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. My expertise lies at the intersection of signal processing and deep learning.

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. 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 am the responsible lecturer for the TU/e course Machine Learning for Signal Processing, where I shape both its content and delivery. I am excited to continue expanding my expertise in the broad domain of signal processing and applied deep learning.

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