Making sense of signals, images and data
The Signal Processing Systems (SPS) group studies theories and techniques to extract meaningful information from signals, images, and multivariate data sets. We combine academic excellence with a strong real-world impact in biomedical instrumentation, medical image analysis, video surveillance, autonomous vehicles, digital wireless and optical communication, hearing aids, and intelligent lighting.
The SPS group has top scientists in signal and image analysis, information and communication theory, and machine learning and artificial intelligence. We also host many senior clinical and industrial experts on a part-time basis, which allows many of our students to be co-supervised by these experts.
We are an academic research team within the Signal Processing Systems group at Eindhoven University of Technology. Our main research...
Biomedical Diagnostics Lab
Clinical relevance is our commitment, achieved through close collaboration with selected clinical/industrial partners and advisors.
We focus on the fundamental limits of information processing (transmission, storage, and sensing) underlying our modern digital society....
Lighting and IoT Lab
With a strong background in signal procession, communication and information theory and in electronics, we are eager to connect to the...
NeuroPlatform is a multidisciplinary brain research program involving academic and commercial partners from both the Netherlands and...
Mobile Perception Systems Lab
The Mobile Perception Systems Lab researches methods in Artificial Intelligence that allow mobile autonomous systems to perceive their...
Video Coding & Architectures
Artificial Intelligence within the SPS Group
The SPS group conducts both fundamental and application-driven research on cutting-edge Artificial Intelligence (AI) technology for signal processing systems. We also provide a broad palette of academic coursework on AI that ranges from neuroscience-inspired learning algorithms to deep learning technology and from introductory to highly specialized levels.
Our group includes more than 25 academic faculty members and about 100 PhD students with specialized expertise across a wide range of machine learning and signal processing topics. This page provides a gateway to our activities on AI for signal processing systems.Read more
Meet some of our Researchers
Anouk van Diepen
Beatrijs van der Hout
Wim van Houtum
Bert de Vries
Merel van Gilst
Hans van Dijk
Ruud van Sloun
Judith van Laar
Catarina Dinis Fernandes
Hans van Gorp
Astrid Barreiro Berrio
Vinicius Oliari Couto Dias
Myrthe van der Ven
Dook van Mechelen
Esmée de Boer
As a hub in the regional innovation ecosystem, our group collaborates intensively with industry, hospitals and other societal stakeholders, with broad impact:
- Bidirectional staff exchanges: around 20 senior experts from strategic industrial and clinical partners have part-time appointments in the group, mostly at the level of full professor. Also, several of our senior staff members serve as scientific advisor to a variety of high-tech companies. Furthermore, many of our PhD students are embedded for a significant part of their time with strategic partners.
- Joint roadmaps: we contribute structurally to joint roadmaps with industry in the framework of e.g. the Center for Wireless Technology, the Center for Care and Cure Technologies and the Eindhoven MedTech Innovation Center.
- Industrial funding: many of our PhD projects are funded partly (and in several cases fully) by industry.
- Patents: our research frequently results in patent applications, either jointly with industry or with TU/e as main applicant.
- Real-world applications: over the years, many of our research results were absorbed in industrial products and/or clinical practice.
- Start-up companies: since 2000 we have produced 11 start-up companies.
Our most recent peer reviewed publications
Systolic blood pressure estimation using ECG and PPG in patients undergoing surgeryBiomedical Signal Processing and Control (2023)
Improving Lateral Resolution in 3-D Imaging With Micro-beamforming Through Adaptive Beamforming by Deep LearningUltrasound in Medicine and Biology (2023)
DeepLOS: Deep learning for late-onset sepsis prediction in preterm infants using heart rate variabilitySmart Health (2022)
A model-based approach to generating annotated pressure support waveformsJournal of Clinical Monitoring and Computing (2022)
Adapted ST analysis during laborJournal of Maternal-Fetal and Neonatal Medicine (2022)
Visiting addressFluxGroene Loper 195612 AP EindhovenNetherlands
Postal addressP.O. Box 513Department of Electrical Engineering5600 MB EindhovenNetherlands
Secretary BM/d, Mobile and Perseption Systems, Neu3CAbmd.secreesps@ tue.nl
Secretary VCAvca.secretariat@ tue.nl
Secretary BIAS, ICT, Lighting and IoTSecretarysecreesps@ tue.nl