Hi!

I am a postdoctoral researcher at Eindhoven University of Technology (TU/e). I research the use of generative models for signal processing applications, ranging from medical imaging to semiconductor manufacturing and automotive radar. My research interests are centered around fundamental probabilistic machine learning techniques and the possibility of integrating them with classical signal processing methods. I am the co-creater of the zea Python package for cognitive ultrasound imaging. Currently, I am also a member of the EURASIP Academy. Besides my research, I love to play guitar, trumpet, chess, code, and climb rock.

This website serves two purposes. Beside an overview of my work, I also try to post some interesting articles on things I learned or figured out that might be useful to anyone.

News

Publications

26 Jan 2026

Ultrasound Imaging in the Era of Deep Generative Modeling

Stevens, Tristan S.W. (2026), Eindhoven University of Technology

16 Jan 2026

Task-Based Adaptive Beamforming for Efficient Ultrasound Quantification

Nolan, Oisín, et al. (2026), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

12 Sep 2025

Nuclear Diffusion Models for Low-Rank Background Suppression in Videos

Stevens, Tristan S.W., et al. (2026), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

24 Aug 2025

Semantic Diffusion Posterior Sampling for Cardiac Ultrasound Dehazing

Stevens, Tristan S.W., et al. (2025), Preprint

12 Aug 2025

Patient-Adaptive Focused Transmit Beamforming using Cognitive Ultrasound

van Nierop, Wessel L., Nolan, Oisín, Stevens, Tristan S.W., et al. (2025), Preprint

21 Jul 2025

zea: A Toolbox for Cognitive Ultrasound Imaging

Stevens, Tristan S.W., et al. (2025), The Journal of Open Source Software (in review)

28 May 2025

High Volume Rate 3D Ultrasound Reconstruction with Diffusion Models

Stevens, Tristan S.W., et al. (2025), High Volume Rate 3D Ultrasound Reconstruction with Diffusion Models, IEEE Transactions on Medical Imaging

16 Apr 2025

Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging

Stevens, Tristan S.W., et al. (2025), Philosophical Transactions of the Royal Society A

9 Sep 2024

Sequential Posterior Sampling with Diffusion Models

Stevens, Tristan S.W., et al. (2025), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

21 Jun 2024

Active Diffusion Subsampling

Nolan, Oisín, Stevens, Tristan S.W., et al. (2025), Transactions on Machine Learning Research

21 Jul 2023

Dehazing Ultrasound using Diffusion Models

Stevens, Tristan S.W., et al. (2023), Dehazing Ultrasound using Diffusion Models, IEEE Transactions on Medical Imaging

10 Jan 2023

Removing Structured Noise with Diffusion Models

Stevens, Tristan S.W., et al. (2025), Transactions on Machine Learning Research

1 Dec 2022

A Hybrid Deep Learning Pipeline for Improved Ultrasound Localization Microscopy

Stevens, Tristan S.W., et al. (2022), International Ultrasonics Symposium (IUS)

23 May 2022

Accelerated Intravascular Ultrasound Imaging using Deep Reinforcement Learning

Stevens, Tristan S.W., et al. (2022), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

23 May 2022

Deep Proximal Unfolding For Image Recovery from Under-Sampled Channel Data in Intravascular Ultrasound

Chennakeshava, Nish, et al. (2022), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

23 Aug 2021

Automated Gain Control Through Deep Reinforcement Learning for Downstream Radar Object Detection

Stevens, Tristan S.W., et al. (2021), IEEE 29th European Signal Processing Conference (EUSIPCO)

21 Oct 2019

Deep Learning for Radar Target Detection in Non-Homogeneous Clutter

Stevens, Tristan S.W., et al. (2019), Preprint