Fuda van Diggelen

Fuda van Diggelen is a Postdoctoral Researcher at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI) and the Institute of Microengineering (IGM). Their primary research focuses on the intersection of robotics and artificial intelligence, particularly in robot learning and emergent behaviors in swarms. They are part of the Laboratory of Intelligent Systems (LIS), where they investigate adaptive neural networks for distributed learning in robot swarms.

Van Diggelen holds a PhD in Evolutionary Robotics from Vrije Universiteit Amsterdam (2024), supervised by Guszti Eiben and Eliseo Ferrante. Their doctoral work explored robot learning algorithms in evolving populations. They also earned two Master’s degrees: Human Movement Science (cum laude) from VU Amsterdam and Mechanical Engineering (Bio-Robotics) from TU Delft.

Research interests include embodied intelligence, complex systems, control theory, and applications in healthcare such as ICU data analysis during the COVID-19 pandemic. Notable achievements include a nomination for the Best Master’s Thesis Award at VU Amsterdam and 3rd place in the IEEE RAS Multi Robot Systems (MRS) competition.

They have contributed to projects like the Revolve software framework for robot evolution and the Dutch ICU Data Warehouse collaboration. Their work bridges robotics, AI, and healthcare, with a focus on developing adaptive systems for real-world challenges.