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Hans van Gorp

Postdoctoral Researcher · TU/e, NXP Semiconductors

h.v.gorp@tue.nl · hansvangorp.github.io · Eindhoven, The Netherlands

Research areas

• Signal processing
• Deep learning
• Deep generative models
• Deep learning for inverse problems
• Active inference
• Automatic sleep staging
• FMCW radar processing
• Ultrasound operator guidance

Education

• PhD (cum laude) on deep generative modeling in sleep diagnostics, Eindhoven University of Technology and Philips Sleep and Respiratory Care, 2026
• MSc in Electrical Engineering, Eindhoven University of Technology, 2020
• BSc in Electrical Engineering, Eindhoven University of Technology, 2018

Work experience

• February 2026 - Present: Postdoctoral researcher
  • Eindhoven University of Technology, Department of Electrical Engineering, Signal Processing Systems
  • NXP Semiconductors
  • Project: Deep learning in automotive radar
• September 2020 - January 2026: PhD (cum laude)
  • Eindhoven University of Technology, Department of Electrical Engineering, Signal Processing Systems, BM/d Lab
  • Philips Sleep and Respiratory Care, Eindhoven
  • Project: Deep Generative Modeling in Sleep Diagnostics
• July 2024 - November 2024: PhD Internship
  • Qualcomm AI Research, Amsterdam
  • Project: Neural Augmented Kalman Filters for Road Network Assisted GNSS Positioning
• August 2019 - October 2019: Research Intern
  • Philips Research, Eindhoven
  • Project: Suppression of pump distortion for inflation-based noninvasive blood pressure measurement

Grants awarded

• 2026: TTT-AI voucher
  • Polaris: Operator Guidance for Carotid Ultrasound

Publications

• Ultrasound Operator Guidance Using World Modeling and Retrieval Based Action Planning Noortje I.P. Schueler, Hans van Gorp, and Ruud J.G. van Sloun. arXiv preprint, 2026.
• The Geometry of LISTA Hans van Gorp, Oisín Nolan, Yonina C Eldar, and Ruud J G van Sloun. IEEE Signal Processing Magazine, 2026.
• Automatic Sleep Staging and Atonia Detection in RBD Using Single-Channel Chin EMG Hans van Gorp, Jaap F van der Aar, Ruud J G van Sloun, Angelique Pijpers, Pedro Fonseca, Sebastiaan Overeem, Merel M van Gilst. Journal of Parkinson’s Disease, 2026.
• Deep Generative Modeling in Sleep Diagnostics Hans van Gorp. PhD thesis, Eindhoven University of Technology, 2026.
• A Deep Generative Model for Five-Class Sleep Staging with Arbitrary Sensor Input Hans van Gorp, Merel M van Gilst, Pedro Fonseca, Fokke B van Meulen, Johannes P van Dijk, Sebastiaan Overeem, and Ruud J G van Sloun. IEEE Journal of Biomedical and Health Informatics, 2025.
• Neural Augmented Kalman Filters for Road Network Assisted GNSS Positioning Hans van Gorp, Davide Belli, Amir Jalalirad, Bence Major. ICML Workshop on Machine Learning for Wireless Communication and Networks, 2025.
• SSC-SleepNet: A Siamese-Based Automatic Sleep Staging Model with Improved N1 Sleep Detection Songlu Lin, Zhihong Wang, Hans van Gorp, Mengzhu Xu, Merel M van Gilst, Sebastiaan Overeem, Jean-Paul Linnartz, Pedro Fonseca, Xi Long. IEEE Journal of Biomedical and Health Informatics, 2025.
• Removing Structured Noise Using Diffusion Models Tristan S.W. Stevens, Hans van Gorp, Faik C. Meral, Junseob Shin, Jason Yu, Jean-Luc Robert and Ruud J.G. van Sloun. Transactions on Machine Learning Research (TMLR), 2025.
• Deep Sylvester Posterior Inference for Adaptive Compressed Sensing in Ultrasound Imaging Simon W Penninga, Hans van Gorp, and Ruud J G van Sloun. ICASSP, 2025.
• Learning Structured Compressed Sensing with Automatic Resource Allocation Han Wang, Eduardo Pérez, Iris A. M. Huijben, Hans van Gorp, Ruud van Sloun, and Florian Römer. ICASSP, 2025.
• Hypnogram and Hypnodensity Analysis of REM Sleep Behaviour Disorder Using Both EEG and HRV-Based Sleep Staging Models Jaap F. van der Aar, Merel M. van Gilst, Daan A. van den Ende, Hans van Gorp, Peter Anderer, Angelique Pijpers, Pedro Fonseca, Elisabetta Peri, Sebastiaan Overeem. Journal of Sleep Research, 2025.
• The Tree of Diffusion Life: Evolutionary Embeddings to Understand the Generation Process of Diffusion Models Vidya Prasad, Hans van Gorp, Christina Humer, Anna Vilanova, and Nicola Pezzotti. arXiv preprint, 2024.
• Single-Channel EOG Sleep Staging on a Heterogeneous Cohort of Subjects with Sleep Disorders Hans van Gorp, Merel M van Gilst, Sebastiaan Overeem, Sylvie Dujardin, Angelique Pijpers, Bregje van Wetten, Pedro Fonseca and Ruud J G van Sloun. Physiological Measurement, 2024.
• Model-Based Diffusion for Mitigating Automotive Radar Interference Jeroen Overdevest, Xinyi Wei, Hans van Gorp, and Ruud J G van Sloun. ICASSP, 2024.
• Studying Sleep: Towards the Identification of Hypnogram Features That Drive Expert Interpretation Caspar van der Woerd, Hans van Gorp, Sylvie Dujardin, Manuel Sastry, Humberto Garcia Caballero, Fokke van Meulen, Stef van den Elzen, Sebastiaan Overeem, Pedro Fonseca. Sleep, 2023.
• Modeling the Impact of Inter-Rater Disagreement on Sleep Statistics Using Deep Generative Learning H. van Gorp, M. M. van Gilst, P. Fonseca, S. Overeem, and R. J. G. van Sloun. IEEE Journal of Biomedical and Health Informatics, 2023.
• Aleatoric Uncertainty Estimation of Overnight Sleep Statistics Through Posterior Sampling Using Conditional Normalizing Flows H. van Gorp, M. M. van Gilst, P. Fonseca, S. Overeem, and R. J. G. van Sloun. ICASSP, 2023.
• Certainty About Uncertainty in Sleep Staging: A Theoretical Framework H. van Gorp, I. A. M. Huijben, P. Fonseca, R. J. G. van Sloun, S. Overeem, and M. M. van Gilst. Sleep, 2022.
• Deep Unfolding with Normalizing Flow Priors for Inverse Problems X. Wei, H. van Gorp, L. Gonzalez Carabarin, D. Freedman, Y. C. Eldar, and R. J. G. van Sloun. IEEE Transactions on Signal Processing, 2022.
• Representations of Temporal Sleep Dynamics: Review and Synthesis of the Literature L. W. A. Hermans, I. A. M. Huijben, H. van Gorp, T. R. M. Leufkens, P. Fonseca, S. Overeem, and M. M. van Gilst. Sleep Medicine Reviews, 2022.
• Image Denoising with Deep Unfolding and Normalizing Flows X. Wei, H. van Gorp, L. Gonzalez Carabarin, D. Freedman, Y. C. Eldar, and R. J. G. van Sloun. ICASSP, 2022.
• Active Deep Probabilistic Subsampling H. Van Gorp, I. A. M. Huijben, B. S. Veeling, N. Pezzotti, and R. J. G. Van Sloun. ICML, 2021.
• Dose Distribution as Outcome Predictor for Gamma Knife Radiosurgery on Vestibular Schwannoma P. P. J. H. Langenhuizen, H. van Gorp, S. Zinger, H. B. Verheul, S. Leenstra, and P. H. N. de With. Medical Imaging, 2019.

Patents

• System and Method for Generating Output Data Using a Generative Model H. van Gorp, P. Fonseca, M. M. van Gilst, S. Overeem, and R. J. G. van Sloun. US Patent Application 2025/0079004, 2025.
• System and Method for Estimating Sleep Stage H. van Gorp, P. Fonseca, M. M. van Gilst, S. Overeem, and R. J. G. van Sloun. US Patent Application 2025/0072825, 2025.

Teaching

• September 2026 - Present: Responsible lecturer
  • Eindhoven University of Technology
  • Course: Machine Learning for Signal Processing
• September 2020 - September 2026: co-lecturer
  • Eindhoven University of Technology
  • Course: Machine Learning for Signal Processing
• September 2016 - September 2020: Student Teaching Assistant
  • Eindhoven University of Technology
  • Courses: Computation, Calculus, Applied Physics

Volunteering

• Leader at Scouting Nederland for the ‘welpen’ (cub scouts), kids aged 7 through 11