CV

You can download [PDF] (1-6-2023)

Education

• 2020 - now   Ph.D. Evolutionary Robotics Vrije Universiteit Amsterdam
• 2018 - 2020: M.Sc. Mechanical Engineering Technische Universiteit Delft
                       Thesis: Adaptive Control for Evolutionary Robotics.
• 2017 - 2020: M.Sc. Human Movement Science Vrije Universiteit Amsterdam
                       Thesis: The Role of Proprioceptive Feedback in Learning Locomotion.
• 2014 - 2017: B.Sc. Human Movement Science Vrije Universiteit Amsterdam
                       Thesis: Do humans continuously minimize metabolic energy expenditure per meter during walking?

Work experience

• Spring 2022: Visiting Researcher Technology Innovation Institute (TII)
                       Collaboration on machine learning in racing drones (for ICRA) and swarm experiments.

• 2019 - 2020: Research Internship Vrije Universiteit Amsterdam, Computer Science
                       Conducting evolutionary robotics research for my master thesis.

• 2019 - 2020: Master Programme Committee Vrije Universiteit Amsterdam, Human Movement Science
                       Representing students’ interest and advising programme board to improve education.

• Spring 2018: Teacher Assistant Vrije Universiteit Amsterdam, Human Movement Science
                       Teaching during practicals in the course Physics and Measurements.

• 2014 - 2019: Tutoring Bijlesnetwerk/Lyceo
                       Tutoring high school students in mathematics, physics, chemistry and biology.

Publications

• F. van Diggelen, N.P.A Cambier, E. Ferrante, A.E. Eiben (2024) "A model-free method to learn multiple skills in parallel on modular robots." Nature Communications 15(2), 6267. doi: 10.1038/s41467-024-50131-4.Website.
• F. van Diggelen, M. De Carlo, N.P.A Cambier, E. Ferrante, A.E. Eiben (2024) "Emergence of Specialised Collective Behaviors in Evolving Heterogeneous Swarms." Parallel Problem Solving from Nature (PPSN XVIII) LNCS 15149, pp 53-69. Paper.
• F. van Diggelen, E. Ferrante, A.E. Eiben (2023). "Comparing robot controller optimization methods on evolvable morphologies." Evolutionary Computation, pp. 1-19, doi: 10.1162/evco_a_00334.
• T.A. Dam, L.F. Roggeveen, F. van Diggelen, et al. (2022). "Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning." Annals of Intensive Care 12(1), pp 1-9, doi: 10.1186/s13613-022-01070-0.
• F. van Diggelen, T. Karagüzel, J. Lo, E. Ferrante, N. Cambier, A.E. Eiben (2022). "Environment induced emergence of collective behaviour in evolving swarms with limited sensing." In Proceedings of the Genetic and Evolutionary Computation Conference . pp. 31-39, doi: 10.1145/3512290.3528735.
• F. van Diggelen, E. Ferrante, N. Harrak, J. Luo, D. Zeeuwe and A. E. Eiben (2021). "The Influence of Robot Traits and Evolutionary Dynamics on the Reality Gap." IEEE Transactions on Cognitive and Developmental Systems, doi: 10.1109/TCDS.2021.3112236.
• G. Lan, M. De Carlo, F. van Diggelen, J. M. Tomczak, D. M. Roijers, and A.E. Eiben (2021). "Learning directed locomotion in modular robots with evolvable morphologies." Applied Soft Computing 111, pp. 107688, doi: 10.1016/j.asoc.2021.107688.
• F. van Diggelen, E. Ferrante, A.E. Eiben (2021). "Comparing lifetime learning methods for morphologically evolving robots." In Proceedings of the Genetic and Evolutionary Computation Conference Companion. pp. 93-94, doi: 10.1145/3449726.3459530.
• L.M. Fleuren, D.P. de Bruin, M. Tonutti, et al. (2021). "Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse." Intensive Care Medicine Experimental 9(1), pp 32, doi: 10.1186/s40635-021-00397-5.
• L.M. Fleuren, D.P. de Bruin, M. Tonutti, et al. (2021). "Large-scale ICU data sharing for global collaboration: the first 1633 critically ill COVID-19 patients in the Dutch Data Warehouse." Intensive Care Med 47, 478-481, doi: 10.1145/3512290.3528735.
• F. van Diggelen, R. Babuska, and A. E. Eiben (2020). "The Effects of Adaptive Control on Learning Directed Locomotion." IEEE Symposium Series on Computational Intelligence (SSCI), doi: 10.1109/SSCI47803.2020.9308557.

Scientific Outreach

• Rijksmuseum Boerhaave: brAInpower Science Museum
• De kennis van nu special: de robot evolutie Dutch national television
• Joint Lectures on Evolutionary Algorithms (JoLEA)

Teaching

Physics and Measurements

Learning Machines

Other Activities, Projects & Achievements

• Nominated for best Master thesis award: at Vrije Universiteit Amsterdam for my work The Role of Proprioceptive Feedback in Learning Locomotion.
• 3rd Place in MRS competition: IEEE RAS on Multi Robot Systems (MRS), won 3rd place in multi-robot collaboration task using real drones.
• Volunteering during COVID-19: Helped to build the Dutch ICU Data warehouse, and developed reinforcement- and supervised learning models to improve hospital policies.
• Marathon: Completed Rotterdam marathon run in 3:24:55.