User's stories (description, needs, acceptance criteria)Prioritize the backlog- Lead and manage workload- Define sprint goals and align the team to achieve these goals- Validate User Stories and MLC gates.- Organize and support product delivery on client side- Client communication and function delivery

Continental Engineering Services (CES) develops innovative and challenging solutions in Autonomous Driving Assistance (ADAS).CEM200 Project: Premium Traffic Participants FusionOur Mission:We update traffic participants fusion to be able to handle feature-level inputs from sensors. This should improve the quality in the context of L3 automated driving

From May 2021 to May 2022: Project Goal: Representation of the road environment based on camera and radar data fusion.Accomplishments:- Modeling of traffic lanes.- Computation of collision-free trajectories (road occupancy detection).- Development of parking assistance functionalities.- Development of unit tests.- Writing and analysis of requirements.From January 2021 to May 2021:Project goal: Define the state and orientation of the truck driver's cab.Achievements: - Evaluation and performance improvement of visual odometry algorithms. - Development of unit tests.From September 2019 to April 2020:Project Goal: Assisting in the maneuvering of vehicles equipped with trailers.Achievements: - Integration of trailer detection and tracking algorithms from camera data. - Evaluation and improvement of performances.- Responsible for a team of 6 people for code quality improvement (MISRA).

This end-of-study project was a continuation of the Global Drive project. The objective was to improve detection and classification and to develop tracking of road obstacles in an urban environment. For this, two multi-object tracking methods were implemented: - An extended Kalmaan filter was used for the radar data- A particle filter has been developed for camera data

The objective of the Global Drive project was to detect road obstacles in an urban environment. Based on radar/camera data fusion, two approaches were developed. The first method consisted in developing a neural network to detect and classify objects of interest. The second method used computer vision algorithms to segment the surrounding objects, and the YOLO neural network to classify the objects.

Research Project Objective: Incremental reconstruction of an object for remote 3D visualization.Achievements: - Realization of a state of the art.- Implementation and calibration of the scanner and its capture surface with augmented reality applications.- Development of filters and acquisition of 3D points.- Reconstruction and meshing of the figure from open source libraries.

Project objective: Development of an HMI and remote control of a drone for inspection and control missions.Achievements:- Realization of an HMI for the creation and the follow-up of the mission.- Creation and transfer of waypoint missions.- Guidance and navigation of the drone point by point.- Recovery of video streams for analysis.- Saving mission data.- Development of security features.

Objectif: Implémentation logicielle d’une nouvelle méthode de mesures dans le domaine de l’automobile.