About me

I am a postdoctoral researcher at the Eindhoven University of Technology (TU/e), working in close collaboration with NXP Semiconductors on advancing deep learning methods for automotive radar. I obtained my PhD (cum laude) from the Signal Processing Systems group in the Department of Electrical Engineering at TU/e, with research conducted in partnership with Philips Sleep and Respiratory Care. My expertise lies at the intersection of signal processing and deep learning. During my doctoral research, I explored how deep generative models can be leveraged to improve objective sleep monitoring, while also venturing into other signal processing areas such as inverse problems and active inference. I previously completed a summer internship at Qualcomm AI Research, where I worked on geopositioning using deep Kalman filtering techniques. Beyond research, I greatly enjoy presenting and teaching. I contribute as a co‑lecturer to the TU/e course Machine Learning for Signal Processing, where I actively help shape both content and delivery. I am excited to continue expanding my expertise in the broad domain of signal processing and applied deep learning.

Latest Publication

The Geometry of LISTA

Published in IEEE Signal Processing Magazine, 2026

Hans van Gorp, Oisín Nolan, Yonina C Eldar, and Ruud J G van Sloun, “The Geometry of LISTA,” IEEE Signal Processing Magazine, August 2026. [link] [pdf] [code]