Ing. Matteo Bertolucci
Fähigkeiten und Kenntnisse
Werdegang
Berufserfahrung von Matteo Bertolucci
- Bis heute 2 Jahre und 8 Monate, seit Sep. 2022
President and Technical Lead
Moonet SAGL
MES (Syncade) | DCS (DeltaV) | Robotics and Software Design and Validation | Computer System Validation (GAMP5)| IT and Automation Quality Subject Matter Expert | CI/CD Software Expert | Industrial Automation for Highly Regulated Enviroments (Life Science) | PLC | SCADA | OsiPi | IT for Manufacturing applications | Artificial Intelligence | Computer Vision | Python | C/C++ | Cybersecurity | ROS | Matlab | Git | Kneat
- 2 Jahre und 10 Monate, Okt. 2019 - Juli 2022
Software Engineer II
Garmin
- Responsible for the SW integration, SW/HW maintenance and SW development of Garmin and Navionics products following Agile development (Docker, VMware, Azure DevOps, Jenkins), quality driven methodologies, requirements and market-driven deadlines. - Responsible for Data Integrity and Cyber Security projects. - Gained experience with QGIS, C++, Python, GIT, Gerrit, embedded systems, networking, server virtualization, machine learning, Agile software development cycle (CI/CD, Azure DevOps, Docker, VmWare).
- 1 Jahr und 7 Monate, Apr. 2018 - Okt. 2019
Autonomous Driving Engineer - Planning and Deep Learning
Ambarella - Vislab
Algorithm Engineer in the Autonomous Driving team of Ambarella designing path and motion planning algorithms for ADAS and autonomous cars.
- 1 Jahr und 7 Monate, Okt. 2016 - Apr. 2018
Computer Vision and Sensor Fusion Engineer
Ambarella - Vislab
Algorithm Engineer in the Computer Vision and ADAS team of Ambarella designing control systems and developing computer vision and sensor fusion algorithms (MATLAB, C, C++) for autonomous cars and drones.
- 7 Monate, Juni 2015 - Dez. 2015
Master's Thesis Student - Mapping and Perception
Daimler AG / Mercedes-Benz AG
Master's Thesis student working in the Sensor Fusion team on Mercedes-Benz autonomous cars of 2020. The thesis was focused on the use of Kalman filtering and multi-target tracking in order to improve the accuracy of perception systems (Lidar, Radar, Camera) at a limited cost for the embedded CPU on the car. This research work has been presented at IEEE MFI on September 2016.
Ausbildung von Matteo Bertolucci
- 3 Jahre und 5 Monate, März 2013 - Juli 2016
Robotics and Automation Engineering
University of Pisa
Robotics, Electrical systems, Digital control, Real Time Control, Control system engineering, Digital Signal Processing, Avionics, Smart systems, Guidance systems, Navigation systems, Automotive systems, UAV.
- 3 Jahre und 7 Monate, Sep. 2009 - März 2013
Electrical Power Engineering
University of Pisa
Electric power systems, Electric drives and electromechanical systems, Power electronics, Electric vehicles, Smart Grids, Renewable energy, Turbo machinery, Mechanics of materials.
Sprachen
Italienisch
Muttersprache
Englisch
Fließend
Französisch
Gut
Deutsch
Grundlagen
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