Massimo Mischi is a Full Professor at the Faculty of Electrical Engineering of the Eindhoven University of Technology (TU/e) and chairs the Signal Processing Systems (SPS) Division , the largest division at TU/e with over 250 researchers. He founded the Biomedical Diagnostics (BM/d) Lab in 2012, which now includes 180 researchers and clinical/industrial advisors, focusing on biomedical signal processing for diagnostics and monitoring.
Qian Tao is an Assistant Professor at the Department of Imaging Physics , Faculty of Applied Sciences , Delft University of Technology . She previously worked at the Division of Image Processing, Department of Radiology, Leiden University Medical Center from 2009 to 2020. Academic Background: BSc in Electrical Engineering (Fudan University), MSc in Biomedical Engineering (Fudan University), PhD in Biometric Authentication (University of Twente) Research Interests: Focus on trustworthy AI methodologies for critical healthcare applications, including medical imaging for patient diagnosis and clinical intervention. Specializes in cardiac MRI analysis, image-guided interventions for cardiac arrhythmias, and AI in Radiology. Publication Trends: Recent work emphasizes motion correction in cardiac MRI, deep learning for image registration, and novel techniques like TRAFF2 mapping. Keywords include Medical Imaging , Machine Learning , Cardiac MRI , and Quantitative Analysis . Contact: Email: Q.Tao@tudelft.nl
Michel Versluis is a Full Professor at the University of Twente, Netherlands, specializing in Physical and Medical Acoustics within the Physics of Fluids group. His work focuses on microbubbles and microdroplets for medical imaging and therapy, as well as microfluidic applications in medicine and nanotechnology. University of Twente, Physics of Fluids group His research bridges physics and biomedical engineering, with publications in high-impact journals like PNAS and IEEE Transactions. Recent work emphasizes ultrasound-driven microbubble dynamics, additive manufacturing of flow phantoms, and deep learning for super-resolution imaging. 2025 publications: vascular phantoms, PROTEUS simulator, acoustic microbubble control 2024 innovations: 3D-printed medical devices, immunogenic cell death optimization Contact: m.versluis@utwente.nl
Hyosang Lee is an Assistant Professor in the Robotics Section of the Mechanical Engineering Department at Eindhoven University of Technology (TU/e). He holds a PhD from KAIST and has held research positions at the Max Planck Institute and University of Stuttgart. His work focuses on tactile sensing technologies, including artificial skin development, soft robotics, and integration of sensory systems with AI. Bachelor's: Mechanical Engineering, Korea University Master's: Robotics and Mechanical Engineering (double major) PhD: Mechanical Engineering, KAIST (2017) Research interests span tactile sensor design, electrical impedance tomography (EIT), and human-robot interaction. His group emphasizes creating scalable, flexible tactile systems for robots. Recent work includes air pressure sensing for force estimation and biomimetic skin materials. Publications highlight innovations in multi-directional force sensing, soft component technologies, and haptic interfaces for autism therapy. He teaches 'Dynamics and Control of Robotic Systems' and serves on the editorial board of npj Robotics . No formal student advisees are listed, though his lab, the Tactile Sensing and Robotic Skin Group , likely involves graduate researchers. His research contributes to UN Sustainable Development Goals related to health and technology.
Prof. Wouter Roos is a Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Molecular Biophysics department at the Zernike Institute for Advanced Materials. His research focuses on viral dynamics, membrane assemblies, and protein mechanics, utilizing advanced techniques like High Speed Atomic Force Microscopy (HS-AFM) and optical tweezers. Education: Studied Physics at the Universiteit van Amsterdam, earned a PhD from the Universität Heidelberg under Joachim Spatz. Conducted postdoctoral research at Max-Planck-Institut, Institut Curie, and Vrije Universiteit before joining Groningen in 2015. Research Interests: Physical Virology (viral material properties and dynamics), membrane biophysics (synthetic cells and lipid interactions), and molecular motor systems. His work bridges physics, chemistry, and biology to understand nanoscale biological processes. Recent Article Trends: Studies on hybrid membranes for synthetic cells, leukemic cell mechanics, and antibiotic-membrane interactions highlight his interdisciplinary approach. Key techniques include HS-AFM and single-particle tracking. Awards: Received a VIDI grant and multiple national/international grants. His lab leads the oLife Co-Fund consortium and participates in the MOSBRI research infrastructure. Grants & Leadership: Coordinates the oLife Fellowship Programme and chairs the Molecular Biophysics Lab. Active in steering committees for EU-funded initiatives. Labs/Teams: Heads the Molecular Biophysics Lab, focusing on viral dynamics and membrane systems. Collaborates globally on projects like ESCRT-III polymerization and antibiotic mechanisms.
Said Hamdioui serves as a full Professor in the Department of Computer Engineering within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on cutting-edge hardware architectures for neuromorphic computing and energy-efficient AI acceleration, with particular emphasis on memristor-based systems, emerging memory technologies, and fault-tolerant designs for edge applications. His research interests span Neuromorphic Computing , Memristor-Based Architectures , and Energy-Efficient AI Hardware , addressing critical challenges in hardware security, computation-in-memory, and reliable edge AI deployment. Recent work demonstrates significant advancements in RRAM/FeFET testing methodologies, spiking neural network implementations, and spin wave computing alternatives to traditional CMOS. His publications reveal strong trends toward real-world deployment of brain-inspired hardware with practical constraints like power efficiency, testability, and security. Award highlights include: DATE'20 Best Paper Award DFT'21 Outstanding Student Paper ETS 2021 Best Paper Award LATS 2018 & 2022 Best Paper Awards Professor Hamdioui actively contributes to the research community through editorial roles at IEEE Transactions on VLSI Systems , IEEE Design & Test , and Journal of Electronic Testing from 2017-2018. His leadership in multi-partner projects like CONVOLVE and NEUROKIT2E demonstrates strong industry-academia collaboration for edge AI solutions. Current work shows increasing focus on practical deployment challenges including in-field fault monitoring, security vulnerabilities in neuromorphic systems, and realistic brain simulation frameworks.
Sveta Zinger is a Full Professor in context-informed dynamic image analysis for clinical decision support at Eindhoven University of Technology (TU/e). She holds affiliations with the Biomedical Diagnostics Lab, NeuroPlatform, and EAISI Health. Her research focuses on medical image/video analysis, temporal data analysis, and machine learning for clinical applications. She has led projects funded by ZonMw, NWO, Philips, and others. She is also Co-Editor-in-Chief of Computer Methods and Programs in Biomedicine and serves on the Vidi committee for NWO. Education: MSc (2000) from Dnepropetrovsk State University; PhD (2004) from École Nationale Supérieure des Télécommunications, France. Postdoctoral roles at the French Atomic Agency and University of Groningen. Research Projects: Includes FORSEE (video monitoring for adverse events in healthcare) and NEUROTREND (fMRI biomarkers for depression). Awards: Second place in the CAMELYON17 challenge for metastases detection. Her teaching includes courses on DSP fundamentals, medical image processing, and cognitive neuroscience. She collaborates with clinical and industrial partners to advance biomedical diagnostics and healthcare technology.
Carlijn Bouten is Full Professor of Cell-Matrix Interactions in Cardiovascular Regeneration at Eindhoven University of Technology. She leads the Soft Tissue Engineering & Mechanobiology group, investigating cellular interactions with extracellular environments in tissue growth, adaptation, and regeneration. Her research develops biodegradable heart valve prostheses that enable in vivo tissue regeneration, applying tissue engineering approaches to cardiovascular medicine. Professor Bouten holds an MSc from Vrije Universiteit Amsterdam and a PhD from TU/e. She completed postdoctoral research at Université Laval and University of London before joining TU/e's faculty. She directs the national Gravitation program 'Materials-Driven Regeneration' and received an ERC Advanced Grant for cardiac tissue organization research. Research Focus: Her interdisciplinary program spans: Mechanobiological cues in tissue regeneration Development of living heart valve replacements Advanced biomaterials for cardiovascular applications In vitro models for tissue development Soft robotic systems for cardiac assistance Recent publications demonstrate innovations in biohybrid devices, standardized biomaterial testing, and novel tissue patterning techniques. Her work integrates engineering, materials science, and clinical translation through collaborations with medtech spin-offs. Leadership and Recognition: Fellow of the European Alliance for Medical and Biological Engineering President-elect of the Heart Valve Society Member of AcademiaNet for Outstanding Female Scientists Recipient of NWO VICI grant and Aspasia award She leads multinational consortia in regenerative medicine and teaches courses on heart/blood physiology and regeneration. Her lab develops model systems spanning cellular to tissue levels to quantify mechanobiological processes.
Anna Vilanova is a Full Professor in Visual Analytics at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e), and is associated with the Electrical Engineering department's Signal Processing Systems. Previously, she served as Associate Professor at TU Delft (2013-2019) and Assistant Professor at TU/e (2002-2013). Her research focuses on Visual Analytics for high-dimensional data , explainable AI , and biomedical applications including Diffusion Weighted Imaging, 4D Flow, and Pangenomics. Education: Doctorate in Computer Graphics & Visualization (2001) Master in Computer Science (1997), Universitat Politècnica de Catalunya Research Highlights: Vilanova leads work on Visual Analytics systems for biomedical data, with recent publications in Diffusion MRI modeling , Tractography visualization , Explainable AI frameworks , and Pangenomic variant analysis . Her work bridges dimensionality reduction , uncertainty visualization , and medical imaging applications. Scientific Contributions: NWO-Veni grant (2005): "Visualization of global tensor information for diffusion tensor imaging" NWO-Aspasia grant (2013) Best Poster Award EuroVis (2025) Best Demo/Poster Awards (2022) Leadership & Service: Vilanova serves on the IEEE VIS Steering Committee , was EUROGRAPHICS President (2019-2022), and contributes to conferences like IEEE Visualization and EG-EuroVis . She co-founded the EAISI Health research initiative at TU/e.
Michael Levin is a Distinguished Professor at Tufts University in the Department of Biology within the School of Arts and Sciences. He serves as Director of both the Allen Discovery Center at Tufts University and the Tufts Center for Regenerative and Developmental Biology. His laboratory investigates the intersection of developmental biology, artificial life, bioengineering, synthetic morphology, and cognitive science. Allen Discovery Center at Tufts Tufts Center for Regenerative and Developmental Biology Tufts/UVM: ICDO Harvard Wyss Institute Stibel Dennett Consortium for Brain and Cognitive Science The Proteus Institute MIT Science and Technology Center EBICS Levin's research focuses on understanding diverse intelligence in evolved, designed, and hybrid complex systems. His lab combines developmental biophysics, computer science, and behavioral science to study how cognition scales up from cellular competencies to organism-level behaviors. A key specialty is developmental bioelectricity—the study of how somatic electrical networks store, process, and act on information to control large-scale body structure. His team creates tools to read and edit the bioelectric code guiding proto-cognitive computations in the body. Levin's publications reveal a strong focus on bioelectricity, morphogenesis, and non-neural cognition across multiple model systems including Xenopus, planarians, and synthetic living constructs. His recent work explores collective intelligence as a unifying concept across biological scales, the development of microfluidic devices for measuring electrical connectivity, and optical estimation of bioelectric patterns in living embryos. His research spans fundamental developmental mechanisms to potential biomedical applications in regeneration and disease treatment. As an editor, Levin serves as Co-Editor-in-Chief of Bioelectricity and Founding Associate Editor of Collective Intelligence. He has mentored numerous post-doctoral fellows and graduate students who have gone on to establish their own research programs. His lab has received significant attention for creating novel biological machines (xenobots) and demonstrating that cells can store and transmit behavioral memory outside the brain. The Levin Lab maintains several significant research initiatives including the Allen Discovery Center at Tufts, the Tufts Center for Regenerative and Developmental Biology, and collaborations with the Wyss Institute at Harvard. The lab employs a multidisciplinary approach combining wet lab experiments with computational modeling to investigate how living systems achieve goal-directed behavior and pattern formation.
Dr. Dierck Hillmann is an Associate Professor at the Faculty of Science, Department of Biophotonics and Medical Imaging, Vrije Universiteit Amsterdam. He holds a PhD in Holoscopy from Luebeck University (2013). His research focuses on advanced optical imaging techniques, particularly Optical Coherence Tomography (OCT), with applications in retinal imaging, functional signal analysis, and computational imaging. He is affiliated with the LaserLaB - Biophotonics and Microscopy research group. Key research areas include improving OCT resolution through holographic methods, functional imaging of retinal neurons and photoreceptors, and developing computational adaptive optics to enhance imaging quality. His work addresses challenges like speckle reduction, aberration correction, and real-time data processing in biomedical imaging. Dr. Hillmann’s contributions span over 37 publications, including innovations in full-field OCT, optoretinography, and phase-sensitive measurements. He teaches courses such as Computational Optical Imaging and Light-Tissue Interaction. His current project explores imaging individual retinal cells and their functions using advanced techniques. No scientific awards are explicitly listed, but his extensive publication record reflects significant academic impact. Students advised are not specified in the provided materials.
Ralf Peeters is a Full Professor in Mathematics of Knowledge Engineering at Maastricht University's Faculty of Science and Engineering , Department of Advanced Computing Sciences. He serves as Vice-Dean of Research and Director of the STEM Graduate School, while leading the university's team at the inter-university research school DISC and co-chairing the Mathematics Centre Maastricht. Education: PhD in Mathematics (Free University, Amsterdam, 1994) Technical Mathematics (Delft University of Technology, 1988) Research Interests span applied mathematics, systems and control theory, signal/image processing, artificial intelligence, and biomedical engineering applications. His work bridges mathematical techniques with real-world challenges in healthcare and industrial systems. Recent Publications highlight advancements in deep learning for cardiac signal reconstruction, tensor-based signal decomposition, and recurrence plot analysis. These works integrate machine learning with clinical diagnostics, particularly in electrocardiographic imaging and arrhythmia characterization. Key Collaborations: Mathematics Centre Maastricht Dutch Mathematics Platform Dutch Institute of Systems and Control Leadership Roles: Vice-Dean of Research (FSE), Director of STEM Graduate School, Head of DISC-affiliated team, and Co-Chair of Mathematics Centre Maastricht. He has supervised over 25 PhD projects, emphasizing applied research across health and industrial domains.
Dr. Saer Samanipour is a Visiting Professor at the Van 't Hoff Institute for Molecular Sciences, part of the Faculty of Science at the University of Amsterdam. His research focuses on advanced analytical techniques for environmental and biomedical applications, with a strong emphasis on non-targeted analysis, mass spectrometry, and machine learning integration. He leads efforts in developing open-source tools like GcDUO and jHRMSToolBox to enhance data interpretation in complex chemical datasets. Key areas include environmental contaminant detection, chemical exposure assessment via wastewater-based epidemiology, and proteomic analysis of snake venoms. His work bridges computational methods with experimental chemistry to address global challenges in environmental health and toxicology. Primary affiliation: Van 't Hoff Institute for Molecular Sciences Research themes: Non-targeted LC-HRMS workflows, machine learning applications in analytical chemistry, PFAS analysis, and exposome research Software contributions: GcDUO (GC×GC-MS), jHRMSToolBox (HRMS data processing) His publications highlight innovations in data-driven approaches for compound prioritization, toxicity prediction, and method optimization. Recent work explores chemical space exploration and chemometric strategies for complex mixture analysis, with applications to environmental monitoring and forensic science.
Prof. SG (Guid) Oei is a full-time faculty member at the Eindhoven University of Technology (TU/e) in the Biomedical Diagnostics Lab under the Department of Electrical Engineering. He serves as a leading academic in the Eindhoven MedTech Innovation Center and the Center for Care & Cure Technology Eindhoven , focusing on advanced signal processing systems for maternal-fetal health diagnostics. Primary Affiliation: Professor , Electrical Engineering, TU/e Research Centers: Eindhoven MedTech Innovation Center, Biomedical Diagnostics Lab, Center for Care & Cure Technology Eindhoven Research Focus : Developing non-invasive fetal monitoring technologies, including electrohysterography and speckle tracking echocardiography , to improve detection of fetal distress, preterm birth prediction, and maternal-fetal health outcomes. His work bridges biomedical diagnostics with machine learning, emphasizing real-time clinical applications. Scientific Contributions : Over 288 research outputs with 4568 citations, including pioneering studies on: Fetal myocardial deformation analysis AI-enhanced cardiotocogram interpretation Extra-uterine life support system design Impact of maternal mental health on labor outcomes Optimization of uterine monitoring techniques Collaborative Networks : Works with key researchers like Jan WM Bergmans (NeuroPlatform), Massimo Mischi (Biomedical Diagnostics), and Judith OEH van Laar on projects spanning prenatal diagnostics, maternal-fetal coupling, and simulation-based obstetric training.
Judith OEH van Laar is an Assistant Professor in the Signal Processing Systems group at Eindhoven University of Technology (TU/e) and a gynecologist at Máxima Medical Center. Her research focuses on technological advancements for maternal and fetal health, including fetal monitoring systems and congenital defect detection. She holds a Master's in Medicine from Radboud University (2004) and a PhD from TU/e (2012) on fetal autonomic responses during pregnancy. She completed gynecology specialization at Máxima Medical Center (2014). Research interests include fetal electrocardiography, heart rate variability, and cardiotocogram analysis. She leads projects like HASTA (Healthy Ageing Starts with a HealThy stArt) and contributes to MEDEIA (MEDical Engineering Innovations and Applications). Recent work involves AI-driven fetal health assessment and maternal physiological monitoring. Key collaborations span biomedical engineering and clinical medicine.
