CV

Education

• Ph.D. in Automatic Sleep Staging using Deep Generative Modeling, Eindhoven University of Technology and Philips Sleep and Respiratory Care, end of 2025 (expected)
• MSc in Electrical Engineering, Eindhoven University of Technology, 2020
  • End project: Active deep probabilistic subsampling
• BSc in Electrical Engineering, Eindhoven University of Technology, 2018
  • End project: Dose distribution as outcome predictor for gamma knife radiosurgery on vestibular schwannoma

Work experience

• September 2020 - Present: Ph.D. Candidate
  • Eindhoven University of Technology, Department of Electrical Engineering, Signal Processing Systems, BM/d Lab
  • Philips Sleep and Respiratory Care, Eindhoven
  • Project: Automatic Sleep Staging using Deep Generative Modeling
• July 2024 - November 2024: Ph.D. 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

Research areas

• Signal Processing
• Deep learning
  • Deep generative models
  • Deep learning for inverse problems
  • Active Inference
• Automatic sleep staging

Patents

SYSTEM AND METHOD

SYSTEM AND METHOD FOR ESTIMATING SLEEP STAGE

Publications

Neural Augmented Kalman Filters for Road Network assisted GNSS positioning

SSC-SleepNet: A Siamese-Based Automatic Sleep Staging Model with Improved N1 Sleep Detection

A Deep Generative Model for Five-Class Sleep Staging with Arbitrary Sensor Input

Removing Structured Noise using Diffusion Models

Deep Sylvester Posterior Inference for Adaptive Compressed Sensing in Ultrasound Imaging

Learning Structured Compressed Sensing with Automatic Resource Allocation

Hypnogram and Hypnodensity Analysis of REM Sleep Behaviour Disorder Using Both EEG and HRV-Based Sleep Staging Models

The Tree of Diffusion Life: Evolutionary Embeddings to Understand the Generation Process of Diffusion Models

Single-channel EOG sleep staging on a heterogeneous cohort of subjects with sleep disorders

Model-Based Diffusion for Mitigating Automotive Radar Interference

Studying Sleep: Towards the Identification of Hypnogram Features that Drive Expert Interpretation

Modeling the impact of inter-rater disagreement on sleep statistics using deep generative learning

Aleatoric uncertainty estimation of overnight sleep statistics through posterior sampling using conditional normalizing flows

Certainty about uncertainty in sleep staging: a theoretical framework

Deep unfolding with normalizing flow priors for inverse problems

Representations of temporal sleep dynamics: Review and msynthesis of the literature

Image denoising with deep unfolding and normalizing flows

Active deep probabilistic subsampling

Dose distribution as outcome predictor for gamma knife radiosurgery on vestibular schwannoma

Teaching

• September 2020 - Present: 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