Find Academic Supervisors

• Information Visualization
• Human-Computer Interaction
• Machine Learning
• +6 more

Dr. Angelos Chatzimparmpas is an Assistant Professor in the Department of Information and Computing Sciences at Utrecht University's Faculty of Science, specializing in the Visualization and Graphics subgroup. His research focuses on developing visual analytics systems to enhance understanding and trust in machine learning models, particularly in the domain of Explainable AI (XAI). He maintains active collaborations with institutions including Northwestern University where he completed his postdoctoral research. Dr. Chatzimparmpas earned his educational credentials through an impressive international trajectory: BSc and MSc in Informatics and Telecommunications Engineering from the University of Western Macedonia, Greece (2017), PhD in Computer and Information Science from Linnaeus University, Sweden (completed February 2023), followed by a postdoctoral position in Computer Science at Northwestern University, USA (completed March 2024). His research interests span Information Visualization, Human-Computer Interaction, and Machine Learning with a specialized focus on Explainable AI. He investigates visual exploration of machine learning models' inner workings, model uncertainty quantification, evaluation of visualization systems using deep learning architectures, and detection of AI-generated images (deepfakes). His work bridges theoretical machine learning concepts with practical visualization techniques to make complex AI systems more transparent and trustworthy for human users. Analysis of his recent publications reveals a clear trajectory focusing on visual analytics for machine learning interpretability. His work systematically addresses challenges in understanding ensemble learning methods, dimensionality reduction techniques, and deep learning models through innovative visualization approaches. A significant portion of his research targets the growing problem of AI-generated content, developing methods to distinguish authentic from synthetic media. His publications appear in top-tier venues including IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, and CHI Conference proceedings. Dr. Chatzimparmpas teaches several advanced courses including Data Science Colloquium, Game Programming, Optimization and Vectorization, and Visual Analytics for Big Data. His teaching directly reflects his research expertise, providing students with cutting-edge knowledge in visualization and machine learning integration. He is actively involved with the Utrecht Platform for Applied Data Science and contributes to research in Applied Data Science, Game Research, and Human-centered Artificial Intelligence. His work demonstrates strong interdisciplinary connections between computer science, cognitive science, and domain-specific applications requiring trustworthy AI systems.

• Educational Psychology
• Example-Based Learning
• Multimedia Learning
• +5 more

Tamara van Gog is Professor of Educational Sciences at Utrecht University and Distinguished International Professor of Learning and Instruction at the LEAD Graduate School and Research Network of the Eberhard Karls University of Tübingen, Germany. She coordinates the research program of the Education section at Utrecht University and has made significant contributions to the field of educational psychology through her extensive research and publications. Her educational background includes a degree in Developmental and Educational Psychology from Tilburg University (2001) and a PhD cum laude from the Open University of the Netherlands (2006). She previously held positions at the Open University of the Netherlands and Erasmus University Rotterdam, where she was appointed endowed professor of Educational Psychology in 2012. Van Gog's research primarily focuses on example-based learning, multimedia learning, and self-regulated learning, reflection, and critical thinking skills. She frequently employs eye tracking methodology to investigate learning processes across all educational levels and in medical contexts. Her work bridges cognitive psychology with practical educational applications, examining how learners process information and regulate their learning. Her recent publications demonstrate a consistent focus on metacognition, self-regulation, and the application of eye tracking in educational settings. She explores how students monitor and regulate their learning, how teachers assess student understanding, and how technology can support these processes. Her research spans K-12 education, higher education, and medical training contexts. NWO Rubicon grant (2007) NWO Veni grant (2008) NWO Vidi grant (2012) NWO Vici grant (2021) Member of The Young Academy of the Royal Netherlands Academy of Arts and Sciences (2010-2015) Van Gog has secured substantial research funding throughout her career, including multiple prestigious NWO grants. She has served on editorial boards for leading journals including Contemporary Educational Psychology and Journal of Experimental Psychology: Applied. Her work has influenced both theoretical frameworks and practical applications in educational settings. She collaborates extensively with researchers across multiple institutions and disciplines, demonstrating the interdisciplinary nature of her work. Her research team frequently investigates innovative techniques for using eye tracking as both a research tool and an instructional enhancement in educational contexts.

• Video-Based Learning
• Self-Regulated Learning
• Learning-by-Teaching
• +6 more

Dr. Vincent Hoogerheide is an Assistant Professor at the Department of Education within the Faculty of Social and Behavioural Sciences at Utrecht University. He holds a Master's degree (2011) and PhD (2016) in educational psychology from Erasmus Universiteit Rotterdam, both earned cum laude . His research focuses on video-based learning , self-regulated learning (SRL) , and learning-by-teaching through vlogging , exploring how these methods enhance motivation and academic success. PhD in Educational Psychology (2016) Master's in Educational Psychology (2011) BSc in Psychology (2009) Hoogerheide's work investigates the efficacy of video modeling examples and self-regulated learning strategies in digital environments. He also pioneered research on student-created instructional videos as a homework activity, demonstrating its effectiveness and enjoyment. His publications often bridge educational psychology , technology in education , and cognitive load theory , with recent studies analyzing task-selection training, mental effort appraisals, and the role of solution diversity in vicarious learning. Scientific recognition includes being identified as the 33rd most productive researcher in top-tier educational psychology journals (2017-2022). He has contributed to 40 research outputs and participated in 17 academic activities , including invited talks, editorial work, and hosting academic visitors. His media contributions, such as the 2019 Learning Scientists article and 2024 EARLI Research Stories podcast, highlight his commitment to translating research into practice.

• Nanophotonics
• Nanomaterials Science
• Iontronic Microscopy
• +6 more

Dr. Zhu Zhang is a Researcher at Utrecht University, affiliated with the Faculty of Science, Department of Physics, Debye Institute for Nanomaterials Science, and the Nanophotonics Research Group. Based at the Leonard S. Ornstein Laboratory in Utrecht, Zhang conducts cutting-edge research at the intersection of nanophotonics, electrochemistry, and nanomaterials science, with a focus on developing advanced microscopy techniques to visualize nanoscale phenomena. Zhang's research program centers on iontronic microscopy and the study of colloidal systems at the nanoscale. Key contributions include developing methods to visualize ionic currents under optical microscopes, investigating nanoscale electrocatalytic reactions, and understanding the dynamics of colloidal particles in electro-osmotic environments. The research combines experimental physics with nanotechnology to create innovative approaches for studying processes that were previously difficult to observe directly. Analysis of Zhang's publication record from 2019-2025 reveals a consistent trajectory of increasingly sophisticated research in nanophotonics. The work has evolved from fundamental studies of nanoparticle charge and Brownian motion to more complex investigations of electrocatalysis and iontronic regulation inside nanostructures. Recent publications demonstrate growing expertise in combining multiple techniques—optical microscopy, microfluidics, and electrochemical methods—to address challenging problems in nanoscience. As an educator, Zhang contributes to undergraduate physics education through teaching assistant roles, specifically in the practical component of statistical physics courses where students learn microscopy techniques and data analysis. Zhang's technical expertise spans light and electron microscopy, microfluidics, and computational analysis using Python and Matlab, providing a comprehensive skill set for nanoscale research.

• Veterinary Education
• Competency-Based Learning
• Programmatic Assessment
• +4 more

Prof. Harold Bok is a full-time Professor and Vice Dean for Education at Utrecht University's Faculty of Veterinary Medicine. He chairs the research group 'Educational Scholarship in Veterinary Medicine', focusing on bridging educational theory and practice in veterinary education. His academic journey includes a DVM (2005), PhD in 'Competency-based Veterinary Education' (2014), Utrecht University Teaching Fellowship (2015-2017), and Principal Fellow at Utrecht's Centre for Academic Teaching (2023). His research specializes in: Competency-based curriculum design and workplace learning Programmatic assessment frameworks and entrustable professional activities Innovations in veterinary education technology and simulation Professional development and clinical skill acquisition His recent publications demonstrate strong focus on assessment methodologies, educational technology integration, and competency-based veterinary training, with increasing emphasis on digital learning solutions and program evaluation. Honors and Awards AAVMC Presidential Award for Meritorious Service (2020) The Clinical Teacher IMPACT Award (2024) Best PhD-Thesis in Medicine/Veterinary Medicine (2015) 2× Nominee for Senior Teacher of the Year (2017, 2019) Best Scientific Paper in Medical Education (2012) As Vice Dean, he oversees educational programs including the Bachelor's and Master's in Veterinary Medicine, and leads initiatives in competency-based curriculum development. He chairs international committees including AAVMC's Council on International Veterinary Medical Education (2019-2020).

Matthijs SpaanView profile

Professor

• Safe and Robust Reinforcement Learning
• Planning Under Uncertainty
• Sequential Decision Making
• +5 more

Matthijs Spaan is a Professor of Reliable AI Algorithms at Delft University of Technology , where he co-directs the Sequential Decision Making group in the Department of Intelligent Systems (EEMCS faculty). Previously, he served as an Associate Professor in the Algorithmics group at TU Delft and as a Senior Research Scientist at the Institute for Systems and Robotics, Instituto Superior Técnico (Lisbon). He holds a PhD in Computer Science (2006) and an MSc in Artificial Intelligence (2002) from the University of Amsterdam. His research focuses on safe and robust reinforcement learning , planning under uncertainty using POMDPs/Dec-POMDPs, and sequential decision-making algorithms . He has contributed to embedding epistemic uncertainty in deep reinforcement learning, safe policy improvement, and constrained decision-making frameworks for smart energy systems, robotics, and traffic optimization. His work includes 15+ key publications in top venues like AAAI, IJCAI, ICAPS, and AAMAS, spanning 2024 to 2011. He has advised four PhD students to completion and co-organized major workshops such as the Lorentz workshop on Rigorous Automated Planning (2022) and AAAI 2022 program. His professional service includes editorial roles at AI Magazine and Journal of Artificial Intelligence Research , area chair positions, and leadership in IJCAI, ICAPS, and IFAAMAS.

Tristan van LeeuwenView profile

Professor

• Inverse Problems
• Computational Imaging
• Tomography
• +2 more

Tristan van Leeuwen is Professor of Computational Inverse Problems at Utrecht University's Mathematical Institute within the Faculty of Science. He is also the leader of the Computational Imaging Group at Centrum Wiskunde & Informatica (CWI) in Amsterdam. Van Leeuwen's research focuses on unraveling the underlying mathematics of imaging techniques to improve their application in healthcare and geosciences. His work develops computational methods, including algorithms, to solve inverse problems involving determining unknown causes or properties of systems based on observable effects. His publications demonstrate applications in various domains including X-ray CT reconstruction, defect detection in industrial settings, and educational data analysis. Recent work has increasingly incorporated machine learning approaches to optimize imaging processes. Van Leeuwen leads the Computational Imaging group at CWI and is involved in multiple externally funded projects including Flexible X-ray Laminography for Art and IMAGINE. He teaches courses on Inverse Problems in Imaging and Scientific Computing.

• Computer Vision
• Medical Imaging
• Artificial Intelligence
• +3 more

Yue Sun serves as a University Researcher in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), affiliated with both the Center for Care & Cure Technology Eindhoven and the Eindhoven MedTech Innovation Center (EMTE). Holding an MSc degree, Sun specializes in computer vision and AI applications spanning medical imaging and agricultural technology. Research interests focus on video-based monitoring systems for clinical and agricultural environments, including premature infant discomfort detection and smart livestock management. Key methodologies involve deep learning, multi-object tracking, and sensor fusion techniques applied to real-world healthcare and farming challenges. Recent work demonstrates strong translational impact through partnerships with clinical and agricultural stakeholders. Publications reveal evolving expertise from foundational work in convex optimization and GPU computing (2011-2015) toward applied computer vision solutions in medical diagnostics and precision farming (2017-2025). Current research emphasizes practical implementations like pig pose estimation systems and breast MRI segmentation tools with direct clinical applications. Professional activities include multiple conference presentations on neonatal monitoring systems and press coverage of agricultural technology implementations. The researcher actively contributes to TU/e's Sustainable Development Goals initiatives, particularly in healthcare technology advancement. Supervision activities and grant details are not explicitly documented in available materials, though collaborative project involvement is evident through multi-institutional publications and the completed EU-funded project 'Advancing Smart Optical Imaging and Sensing for Health' (2016-2019).

Lissa MelisView profile

Assistant Professor

• Operations Research
• Urban Transport Logistics
• Mobility-as-a-Service
• +3 more

Lissa Melis is an Assistant Professor in Operations Research and Operations Management at the Department of QE Operations Research within the School of Business and Economics at Maastricht University. Her research focuses on heuristic algorithms for urban transport systems and the intersection of operations research with explainable AI. She holds a PhD from the University of Antwerp (Belgium), supported by an FWO Fellowship, and completed postdoctoral research at Penn State University in the USA with a President’s Postdoctoral Fellowship. Education: PhD in Applied Economic Sciences (Operations Research) from University of Antwerp FWO Fellowship recipient during PhD Postdoctoral Researcher at Penn State University (Civil and Environmental Engineering) BAEF (Belgian American Educational Foundation) Alumni Research Interests: Design and analysis of (meta)heuristics for transport problems Urban mobility systems and MaaS (Mobility-as-a-Service) Explainable AI (XAI) in decision-making systems Sustainable public transport integration Recent Work Trends: Recent publications explore transparency in AI explanations and optimizing transport networks. Earlier work addresses migration’s societal impacts, suggesting interdisciplinary engagement with sociological and environmental factors. Awards: President’s Postdoctoral Fellowship Program (USA) FWO Fellowship (Belgium) Teaching Roles: Course coordinator for Advanced Operations Research (Master’s) Operations Management for Business Analytics (Bachelor’s) Operations and Supply Chain Management (Business Engineering) Labs/Teams: Involved in Quantitative Economics research groups at Maastricht University focusing on urban systems optimization and AI ethics.

Jojanneke van der BeekView profile

Lecturer

• Educational Psychology
• Learning Disabilities (Dyslexia/Dyscalculia)
• Mathematics Education
• +3 more

Jojanneke van der Beek is a Lecturer at Utrecht University's Faculty of Social and Behavioural Sciences, affiliated with the Department of Development & Education of Youth in Diverse Societies. She teaches in the Bachelor's program in Pedagogical Sciences and Master's programs in Clinical Child, Family and Education Studies, and Educational Sciences: Learning in Interaction. Her work focuses on learning disorders like dyslexia and dyscalculia, emotion regulation in mathematics education, and gender differences in academic achievement. She serves as an orthopedagogical specialist, designs post-academic training programs, and conducts doctoral research titled 'Math and Emotion'. She co-developed the Rekenbelevingsschaal (RBS) assessment tool and the intervention protocol 'Wegwijs in dyslexie en dyscalculie'. Her research highlights psychosocial aspects of learning disabilities, emotion-competence relationships in math problem-solving, and practical interventions for educators. Media contributions include a 2014 article outlining dyscalculia detection strategies for primary schools.

Sanne AbelnView profile

Professor

• Artificial Intelligence
• Bioinformatics
• Genomics
• +7 more

Prof. Sanne Abeln is a Professor at Utrecht University's Faculty of Science, specializing in AI Technology for Life within the Biology department. Her research focuses on developing AI-driven methods to analyze complex biological data, particularly in genomics, proteomics, and cancer biology. She leads the AI for the Life Sciences group, addressing challenges in interpreting life science data through explainable AI and multi-omics integration. Her work spans protein aggregation mechanisms, cancer genomics, and biomarker discovery for neurodegenerative diseases. Key projects include quantifying structural variants in tumors and advancing fluid-based biomarkers using machine learning. Publications highlight interdisciplinary approaches, combining computational methods with experimental data to solve biological problems. Collaborations involve clinical and experimental teams to translate findings into diagnostic tools and therapeutic insights.

Maja DekovicView profile

Professor

• Developmental Psychology
• Child and Adolescent Development
• Parent-Child Relationships
• +5 more

Prof. Maja Dekovic is a Full Professor and Chair of the Department of Clinical Child and Family Studies at Utrecht University, within the Faculty of Social and Behavioural Sciences. She holds a PhD from Radboud University Nijmegen (1991) and has held academic positions at the University of Amsterdam (1998–2004) before joining Utrecht. Her research focuses on child and adolescent development, family dynamics, and evidence-based interventions. She leads the Utrecht Centre for Child and Adolescent Studies (CAS), part of Utrecht University’s Dynamics of Youth strategic theme. Key areas include normative and deviant development, family-based interventions, and cross-cultural parenting. Dekovic has coordinated the Research Master program in Development and Socialization in Childhood and Adolescence and supervised 22 PhD students (4 with cum laude distinctions). She is a Principal Investigator in the NWO Gravitation-funded Consortium of Individual Development (CID). Her work bridges research with societal impact through publications in Dutch journals and collaborations with national consortia addressing externalizing problems, child abuse, and bullying prevention. Education: MA from University of Zadar (1984), MA in Developmental Psychology from Radboud University (1987), PhD from Radboud University (1991). Research Interests: Parent-child relationships, intervention effectiveness, longitudinal methods, developmental psychopathology. Current projects include Rock and Water interventions, Home-Start evaluations, and meta-analyses on parenting and child outcomes. Awards: Lead PI in NWO Gravitation Programme CID (2012–2022), member of editorial boards for international journals.

• Biological Psychology
• Electrophysiology
• Decision-Making under Risk and Uncertainty
• +3 more

Kristel de Groot is a researcher at the Erasmus School of Economics and the Erasmus School of Social and Behavioural Sciences at Erasmus University Rotterdam. She specializes in biological psychology and electrophysiological correlates of decision-making under uncertain and risky conditions, utilizing the Erasmus Behavioural Laboratory. Additionally, she investigates the impact of disabilities on student well-being and academic performance, advocating for inclusive education. She coordinates the Erasmus Functional Impairment Studies (EFIS) longitudinal survey and maintains active roles in research and teaching. Her recent work spans sociodemographic disparities in mental health, impulsivity, and autism traits, with a focus on methodological rigor in behavioral experiments. She has contributed datasets like SMARVUS on statistics and mathematics anxieties. Her research integrates neuroscience, psychology, and educational theory to address both cognitive and practical challenges in decision-making and inclusivity. Notable scientific contributions include experimental studies on risk-taking behavior and longitudinal analyses of student well-being. She is active in disseminating findings through publications and coordinates EFIS projects across multiple platforms, including Facebook, Instagram, and Twitter.

C.J.M. (Cor) SuhreView profile

Researcher

• Educational Research
• Educational Psychology
• Teacher Education
• +7 more

Dr. C.J.M. (Cor) Suhre is a Research Associate in the Faculty of Behavioural and Social Sciences at the University of Groningen, specializing in Teaching and Teacher Education. With over 100 research outputs spanning more than a decade, Dr. Suhre maintains an active research profile in educational psychology and teacher development. Dr. Suhre's research interests focus on educational assessment, teacher education, school leadership, and cognitive development in learning contexts. Their work particularly examines formative assessment practices, logical reasoning development, distributed leadership in schools, and the relationship between school vision and teacher commitment. Recent research has explored the impact of explicit school vision on teacher commitment, formative assessment instruments in science education, and the influence of leadership on PhD students' sense of belonging in Kenyan universities. Analysis of Dr. Suhre's publication history reveals consistent contributions across multiple educational subfields, with particular emphasis on practical applications for classroom instruction and school improvement. The research demonstrates strong methodological diversity, incorporating qualitative, quantitative, and mixed-methods approaches to address complex educational challenges. Best paper award (2017) Dr. Suhre actively contributes to the academic community through editorial work and peer review for journals including Learning Environments Research, Studies in Educational Evaluation, and Learning and Individual Differences. Their scholarly network includes collaborations with researchers across multiple institutions, particularly within the Dutch educational research community.

• Operations Management
• Operations Research & Management Science
• Logistics Optimization
• +4 more

Alexander Hübl is a Lecturer at the University of Groningen's Faculty of Science and Engineering, part of the Engineering Systems and Design (ESD) Group within the Engineering and Technology Institute Groningen. He holds additional roles such as Member of the Board of Examiners for Engineering and previously served as an Assistant Professor at Vienna University of Economics and Business and a Senior Researcher at the FH OÖ Research and Development GmbH. He is also a self-employed logistics and production optimization consultant (prodopt.at) and has volunteered as President of the Upper Austrian Taekwondo Federation since 2015. His education includes a PhD in Management with a focus on Logistics and Operations Management from the University of Vienna (2010–2015), supervised by Prof. Hartl. Earlier, he earned an MSc in Logistics Management from the University of Växjö, Sweden, and a BSc in Supply Chain Management. He also holds a Dipl. Ing. (FH) in Production and Management from the University of Applied Sciences Upper Austria, complemented by a technical college degree in Power Engineering and Power Electronics. Dr. Hübl’s research interests center on hybrid modeling, discrete-event simulation, and optimization techniques applied to production and supply chain systems. He explores topics like preventive maintenance scheduling, vehicle routing, and capacity management in industries such as automotive, retail, and transportation. His work emphasizes practical solutions for operational efficiency, resilience, and sustainability, leveraging stochastic processes and machine learning integration. His articles (2009–2024) highlight trends in hybrid modeling frameworks addressing complex systems, including railway networks, distribution centers, and manufacturing plants. He also focuses on educational applications of simulation in logistics and production. His consultancy and research roles indicate expertise in bridging academic theory with industrial practice. As an advisor, he has guided bachelor’s and master’s theses in PMT and OMT programs. His research group at FH OÖ managed four personnel and focused on supply chain planning methodologies. He contributes to labs/teams like the ESD Group and Engineering and Technology Institute Groningen, continuing his prior work in the FH OÖ Research Group.