Visualization Algorithms Professors and Supervisors in Netherlands

José van DijckView profile

Professor

Utrecht UniversityNetherlands

José van Dijck is a Distinguished University Professor of Media and Digital Society at Utrecht University's Faculty of Humanities, Department of Media and Performance Studies. She obtained her PhD in Comparative Literature from the University of California, San Diego (1992) after graduating from Utrecht University (1985). Previously, she served as Dean of Humanities at the University of Amsterdam (2008-2012) and President of the Royal Netherlands Academy of Arts and Sciences (KNAW, 2015-2018). Her research critically examines the impact of digital platforms, algorithms, and datafication on public values, democracy, and societal structures. Key research domains include platform governance, digital education infrastructures, AI ethics, and the preservation of public values in connective technologies. Her conceptualization of the 'Platform Society' has become foundational in media studies. Major scientific awards include the Spinoza Prize (2021), the C.Edward Baker Award for lifetime achievements from the International Communication Association, and honorary doctorates from Lund University (2019) and University of Oslo (2024). She leads Utrecht University's focus area Governing the Digital Society , developing tools like the Ethical Data Assistant (DEDA) for public institutions. She advises governments on digital policy (e.g., COVID-19 apps) and contributes to initiatives like PublicSpaces coalition. Her research has been supported through the Spinoza Prize grant (€2.5M) focusing on public digital infrastructures. Van Dijck directs research on platformization in education, data governance, and AI. She collaborates with Utrecht Data School and coordinates international projects like PERITIA on trust in expertise. Her work bridges humanities, law, public administration, and computer science.

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Jeroen J.L. SchepersView profile

Associate Professor

Eindhoven University of TechnologyNetherlands

Jeroen J.L. Schepers is an Associate Professor at Eindhoven University of Technology, affiliated with the Department of Industrial Engineering and Innovation Sciences and the Innovation Technology Entrepreneurship & Marketing group. He also holds a position within the EAISI Foundational research institute. His current educational activities include teaching courses on Marketing Perspectives on Product Innovation, Servitization and Customer Experience, and Multivariate Statistics. Dr. Schepers specializes in the digitalization and robotization of frontline services, with particular focus on the psychological responses of both customers and employees to service technologies. His research examines how AI and robotics transform service encounters, exploring questions about customer adoption of service innovations, the impact of technology on service value, and the optimal collaboration between humans and technology in service delivery. His work spans service marketing, human-robot interaction, consumer psychology, and digital service transformation, with particular emphasis on service robotics, customer experience design, and the psychological mechanisms underlying technology adoption in service contexts. His recent publications reveal a strong focus on human-AI collaboration in service contexts, with recurring themes around service robot design, customer perception of technology, and the psychological mechanisms that determine service success or failure. His research demonstrates how service robots impact customer experience, how frontline employees interact with AI systems, and how service encounters can be optimized through intelligent technology integration. The work spans both theoretical development and practical applications across various service industries. Dr. Schepers has received numerous prestigious awards including the Robert Johnston Outstanding Reviewer Award (2024), multiple highly cited papers in the top 1% of Economics & Business, the Insights Scientist of the Year award (2023), and several Industria Education Awards. His research has been recognized with Best Paper Awards from leading service marketing journals and conferences. HybridLabs - €10.4M grant accelerating Dutch innovations in offshore renewables D-SIDE: Decision Support for Intelligent Damage Estimation and Control (€1.1M) 3TU.CEE research project Grant from DAAD for visiting scholarship at University of Mannheim Dr. Schepers leads research within the Innovation Technology Entrepreneurship & Marketing group, focusing on how digital technologies transform service encounters and employee-customer interactions. His work examines both customer-facing service technologies and employee-facing intelligent systems, investigating how these technologies reshape service delivery, customer experience, and employee work practices in the digital age.

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Ömür ArslanView profile

Assistant Professor

Eindhoven University of TechnologyNetherlands

Ömür Arslan is an assistant professor in the Department of Mechanical Engineering at the Eindhoven University of Technology (TU/e) , affiliated with the Robotics Group and the EAISI Mobility and EAISI High Tech Systems institutes. His research focuses on the algorithmic foundations of robotics, particularly safe adaptive motion planning algorithms for robots operating around humans. Education: PhD in Electrical and Systems Engineering (2016), University of Pennsylvania MSc in Electrical Engineering (2012), University of Pennsylvania MSc in Electrical & Electronics Engineering (2009), Bilkent University BSc in Electrical & Electronics Engineering (2007), Middle East Technical University His research interests span robotics, motion planning, control theory, sensor networks, dynamical systems, optimization, machine learning , and machine perception . Recent work includes safe unicycle control, probabilistically safe corridors, and statistical coverage control of mobile sensor networks. He has received nominations for best paper awards at ICRA 2018 and WAFR 2016 . Ömür has supervised student projects such as Hancheng Min's MSc thesis on statistical coverage control and Vincent Pacelli's work on local geometry in motion planning .

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E. EisemannView profile

Professor

Delft University of TechnologyNetherlands

E. Eisemann is a Professor at the Computer Graphics and Visualisation department within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology (TU Delft). Their research focuses on computer graphics, virtual reality, and 3D modeling, with recent publications addressing ray-box intersections, neural scene representations, and interactive modeling systems. Current research trends include Advancements in real-time rendering algorithms Applications of neural networks for 3D scene reconstruction Innovative approaches to human-computer interaction in VR environments Optimization techniques for large-scale environment rendering Research output spans 164 publications, with recent work appearing in venues like Computer Graphics Forum and ACM SIGGRAPH conferences. Supervised work includes 18 formal advisees.

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Zerrin YumakView profile

Assistant Professor

Utrecht UniversityNetherlands

Zerrin Yumak is an Assistant Professor at the Department of Information and Computing Sciences, Faculty of Science, Utrecht University, specializing in virtual humans and social robotics. She leads Task 3.2: Embodiment and Physical Interaction in the RAGE project. Her research focuses on Social and emotional behavior analysis for virtual characters Machine learning applications in motion capture data Constrained motion graph search algorithms Lip-sync and gesture animation generation Real-time multimodal interaction systems Notable projects include the Virtual Human Controller asset for Unity 3D, integrated with BiP Media and Randstad applications. Recent work spans 2025: SemGes for semantics-aware gesture generation 2024: ProbTalk3D emotion-controllable facial animation 2023: Diffusion model-based facial animation (Facediffuser) 2020: Music-driven expressive gesture generation She contributes to workshops like GENEA (2021-2022) and MASSXR (2025), advancing non-verbal behavior modeling for embodied agents.

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Mohammad FotouhiView profile

Assistant Professor

Delft University of TechnologyNetherlands

Mohammad Fotouhi is an Assistant Professor at Delft University of Technology's Faculty of Civil Engineering and Geosciences, specifically within the Materials, Mechanics, Management & Design (3MD) department. He has held academic positions at the University of Glasgow, University of the West of England, and University of Bristol, focusing on structural health monitoring and composite material development. PhD in Mechanical Engineering from Amirkabir University of Technology MSc and BSc in Mechanical Engineering from Amirkabir and Tabriz Universities His research spans bio-inspired composites , 4D printing , and smart materials , with emphasis on self-sensing , multi-functional composites , and damage detection . Recent work explores piezoelectric sensors for structural strain analysis and chaos-integrated neural networks for nonlinear regression. While no formal awards are listed, his publications demonstrate leadership in fatigue monitoring , impact damage detection , and hybrid material design . Collaborations with institutions like University of Bristol and ResearchGate profile highlight his academic network.

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Mohsen KaboliView profile

Assistant Professor

Eindhoven University of TechnologyNetherlands

Mohsen Kaboli is an Assistant Professor (Part-time) at Eindhoven University of Technology (TU/e) in the Netherlands, affiliated with the Department of Electrical Engineering and the Electronic Systems group. Since 2018, he has served as head of the AI, Robotics & Cognitive Vehicle research lab at BMW Group’s Center of Invention in Munich, Germany. Previously, he held positions at Radboud University’s Institute for Brain and Cognition (2019-2022) and Technical University of Munich (TUM) as a postdoctoral research fellow. His research focuses on Embodied Robotics, Visuo-Tactile Interactive Perception, and Machine Learning, with applications in Robotic Grasping, Human-Robot Collaboration, and Neuromorphic Computing. He leads European-funded projects like PHASTRAC (Oscillatory Neural Networks for AI Edge Computing) and INTUITIVE (Tactile User Interfaces). Keywords: Tactile Intelligence, AI, Robotics Application Domains: Mobile Robotics, Medical Instrumentation, Neuroprosthetics His recent publications (e.g., ViTract, Shared Visuo-Tactile Perception) emphasize robust object pose estimation and shape reconstruction using Bayesian filtering and Graph Neural Networks. He has authored ~40 academic works and contributed to 20 patents. Scientific Awards : IEEE Senior Member (2018) Georges Giralt Ph.D. Award (Finalist) IEEE ICRA Outstanding Paper Award (Finalist, 2023) IEEE FLEPS Outstanding Student Award (Winner, 2022) IEEE ROSE Outstanding Paper Award (Winner, 2024) Mohsen Kaboli serves as Editor/Associate Editor for IEEE ICRA, IROS, R-AL, T-RO, and IJRR. His work bridges tactile perception, AI, and robotics, with impacts in wearables, medical devices, and autonomous systems.

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Mahdi KhodadadzadehView profile

Assistant Professor

University of TwenteNetherlands

Mahdi Khodadadzadeh is an Assistant Professor in the Department of Geo-information Processing, specializing in machine learning, data mining, and geospatial analysis. His work bridges traditional and deep learning methods with applications in mineral exploration, environmental modeling, and circular economy initiatives. Research outputs include novel cross-validation techniques for geospatial machine learning (Spatial+, dissimilarity-adaptive methods), hyperspectral mineral mapping for ore characterization, and hybrid models combining artificial neural networks with optimization algorithms. He actively contributes to open-access datasets and methodologies, particularly in drill-core analysis and multi-source data fusion. Collaborations with researchers like R. Zurita-Milla and R. Gloaguen are evident through co-authored publications and shared datasets. His work impacts domains such as mineral exploration, geospatial modeling, and sustainable resource management, with a focus on robust statistical evaluation frameworks and spectral-spatial analysis.

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Koray KaracaView profile

Assistant Professor

University of TwenteNetherlands

Koray Karaca is an Assistant Professor in Philosophy , specializing in the intersection of Artificial Intelligence , Machine Learning , and Philosophy of Science . His work critically examines epistemic and ethical dimensions of AI, with a focus on Knowledge Representation and Reasoning , Human-AI Interaction , and Experimental Methodology in high-energy physics. Research interests span Artificial Intelligence , Autonomous Agent Systems , and Scientific Modeling . His studies analyze diagrammatic representations in collaborative particle physics experiments, inductive risk in ML modeling, and robustness in experimental results. Recent publications explore experimental robustness , Higgs mechanism epistemology , and ethical frameworks for AI . His work combines Physics , Machine Learning , and Philosophical Analysis , addressing challenges in theory-ladenness , data acquisition , and interdisciplinary collaboration . Karaca’s contributions include developing design thinking frameworks for AI systems and evaluating scientific unification across physics domains. His studies on binary classification models highlight the societal implications of technical decisions in machine learning.

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Serdar YavuzyigitogluView profile

Researcher

Erasmus University RotterdamNetherlands

Serdar Yavuzyigitoglu is a Researcher in the Department of Ophthalmology at Erasmus University Medical Center (Erasmus MC), Rotterdam, specializing in uveal melanoma research. His work spans molecular diagnostics, treatment outcomes, and epidemiological studies of this rare ocular malignancy. His primary research focuses on genetic drivers of uveal melanoma (particularly BAP1 and SF3B1 mutations), metastatic progression patterns, and comparative effectiveness of radiation therapies. He investigates how chromosomal aberrations like 8q gain influence prognosis, examines global incidence patterns correlated with pigmentation factors, and analyzes 30-year treatment trends in Dutch patient cohorts. His research bridges molecular biology with clinical outcomes to improve risk stratification and therapeutic decision-making. Analysis of his 15 most recent publications reveals consistent emphasis on metastatic uveal melanoma biology, with growing integration of genomic data into clinical frameworks. His work demonstrates strong epidemiological rigor in population studies while advancing molecular understanding of treatment resistance mechanisms, particularly in liver metastasis contexts. Yavuzyigitoglu actively collaborates with the Rotterdam Ocular Melanoma Study Group (ROMS), contributing to multi-center investigations that have generated significant clinical insights published in high-impact journals including Scientific Reports, Ophthalmology Science, and Cancers.

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Antonios LiapisView profile

Associate Professor

Codarts RotterdamNetherlands

Antonios Liapis is an Associate Professor at the Institute of Digital Games, University of Malta. He completed his PhD in September 2014 under the supervision of Georgios N. Yannakakis at the IT University of Copenhagen. His academic journey includes an M.Sc. in Information Technology from the same institution and a 5-year Diploma in Electrical and Computer Engineering from the National Technical University of Athens. Dr. Liapis has held various academic positions at the University of Malta: Post-doctoral Researcher (2014-2015), Lecturer (2015-2020), Senior Lecturer (2020-2022), and currently Associate Professor (2022-present). He has served as General Chair for multiple international conferences including FDG (2020), GALA (2019), and EvoMusArt (2018-2019). He is an Associate Editor of the IEEE Transactions on Games and a member of the Games Technical Committee of the IEEE Computational Intelligence Society. His research focuses on Artificial Intelligence as an autonomous creator and as a facilitator of human creativity. Key areas include computationally intelligent tools for game design and computational creators that blend semantics, visuals, sound, plot, and level structure to create various game genres including horror, adventure, shooter, and dungeon crawler games. His work has resulted in over 150 peer-reviewed publications and several research awards. Dr. Liapis has secured multiple research grants from the European Commission, including projects on AI-powered robotic material recovery, virtual reality aided design, and learning science through coding and play. His notable project series "Data Adventures" demonstrates the use of open data from Wikipedia, DBpedia, Wikimedia Commons, and OpenStreetMap to automatically generate adventure games with complete plots, characters, items, and locations. His scientific contributions have been recognized with several awards including Best Paper Awards at major conferences, Best Reviewer Award, and Runner-Up Best Student Paper Award. Dr. Liapis has also co-organized 16 workshops in diverse conferences throughout his career. Research interests include: Artificial Intelligence for creative applications Procedural Content Generation in games Computational Creativity systems Machine Learning for game design Affective Computing in virtual environments Human-AI collaboration in creative processes His recent work shows a strong trend toward integrating Large Language Models with game design, exploring quality diversity algorithms for creative applications, and advancing affect modeling for improved player experience. The research spans computer science, artificial intelligence, game studies, and human-computer interaction, with practical applications in education, entertainment, and design.

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Jan Mathijs SchoffelenView profile

Associate Professor

Radboud UniversityNetherlands

Dr. Jan Mathijs Schoffelen serves as Associate Principal Investigator at Radboud University's Donders Institute for Brain, Cognition and Behaviour, where he leads research on brain connectivity using MEG and EEG methodologies. He represents the Norris PI group in the DCCN Representative Council and is a core developer of the globally adopted FieldTrip open-source analysis toolbox, contributing to major initiatives including the Human Connectome Project and MOUS. His research centers on neural synchronization mechanisms during cognitive processes, particularly investigating how brain rhythms facilitate inter-regional communication in language tasks. He addresses critical challenges in non-invasive electrophysiology including signal-to-noise optimization and source reconstruction validity, advancing methods to interpret neural interactions in healthy human cognition where invasive techniques are impossible. Publications reveal consistent focus on gamma-band coherence in sensorimotor systems, attentional modulation through synchronization, and computational frameworks for connectivity analysis. His work bridges theoretical neuroscience with practical tool development, demonstrating growing emphasis on language processing applications alongside foundational motor and visual system investigations. Scientific recognition includes: Young investigator award at Biomag conference, Sapporo (2008) NWO VIDI-grant for independent research leadership (2015) As Principal Investigator, he directs the FieldTrip project while contributing to large-scale collaborations like the Human Connectome Project. His NWO VIDI grant supports methodological innovations for non-invasive connectivity analysis, enabling new investigations into cognitive neuroscience. Embedded within the Donders Institute's Norris research group, he collaborates through the international FieldTrip community to advance electrophysiological analysis standards, maintaining active development of open-source tools that serve thousands of neuroscientists worldwide.

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Gang MeiView profile

Associate Professor

National Research Institute for Mathematics and Computer ScienceNetherlands

Dr. Gang Mei is an Associate Professor in Scientific Computing within the School of Engineering and Technology at China University of Geosciences (Beijing), where he has held academic positions since 2014. His career progression includes Postdoctoral Researcher (2014-2016), Lecturer (Oct-Dec 2016), and current Associate Professor (since Jan 2017). His research bridges computational science and engineering applications with significant editorial contributions to computer science literature. Education: Ph.D. in Computer Science, University of Freiburg, Germany (2014) Research Interests: Dr. Mei specializes in Numerical Simulation and Computational Modeling, GPU Computing, Machine Learning, and Data Mining, with strong applications in Network Science and Spatial Information Systems. His work integrates Distributed and Parallel Computing techniques for large-scale scientific simulations, particularly in geospatial modeling and network analysis. The research demonstrates consistent focus on computational efficiency through hardware acceleration and algorithmic optimization across diverse domains including satellite imagery processing, financial event detection, and medical image classification. Publication Trends: His editorial portfolio reveals strong interdisciplinary patterns connecting computer science fundamentals with domain-specific applications. Recent works emphasize GPU-accelerated methods for data-intensive problems (2020-2022), spatial-temporal modeling (2019-2020), and network science applications (2021). The publications consistently address computational scalability challenges while maintaining practical relevance across geospatial, financial, medical, and engineering contexts. Professional Recognition: As an IEEE Member, Dr. Mei serves on editorial boards for IEEE Access and PeerJ Computer Science, reflecting peer recognition in computational fields. His editorial contributions span 15+ publications demonstrating expertise in evaluating cutting-edge computer science research. Academic Service: Beyond editorial work, Dr. Mei's service includes advising on computational methodology across multiple disciplines. His role as Academic Editor demonstrates commitment to scholarly communication, particularly in bridging theoretical computer science with practical engineering applications. No grant funding details were specified in available materials.

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