Find Academic Supervisors

Freek J. BeekmanView profile

Professor

• Biomedical Imaging
• Nuclear Imaging
• Image Reconstruction Algorithms
• +12 more

Prof. Freek J. Beekman is a Full Professor and head of the Biomedical Imaging section within the Department of Radiation Science & Technology at Delft University of Technology (TU Delft), Faculty of Applied Sciences. He is a leading figure in biomedical imaging, with extensive contributions to nuclear imaging technologies, including SPECT, PET, and CT. His research spans detector development, image reconstruction algorithms, hybrid photonic imaging, and the application of artificial intelligence in medical imaging. Research Interests: His work focuses on advancing imaging modalities through innovations in hardware (e.g., multi-pinhole collimators) and software (e.g., deep learning for attenuation correction). He has pioneered ultra-high-resolution imaging systems, particularly for preclinical and clinical SPECT, and has developed integrated platforms like U-SPECT-BioFluo. His recent research explores glymphatic delivery of nanoparticles, infection imaging, and AI-driven reconstruction techniques, reflecting a strong translational focus. Publication Trends: His most recent publications (2021–2023) emphasize deep learning in SPECT, multi-isotope imaging, high-resolution ex vivo systems, and applications in neuroimaging and oncology. The articles demonstrate a consistent focus on improving image quality, resolution, and clinical utility through physics-informed and AI-enhanced methods. Scientific Awards: NWO Physics Valorization Prize Innovation of the Year Award by the World Molecular Imaging Society (2015, 2018) Edward Hoffman Memorial Award (2017) Bruce Hasegawa Memorial Award (2021) FOM Valorization Award (2013) TU Delft Entrepreneurial Award (2010) Advising and Grants: While specific student names are not listed, his leadership in large collaborative projects and supervision of numerous publications suggests active mentoring. He has secured significant funding through national and international grants, evidenced by his invention of over 20 patent families and successful technology transfer. His founding and leadership of MILabs BV (sold to Rigaku) highlights his impact on commercialization and industry-academia collaboration. Labs and Teams: He leads the Biomedical Imaging research group at TU Delft, which develops cutting-edge imaging systems such as VECTor (SPECT-PET) and EXIRAD-HE. His teams have produced technologies used globally in academic and pharmaceutical research, contributing to tracer development and therapeutic innovation.

Anna VilanovaView profile

Professor

• Visual Analytics
• Explainable AI
• Biomedical Image Analysis
• +6 more

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.

Peter DesainView profile

Professor

• Brain-Computer Interfaces
• Neuroscience
• Electrophysiology
• +3 more

Peter Desain is a Professor and Principal Investigator at the Donders Institute for Brain, Cognition and Behaviour, Radboud University. His work focuses on developing advanced brain-computer interfaces (BCI) leveraging evoked potentials, particularly through code-modulated visual and auditory stimuli. He pioneers methods like noise-tagging and Bayesian dynamic stopping to enhance BCI efficiency and accessibility. His research spans neurotechnology, electrophysiological modeling, and clinical applications such as objective EEG audiometry and ALS communication aids. Recent studies emphasize gaze-independent systems, semantic decoding, and minimizing BCI calibration requirements. Key contributions include optimizing c-VEP code-books, real-time fMRI neurofeedback for memory contexts, and literature reviews on BCI design trends. Experimental pilot studies explore auditory attention and high-frequency SSVEP dynamics. No scientific awards are explicitly mentioned. His work integrates multidisciplinary approaches, bridging neuroscience, machine learning, and engineering to advance human-computer interaction and clinical tools.

Peng WangView profile

Visiting Professor

• Mental Health
• Emotion Dynamics
• Child and Adolescent Development
• +3 more

Peng Wang is a Visiting Professor at the Department of Philosophy of the Sciences within the Faculty of Humanities at Vrije Universiteit Amsterdam. His academic qualifications include a PhD in Language and Emotion from VU University Amsterdam, and advanced studies in Linguistics, Education Research, and Public Health Statistics from Missouri State University, the University of Edinburgh, and the University of Oxford. His research focuses on interdisciplinary topics such as mental health interventions, emotion dynamics in education, neurodiversity advocacy, and healthcare communication. Key areas include transdiagnostic mental health approaches, ecological momentary assessment frameworks, and the integration of AI with neurotechnological research. Recent publications explore innovative methods for mental health monitoring (e.g., trimodal emotion assessment systems), universal school-based interventions for children, and the neuroethical implications of neurodiversity research. His work bridges philosophy of science with applied research in healthcare and education systems. No formal awards are listed, though his research has garnered attention across multiple platforms including Mendeley and Bluesky. Collaborations span global institutions with a focus on child mental health and healthcare professional wellbeing.

Stephen RaineyView profile

Lecturer

• Philosophy of Mind
• Philosophy of Language
• Neurotechnology
• +3 more

Stephen Rainey is a Lecturer and Researcher at Delft University of Technology, affiliated with the 4TU.Ethics research group. His work bridges philosophy, neurotechnology, and ethical governance, focusing on the implications of brain-computer interfaces (BCIs) and neurodata for human identity and rights. He has contributed to European research projects since 2011, particularly in neurotechnology ethics and responsible innovation. His research interests include: Philosophy of mind and language, influenced by Austin, Grice, and Brandom Neurotechnology and its ethical, legal, and societal impacts Theory of governance and responsible research practices Recent publications address neurorights, neuroprosthetic speech, mind-reading technologies, and data governance challenges. His work emphasizes interdisciplinary engagement, combining neuroscience, AI, and political philosophy to analyze human-technology interactions in clinical and societal contexts.

• Artificial Intelligence
• Cognitive Neuroscience
• Robotics
• +3 more

Prof. W.F.G. Haselager is a Professor of Artificial Intelligence at Radboud University Nijmegen, affiliated with the Donders Institute for Brain, Cognition and Behaviour and the Donders Centre for Cognition. He holds dual expertise in philosophy, psychology, and AI, focusing on societal implications of emerging technologies. His research integrates empirical methods (e.g., robotics, computational modeling) with philosophical inquiry into agency, responsibility, and human self-understanding. Education: MSc degrees in Philosophy and Psychology, PhD (1995) from Vrije Universiteit Amsterdam. Teaching responsibilities include bachelor/master programs in AI and Cognitive Neuroscience. Active in public engagement through lectures/workshops on AI ethics, neurotechnology, and free will. Key research themes include neuroethics, AI equity, and brain-computer interfacing. Current projects include the ELSA Lab (AI for Health Equity) and 'Healthy Data' initiatives addressing algorithmic bias and medical AI oversight. He advises Zander Labs on neurotechnology ethics and co-leads multi-institutional grants exploring conversational AI and neurodiverse education. Media appearances include Dutch TV/NOS coverage of brain implants and podcasts on AI sentience. Ancillary activities include the 'Pim Haselager Lectures' series and advisory roles in neurotechnology ethics.

David MarescaView profile

Associate Professor

• Biomolecular acoustic sensors
• Functional ultrasound neuroimaging
• Transcranial ultrasound
• +3 more

David Maresca is an Associate Professor in the Imaging Physics department at the Faculty of Applied Sciences, Delft University of Technology. His research focuses on the intersection of ultrasound imaging physics and molecular engineering, with the goal of enabling ultrasound imaging of cells across space and time in living opaque organs. His research interests include: Biomolecular acoustic sensors Functional ultrasound neuroimaging Transcranial ultrasound Nonlinear ultrasound imaging Engineering of acoustic biosensors Ultrasound imaging of brain function Dr. Maresca's work centers on developing technologies that combine ultrasound physics with molecular engineering to create new imaging capabilities. His lab pioneers approaches to image cells within opaque organs using ultrasound, with applications in neuroscience and biomedical imaging. His research spans from fundamental ultrasound physics to the development of acoustic biosensors and imaging techniques that can detect cellular processes. His recent publications demonstrate a strong focus on advancing ultrasound imaging capabilities, particularly in nonlinear ultrasound techniques, contrast-enhanced ultrasound, and applications in neuroimaging. His work shows increasing interdisciplinary collaboration across physics, engineering, and neuroscience. Dr. Maresca has received recognition including the HFSP Cross-Disciplinary Fellowship. His academic background includes a Ph.D. in Biomedical Engineering from Erasmus MC, an M.Sc. in Acoustics, and a Master's degree in Physics from Université Paris Diderot. He completed postdoctoral work at Caltech and Institut Langevin, ESPCI. His research is supported by collaborations across institutions, with recent work involving researchers from multiple universities and research centers. Dr. Maresca's lab is actively contributing to advancing ultrasound imaging technology and its applications in biomedical research.

Ronald AartsView profile

Professor

• Ambulatory Monitoring
• Signal Processing
• Biomedical Engineering
• +6 more

Ronald Aarts is a Full Professor (part-time) at Eindhoven University of Technology (TU/e) in the Department of Signal Processing Systems, affiliated with the EAISI institute. His research focuses on ambulatory and unobtrusive monitoring systems, integrating engineering with medicine and biology. He holds dual roles as a part-time professor and a long-term researcher at Philips Research since 1977. His expertise spans electromagnetism, acoustics, signal processing, and sensor technology. Education: BSc and PhD in Electrical Engineering and Physics from Delft University of Technology. Research Interests: Sensors for biomedical applications, sleep and cardiology monitoring, epilepsy detection, and wearable health technologies. Awards: Gilles Holst Award (1999), Philips Gold Invention Award (2012), IEEE Fellowship (2007), AES Silver Medal (2010). He has supervised over 19 PhD students and holds >250 patents. Key contributions include advancements in EEG-fMRI artifact suppression, non-invasive circulatory monitoring, and sleep state classification in preterm infants.

Andreea SburleaView profile

Assistant Professor

• Brain-Computer Interfaces
• Machine Learning
• Neuroprosthetics
• +3 more

Andreea Sburlea is an Assistant Professor in Human Centered Intelligence at the Faculty of Science and Engineering, University of Groningen . Her expertise focuses on Brain-Computer Interfaces , Machine Learning , and Neuroprosthetics , with a particular emphasis on uncertainty quantification in BCI systems. Research Trends : Recent publications highlight her work in applying machine learning and deep learning to motor imagery BCI, transfer learning for P300-based systems, and quantifying classification uncertainties in biosignal applications. Collaborations : Active in international research networks, she collaborates with institutions like the German Research Center for Artificial Intelligence (DFKI) and contributes to conferences such as the Graz Brain-Computer Interface Conference . Contact : Email a.i.sburlea@rug.nl | ORCID

Herke van HoofView profile

Associate Professor

• Reinforcement Learning
• Modular Reinforcement Learning
• Hierarchical Structures
• +5 more

Herke van Hoof serves as Associate Professor at the University of Amsterdam within the Informatics Institute, where he leads research in the AMLab at Science Park (Lab 42, L4.05). His academic journey spans from AI degrees at Groningen University through doctoral studies at TU Darmstadt under Professor Jan Peters to postdoctoral research at McGill University with Professors Joelle Pineau, Dave Meger, and Gregory Dudek. PhD: TU Darmstadt (2016), supervised by Prof. Jan Peters Postdoc: McGill University, Montreal AI Bachelor & Master: University of Groningen Van Hoof's research focuses on overcoming data inefficiency in reinforcement learning through modular and hierarchical approaches. His work explores how structured representations can enable knowledge transfer between tasks, improve learning efficiency, and facilitate applications in domains with complex state and action spaces. The lab investigates symmetry exploitation in multi-agent systems, gradient estimation techniques for discrete variables, and applications to combinatorial problem solving. His publication record shows consistent contributions to top AI venues including ICML, ICLR, NeurIPS, and JMLR over the past seven years. The research trajectory demonstrates evolution from foundational policy search methods toward increasingly sophisticated modular architectures, with recent emphasis on knowledge-assisted AI for critical infrastructure applications through the AI4REALNET project. Third place in ARC prize (Paper award) Van Hoof actively supervises PhD candidates and postdoctoral researchers, with current projects including human-robot collaboration using brain-computer interfaces (with Maryam Alimardani at VU) and interactive robot learning with flexible human input (through The Hybrid Intelligence Centre). His research receives support from multiple funding initiatives including the AI4REALNET project which focuses on applying AI to critical infrastructure systems. As co-organizer of the BeNeRL 2024 workshop and participant in the AI4REALNET consortium, van Hoof maintains strong connections with the broader European AI research community while directing the AMLab's research on modular reinforcement learning approaches.

Peter HagoortView profile

Professor

• Cognitive Neuroscience
• Neurolinguistics
• Language Disorders
• +3 more

Peter Hagoort is a renowned cognitive neuroscientist and Professor of Cognitive Neuroscience at Radboud University Nijmegen. He serves as Director Emeritus of the Max Planck Institute for Psycholinguistics and Founding Director of the Donders Institute for Brain, Cognition and Behaviour. His research focuses on the neural basis of language, employing techniques like ERP, MEG, PET, and fMRI to study language processing in health and disorders such as aphasia, dyslexia, and autism. He holds multiple prestigious awards, including the NWO-Spinoza Prize (2005), the Yuen Ren Chao Prize (2024), and the Silver University Medal from Radboud University (2023/2024). He is a member of the Royal Netherlands Academy of Arts and Sciences (KNAW) and the National Academy of Sciences (USA). Current research interests include the neurobiological mechanisms of language comprehension and production, inter-brain synchrony in communication, and the cognitive neuroscience of spoken language using animal models like bats. He supervises PhD students exploring topics such as vocal learning in bats and neural dynamics of communication in autism spectrum conditions. Awards: Over 10 major prizes, including the Spinoza Prize and Yuen Ren Chao Prize. Grants & Leadership: Programme director of the Gravitation program Language in Interaction; steering roles in national and international initiatives. Labs/Teams: Donders Institute Neurobiology of Language group; Max Planck Psycholinguistics Institute.

Maryam AlimardaniView profile

Associate Professor

• Brain-Computer Interfaces
• Virtual Reality
• Neurofeedback
• +5 more

Dr. Maryam Alimardani is an Associate Professor at the Faculty of Science, Computer Science department, Vrije Universiteit Amsterdam, and a member of the Network Institute. Her research focuses on neurotechnology applications in human-computer interaction, including brain-computer interfaces (BCIs), virtual reality (VR), and robotics. She explores topics such as neurofeedback training for ADHD, workload prediction in flight simulations, and the psychological impact of human-agent interactions. Her work bridges cognitive neuroscience, robotics, and educational technology, with a particular emphasis on improving mental health interventions and learning outcomes through technology. Research interests include EEG analysis for cognitive state monitoring, gamification strategies in BCI training, and the uncanny valley effect in human-robot collaboration. She has contributed to studies on social robotics for stress management, virtual agent design, and the neurophysiological basis of trust in AI systems. Her recent publications address VR flight simulation neural patterns, the role of gender in motor imagery BCIs, and the ethical implications of passive vs. active BCIs. Collaborations span aviation neurophysiology, consumer neuroscience for sustainability, and pediatric language learning through robots. Alimardani teaches Human-Computer Interaction courses and leads projects on adaptive learning systems. Her work emphasizes translational research, applying neuroscientific insights to real-world applications in education, healthcare, and human-technology collaboration.

Hans van DijkView profile

Researcher

• Biomedical Engineering
• Clinical Neurophysiology
• Electrophysiology
• +7 more

Hans van Dijk serves as a Senior Researcher in the Signal Processing Systems group within the Department of Electrical Engineering at Eindhoven University of Technology. He simultaneously holds leadership and research positions at multiple institutions, heading the Clinical Physics department at Kempenhaeghe (an institute specializing in Epileptology and Sleep medicine) and working as a Senior Researcher at the University Hospital in Ulm, Germany. His multidisciplinary career bridges engineering, clinical neurophysiology, and sleep medicine. Dr. van Dijk's research focuses on biomedical engineering applications in Clinical Neurophysiology, with particular expertise in electrophysiological techniques including EEG, EMG, and ECG. His work centers on developing and applying signal processing methods to diagnose neurological disorders, with specific emphasis on seizure detection using EEG , High-Density EMG for facial and masticatory muscles , and alternative diagnostic methods for sleep disorders . His recent publications demonstrate a strong focus on applying machine learning techniques to sleep medicine and epilepsy monitoring. Analysis of Dr. van Dijk's recent publications (2021-2025) reveals a consistent research trajectory in developing advanced signal processing methods for clinical neurophysiology. His work spans three main domains: epilepsy monitoring and seizure detection (particularly in children), sleep disorder diagnostics (using multimodal approaches beyond traditional polysomnography), and advanced EMG techniques for motor unit analysis. His research increasingly incorporates deep learning and multi-modal sensor fusion approaches to improve diagnostic accuracy while reducing the invasiveness of monitoring procedures. 2699 citations according to Scopus metrics 101 research outputs documented in institutional repository Active research collaboration with Philips Research and Kempenhaeghe Contributions to UN Sustainable Development Goals through medical diagnostics research Dr. van Dijk supervises research activities with 8 documented supervised works, collaborating extensively with clinical and engineering researchers across multiple institutions. His research program integrates signal processing expertise with clinical needs in neurology and sleep medicine, developing practical solutions for monitoring and diagnosing neurological disorders. His work at Kempenhaeghe focuses on translating engineering innovations into clinical practice for epilepsy and sleep disorder patients.

• Information Visualization
• Augmented Reality
• Human-Computer Interaction
• +2 more

Boyu Xu is a researcher at Utrecht University 's Faculty of Science , affiliated with the Department of Information and Computing Sciences and the Visualization and Graphics group. Her work bridges Information Visualization , Augmented Reality (AR) , and Neuroscience Data Analysis , focusing on tools for exploring scientific literature. She developed the DatAR project, which enables neurologists to analyze connections between brain regions and diseases from over 400,000 PubMed publications. Her research also explores how Generative AI can enhance creative processes in visual art and design. Prior to her PhD, she worked on graphic design , game design , and commercial AR applications , with a portfolio at xuboyumedia.com . Her publications (2024–2025) at conferences like MultiMedia Modeling and CHIIR emphasize AR-based research methodologies , interactive neuroscience tools , and timeline visualization for mapping indirect-to-direct relationships in scientific data. She collaborates with supervisors Prof. Lynda Hardman and Dr. Wolfgang Hürst , but no formal advising roles or scientific awards are listed.

Marion TränkleView profile

Lecturer

• Performance Art
• Systems Thinking
• Interactive Media
• +5 more

Marion Tränkle is an active lecturer at the ArtScience Interfaculty of the Royal Academy of Art, The Hague (KABK), where she coaches students and develops courses on systems thinking and rule-based performance systems. She also serves as a Coach and Industrial Liaison at Eindhoven University of Technology's Department of Industrial Design since 2014, working with Professor Harm van Essen on 'social interactions with shared systems.' Her educational background spans multiple disciplines: PhD from Brunel University London (2012), MSc in Media Technology from Leiden University (2005), BA in Contemporary Dance from Amsterdam School of the Arts (2001), and an Engineer Diploma in Architecture from Technical University Berlin (1993). She has also completed specialized training in Software Engineering (2017/18) and Stage Lighting (2016). Tränkle's research interests center on the intersection of performance art, systems thinking, and technology. She creates work that deliberately negotiates 'the constructive tension between the carefully constructed and generative processes, between risk and responsibility, and between autonomous performance and human intervention.' Her practice integrates computational processes with live-performance, often using electronics, EEG data, and interactive systems to create immersive stage scenarios. She explores how simple rules can generate complex emergent behaviors, drawing from complexity science and computing principles. Her recent creative works demonstrate a consistent exploration of brain-computer interfaces, interactive light systems, and collaborative performance structures. Projects like (un)focussed and BLINK...and sync use EEG data to create real-time visual and auditory experiences, while ON TRACK and TAROT investigate mechanical systems and embodied symbolism through performance. 2nd Prize in the competition for short dance films on Internet 'webdans' (2001) Netherlands Foundation for Visual Arts, Design and Architecture Research/Travel Grant (2010) e-MobiLArt participant, funded EU CULTURE 2007 Programme (2008-09) Brunel University Doctoral Research Scholarship/fee waiver (2007-10) Tränkle actively collaborates with artists, designers, and engineers through collectives like NOW (with Ivo Bol and Roos van Berkel) and previously In Serial. She is a member of the BAU Committee for Amsterdam's independent performance scene. Her teaching philosophy emphasizes that 'making, learning, and teaching are reciprocal processes that flourish best in collaborative, and project-based environments,' which she implements through workshops, seminars, and interdisciplinary courses across multiple institutions in the Netherlands, Germany, and Canada.