9747 AG Groningen
I am interested in interdisciplinary research in and around computer science and artificial intelligence: nature-inspired computing, understanding human cognition, and advancing artificial intelligence.
My PhD is on non-digital computing theory in the MINDS research group and the CogniGron research center, funded by the European Post-Digital research network. I am developing concepts and methods for programming and interfacing with unconventional computers. I am working with analog neuromorphic hardware (spikes!), photonic computing systems, and other physical systems that can compute and/or learn.
In my free time I am a hobby photographer, like to read, travel, and go to music and art events.
To schedule a meeting, please use this page to book a time in my calendar.
I am available to supervise bachelor and master projects at RUG in fall 2022. If you are interested in working on a project related to machine learning or neural networks in novel neuromorphic hardware systems, please send me an email.
Topic ideas that I would find particularly interesting:
- learning in neural networks using local learning rules for bio-plausibility and efficient hardware implementation: equilibrium propagation and learning algorithms using dendritic processing are particularly promising.
- evolving modular components in recurrent neural network architectures.
- exploring different local learning rules in recurrent neural networks.
- autonomous multi-task learning for recurrent neural networks (e.g. using conceptors).
- neurosymbolic programming for neuromorphic hardware: merging machine learning with “classical” programming.
|Jun 2022||Back in Groningen after three months at the Institute of Neuroinformatics (ETH/UZH in Zurich).|
|May 2022||Talk on physical reservoir computing to the CogniGron research center (slides).|
|Mar 2022||Internal Post-Digital presentation of progress on programming spiking neuromorphic hardware.|
|Feb 2022||Presentation on my PhD topic to the CogniGron center of cognitive materials (slides).|
- Hands-on reservoir computing: a tutorial for practical implementationNeuromorphic Computing and Engineering 2022
- Automated architecture design for deep neural networksArXiv Aug 2019