{"id":5286,"date":"2025-09-25T09:02:31","date_gmt":"2025-09-25T08:02:31","guid":{"rendered":"https:\/\/mecatron.rma.ac.be\/?page_id=5286"},"modified":"2025-09-25T09:02:31","modified_gmt":"2025-09-25T08:02:31","slug":"joao-pedro-dias-rodrigues","status":"publish","type":"page","link":"https:\/\/mecatron.rma.ac.be\/index.php\/people\/joao-pedro-dias-rodrigues\/","title":{"rendered":"Joao Pedro Dias Rodrigues"},"content":{"rendered":"

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AI Specialist<\/span><\/h4>\n

Robotics & Autonomous Systems,
Royal Military Academy<\/p>\n

Address<\/h4>\n

Avenue De La Renaissance 30, 1000 Brussels, Belgium<\/p>\n

Contact Information<\/h4>\n

Call<\/strong>: –<\/p>\n

Email<\/strong>: JoaoPedro.DiasRodrigues@mil.be<\/a><\/p>\n

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Pedro Rodrigues is a researcher in the Robotics & Autonomous Systems (RAS<\/span>) unit of the Department of Mechanics at the Royal Military Academy (RMA), contributing to European Commission, European Defence Agency, and Belgian Defence projects in ground, air, and maritime robotics.\u00a0<\/span><\/div>\n
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His work will focus on applying machine learning methodologies to unmanned systems research across multiple projects within\u00a0RAS<\/span>\u00a0with the goal of strengthening the autonomy and operational readiness of these systems. He is integrated in the project SAFIR-READY, where he applies his skills to identify and classify unmanned aerial traffic, and in the E=MCM, where he will assist in improving autonomous unmanned systems detection of drifting mine.\u00a0<\/div>\n
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Pedro earned a master\u2019s degree in Physical Engineering from the University of Aveiro, with his first contact with AI being his thesis exploring beyond-the-Standard-Model particle-physics frameworks. Before joining RMA, he was an AI researcher at the German Cancer Research Centre, developing generative models, segmentation pipelines and interactive visualisation tools for medical imaging.<\/div>\n<\/div>\n

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