Rene Miedema

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Ir Rene Miedema

  • Position: MSc, Scientific Researcher, Erasmus MC
  • Member of:

Biography

Rene Douwe Miedema was born in Spijkenisse, The Netherlands in 1992. He received his BSc degree in Electrical Engineering in 2015 and his MSc Computer Engineering in 2019 both from the Delft University of Technology. Currently, he is a PhD student at the Neuroscience Department of the Erasmus Medical Center under the supervision of Christos Strydis and co-supervision of Mario Negrello. His research investigates the use of machine learning for brain simulations.

Research Interests

  1. High-Performance Computing
  2. Machine learning
  3. Numerical methods
  4. Brain modeling

Education

2019

Master of Science

in Computer Engineering, Delft University of Technology

2015

Bachelor of Science

in Electrical Engineering, Delft University of Technology

Publications

1. ExaFlexHH: an exascale-ready, flexible multi-FPGA library for biologically plausible brain simulations.

Miedema R, Strydis C
in Frontiers in neuroinformatics 2024
DOI: 10.3389/fninf.2024.1330875

2. Tricking AI chips into simulating the human brain: A detailed performance analysis

Landsmeer L, Engelen M, Miedema R, Strydis C
in Neurocomputing 2024
DOI: 10.1016/j.neucom.2024.127953

3. Synthesis-Free, Flexible and Fast Hardware Library for Biophysically Plausible Neurosimulations - POSTER

Rene Miedema, Georgios Smaragdos, Mario Negrello, Zaid Al-Ars, Matthias Möller, and Christos Strydis
in FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays 2020
DOI: 10.1145/3373087.3375374

4. flexHH: A Flexible Hardware Library for Hodgkin-Huxley-Based Neural Simulations

Miedema R, Smaragdos G, Negrello M, Al-Ars Z, Möller M, Strydis C
in IEEE Access 2020
DOI: https://dx.doi.org/10.1109/ACCESS.2020.3007019

5. A novel simulator for extended Hodgkin-Huxley neural networks.

Sotirios Panagiotou, Rene Miedema, Harry Sidiropoulos, Georgios Smaragdos, Christos Strydis, Dimitrios Soudris
in 2020
DOI: 10.1109/BIBE50027.2020.00071

6. High-Performance Hardware Accelerators for Solving Ordinary Differential Equations.

Ioannis Stamoulias, Matthias Möller, Rene Miedema, Christos Strydis, Christoforos Kachris, Dimitrios Soudris
in Proceedings of the 8th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies 2017
DOI: 10.1145/3120895.3120919
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