Picture of myself

Vincent Schellekens
researcher in sustainable AI

Welcome to my homepage! I am an engineer and researcher interested in sustainable artificial intelligence (low-resource machine learning, sustainable computing systems, etc.); see more on my research page. I am currently working as a researcher on sustainable electronics at imec. Find my complete cursus and more about me here. Don't hesitate to also check out my list of publications and related code.

Latest news

  • [02/2024] Working on updating my website after abandoning it for quite a while now... I hope to make it less ugly :-)
  • [05/2023] Researcher postition at imec in sustainable electronics.
  • [05/2022] Postoctoral researcher at the CEA Paris-Saclay on inverse problems on graphs applied to reflectometry.
  • [10/2021] Postdoctoral stay in ENS de Lyon with Rémi Gribonval on sparse deep neural network training.
  • [09/2021] Accepted paper, a tutorial on sketched learning in IEEE Signal Processing Magasine.
  • [06/2021] I'm a doctor :-) I succesfully defended my PhD thesis on the 28th of June! Massive thanks to everyone involved in this long but exciting adventure. You can (for now) find my thesis on the publications page of this site.
  • [02/2021] Accepted papers: I will be spamming the Information and Inference journal with two accepted papers :-) "Compressive Learning with Privacy Guarantees" and "Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines", soon to appear... stay tuned!
  • [08/2020] Invited talk: from the comfort of my office, titled "When compressive learning fails: blame the decoder or the sketch?", at the seminar series of the IDCOM Compressive Sensing group, Edinburgh.
  • [07/2020] Invited talk: I gave a (virtual) talk, "Introduction to Compressive Sensing", at the Institute of Neuroinformatics, University of Zurich and ETH Zurich.
  • [07/2020] Website update: I just added this "Latest news" section (well, you have to start somewhere).
  • [04/2020] Abstract accepted: our 2-page abstract " When compressive learning fails: blame the decoder or the sketch?" was accepted for presentation at iTWIST'20 (postoned due to COVID-19).