Cristino De Souza Junior Email & Phone Number

Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates

Leading a high-performing, multicultural team of 15 researchers and engineers specializing in Guidance, Navigation, and Control (GNC). I oversee two critical company-level projects: one focusing on multi-agent cooperative trajectory planning and tracking, and another on data-driven inertial navigation. Additionally, our group is responsible for developing core technical components for other major UAV projects, including GNSS-less navigation and terminal guidance systems. My role also encompasses strategic decision-making, stakeholder engagement, and managing collaborations with international partners to ensure project success and alignment with organizational goals.

Abu Dhabi, United Arab Emirates

Managed a team of three GNC engineers, overseeing both navigation and guidance tasks. Key responsibilities included implementing an Error-State Extended Kalman Filter (ES-EKF) for vision-based navigation and developing terminal guidance systems for UAVs. This work involved adapting conventional guidance laws, such as Proportional Navigation (PNG) and Augmented PNG (APNG), implementing them in ROS/C++, and deploying them for real-time operation on fixed-wing UAVs.

Abu Dhabi, Emirados Árabes Unidos

Responsible for designing the sensor fusion strategy for the GNSS-less navigation project, including prototyping in MATLAB and implementation in C++ using ROS. Tasks involved modeling the kinematics of UAVs and their sensors, as well as developing strategies to address non-Gaussian distributions. Additionally, I contributed to other GNC domains, including UAV swarm coordination and formation control.

Compiégne

My doctoral research focused on developing guidance laws to address the multi-agent pursuit of a single, faster evader. This work encompassed a broad range of approaches, including collective motion strategies (e.g., swarming and flocking), conventional guidance laws, and deep learning-based methods. Beyond theoretical analysis and simulations, I extended my research to practical applications by deploying the developed algorithms on both indoor and outdoor drones, demonstrating their real-world feasibility.

Clayton, Victoria, Australia

Investigating on cooperative interception of agile and dynamic targets, exploring the application of various Deep Reinforcement Learning (DRL) algorithms, including Twin Delayed Deep Deterministic Policy Gradient (TD3) and Deep Deterministic Policy Gradient (DDPG), to solve the multi-pursuer single-evader problem. Key findings from this research were published in IEEE RA-L and presented at ICRA (link for the paper).

Compiègne

França

Doctor Of Philosophy - Phd, Mechatronics, Robotics, And Automation Engineering

Education record

Bachelor'S Degree, Mechatronics, Robotics, And Automation Engineering

Activities and Societies: Coordination of students group in UAV (2 years) Embedded microcontrolled system for a UAV (12 scholarship).