mahm.al.masri
About Candidate
Skilled robotics researcher with a demonstrated track record in robotics, sensor fusion, computer vision, applied mathematics, and artificial intelligence. Eager to transition into an academic role as an assistant professor. Dedicated to maintaining a leading-edge in both theoretical and applied research, while delivering top-tier courses that incorporate the latest advancements to engineering students. My extensive background in applied research within startup environments has refined my ability to translate world-class research into practical innovations. I possess robust connections within the French robotics industry and academia, facilitating collaborative research opportunities and enhancing student learning experiences. I actively contribute to the academic community as a peer reviewer for prestigious journals and conferences, ensuring the rigor and relevance of research contributions.
Location
Education
Title: Diagnosis of robotic platforms. Evolutionary hybrid method integrating interaction with an expert operator. Domains: robotics, control, fault diagnosis, signal processing, sensor fusion, applied maths, and AI. Professional Development Courses: team management, public speaking, University-Level Teaching, and consulting strategies.
Domains: robotics, autonomous systems, and sensor fusion.
Domain: fault diagnosis, signal processing, AI, and electronics.
This is a 6-month specialization that covers key topics in modern robotics: modeling, planning, mobile robotics, grasping, kinematics, dynamics, and control.
Work & Experience
- Conducted applied research in autonomous navigation, computer vision, sensor fusion, algorithms, and applied mathematics for a painter robot - Implemented the code using C++, Qt and OSG. Done Prototypes with Matlab and Python3. - Collaborated with multi-disciplinary teams to design experiments, collect data, and interpret results - Projects include: code architecture refactoring and design, control laws for narrow passages crossing, control laws for smooth movement of the mobile manipulator during painting, obstacle awareness with noisy data, and sensor data filtering.
Note: this is a collaboration between Les Companions and IMT Nord Europe university. In addition to my mission at Les Companions: - Researched state-of-the-art technologies that could benefit the highly autonomous painter robot - Optimized hardware setup to prevent collision with unmodeled elements of the robot, enhancing functionality - Analyzed dynamics and kinematics of mobile manipulator robot to ensure smooth movement
- Managed a small team of robotics engineers to develop an autonomous intelligent robot charger for electric vehicles, completing projects within specified deadlines - Incorporated sensors and perception technologies including RBG- D, IMU, and 2D/3D Lidars. - Combined sensor information using sensor fusion techniques (UKF, Particle Filters) to achieve precise localization and 3D object tracking. - Successfully trained Artificial Intelligence models to achieve high precision in computer vision tasks such as detecting, segmenting, and estimating real-time 3D poses of targets - Designed control law for autonomous high-precision docking with a heavy robot (500 kg) and 3cm precision on the final position.
I achieved my PhD in Collaboration with INRAE. Achievements: - Developed novel fault detection algorithms using Applied Mathematics, Data Statistics, and Artificial Intelligence. - Established a strong reputation in the field by contributing to prestigious publications including Neurocomputing journals, conferences, and book chapters - Supervised interns and conducted research in robotics and human-robot interaction field
I performed a teaching mission at Polytech and ISIMA engineering schools. - Designed engaging laboratory content for programming, C++, POO, data structures, Linux, automatics, and robotics - Created course structures, facilitated learning, and evaluated students' progress through examinations - Contributed to the development of new algorithmic courses and exams through collaboration with faculty colleagues
Developed strategies to enhance system cybersecurity by implementing fault diagnosis methods for controller protection