Find Academic Supervisors

Gerald JonkerView profile

Lecturer

• Education
• Chemical Engineering
• Sustainable Design
• +4 more

Dr. Gerald Jonker is a Lecturer at the Faculty of Science and Engineering (FSE) at the University of Groningen. He serves as Head of the Industrial Engineering Systems group and Programme Director of the Bachelor of Industrial Engineering and Management (IEM). His roles include leading curriculum reforms, promoting sustainable design education, and advancing internationalization strategies. He holds a PhD in Chemical Engineering (1999) and has extensive experience in both academia and consultancy. Educationally, his focus spans academic leadership, engineering pedagogy, and sustainable development. He has contributed to initiatives such as the FSE Vision on Learning and Teaching ('Experts Crossing Borders') and the International Classroom project. His teaching includes courses like 'Sustainability for Engineers' and 'Research Methodology' at both bachelor and master levels. Research interests center on engineering design methodology, sustainable design practices, and innovation in technical education. He has authored books like Engineering for Sustainability: A Practical Guide and peer-reviewed publications in chemical engineering and education innovation. His work bridges academic research and practical applications, particularly in product technology and process optimization. Leadership roles include chairing the USSE Board and participating in international educational collaborations (e.g., U4 conference, ENLIGHT network). He has supervised numerous student projects and remains active in educational policy advising at the university level.

Laura BallatoView profile

Lecturer

• Developmental Psychology
• Coaching
• Intercultural Competence
• +3 more

Laura Ballato is a Lecturer and Coordinator of the Buddy Project & Study Abroad Minor Programme at the University of Groningen’s Faculty of Behavioural and Social Sciences. She specializes in Developmental Psychology, Coaching, and Intercultural Competence, with expertise in Dynamic System methods and Longitudinal Research. Her work focuses on adolescent behavior, risk-taking, and social interactions. Research interests include applying computational models (e.g., agent-based systems) to study developmental processes. She has published on topics like friendship dynamics and risk behaviors during adolescence, using dynamic systems theory to analyze behavioral patterns. Ballato also maintains an ancillary practice as an ACT therapist and coach through her private practice, lauraballato.com. She holds a PhD in Developmental Psychology, as evidenced by her 2012 thesis on friendship interactions and risk behaviors.

Catherine RigolletView profile

Assistant Professor

• Physics
• Nuclear Physics
• Applied Physics
• +4 more

Catherine Rigollet is an Assistant Professor/Lecturer at the University of Groningen, affiliated with the Faculty of Science and Engineering. She specializes in experimental nuclear physics, focusing on topics such as nuclear reactions, storage ring techniques, and neutron capture studies. Her work often involves collaborations with international teams like the R3B Collaboration at FAIR and EXL Collaboration. Research interests include nuclear structure, isotopic cross-section analysis, and applications to astrophysical processes. She contributes to the design and optimization of advanced detectors, such as the NeuLAND neutron spectrometer. Her publications span experimental methodologies, precision measurements in nuclear systems, and theoretical interpretations of nuclear phenomena. Teaching responsibilities include courses on nuclear energy, plasma physics, and nuclear astrophysics. She is part of the X-Lab and PAM — Lectures Team 1 within the Faculty, emphasizing hands-on research and interdisciplinary collaboration.

Siewert Jan MarrinkView profile

Professor

• Molecular Dynamics
• Biomembrane Simulations
• Coarse-Grained Modeling
• +4 more

Siewert Jan Marrink is a Professor of Molecular Dynamics at the University of Groningen's Faculty of Science and Engineering. He holds a prominent position in the international computational biology community, particularly known for developing the MARTINI coarse-grained molecular modeling tool. His research focuses on biomembrane simulations, lipid bilayers, and protein-membrane interactions, with significant contributions to understanding membrane fusion, protein oligomerization, and membrane domain formation. Marrink's research interests center on computational approaches to biomolecular systems, with particular emphasis on coarse-grained modeling techniques that balance computational efficiency with chemical accuracy. His MARTINI force field has revolutionized the field of membrane biology by enabling large-scale simulations of complex biological systems that would be computationally infeasible with all-atom models. His work bridges computational chemistry, biophysics, and cell biology, providing insights into fundamental biological processes at the molecular level. Analysis of Marrink's recent publications reveals a strong focus on advancing computational methodologies while applying them to biologically significant problems. His work spans from fundamental force field development (GōMartini 3) to applications in virology, mitochondrial biology, kinase regulation, and membrane protein function. A consistent theme is the development and application of coarse-grained models to study large biomolecular systems and complex biological phenomena that require long simulation timescales. KNAW Membership - Royal Netherlands Academy of Arts and Sciences (2023) ERC Advanced Grant (2022) Honorary Doctorate from University Polytechnics of Bucharest (2020) ERC Advanced Grant (2015) Marrink has supervised 28 research projects and actively participates in major collaborative research initiatives, including NWO Summit grants for fundamental research into the molecular basis of life and Dutch Research Agenda funding for nanomedicine applications. He organizes the biennial MARTINI workshops, which have become a cornerstone event for the coarse-grained modeling community, fostering international collaboration and methodological advancement. As leader of the MARTINI research group, Marrink directs a team focused on developing and applying coarse-grained molecular dynamics techniques. His group collaborates extensively with experimentalists worldwide, creating a synergistic approach where computational predictions guide experiments and experimental findings refine computational models. The MARTINI software framework developed by his team has become a standard tool used globally across multiple disciplines beyond membrane biology.

• Artificial Intelligence
• Optimization
• Agent-Based Simulation
• +5 more

N. Yorke-Smith is a Professor in the Algorithmics department at Delft University of Technology's Faculty of Electrical Engineering, Mathematics and Computer Science. He leads the STAR Lab, which focuses on integrating machine intelligence with human decision-making processes in complex socio-technical systems. His research spans data-driven optimization, agent-based simulation for urban policy analysis, and uncertainty-aware AI algorithms. Key areas of research include: Combinatorial optimization with real-world applications in logistics and energy systems Agent-based models for urban housing markets and policy evaluation Epistemic uncertainty frameworks for reliable AI decision-making Machine learning integration with constraint satisfaction problems Recent work highlights include developing epistemic Bellman operators for reinforcement learning, evaluating circular economy policies in Amsterdam, and advancing online learning techniques for optimization heuristics. His research has been supported through major grants from AiNed, NWO, and EU Horizon programs. Advising focuses on complex scheduling problems, AI for urban systems, and optimization under uncertainty. Notable projects include the EU-funded TULIPS initiative for sustainable transport and the Epistemic AI framework development. STAR Lab collaborates with municipalities, industries, and international partners to translate theoretical advances into practical societal impact.

• Game Theory
• Decision Theory
• Conflict and Cooperation
• +3 more

Zsombor Méder is an Assistant Professor at the University of Groningen's Faculty of Economics and Business, specializing in micro-economics, industrial organization, and game theory. He holds a PhD and focuses on decision theory, conflict resolution, and agent-based simulations. His research explores cooperative mechanisms, strategic behavior, and public health policy, with notable contributions to understanding large-scale cooperation dynamics and time-inconsistent consumer behavior. Education: PhD in Economics (specific details not provided in the text). Teaching includes courses on Matrix Analysis, Data Science & Machine Learning, and Econometrics. Office: Nettelbosje 2, Room 730; contact via z.z.meder@rug.nl or +31 6 5001 9843. Research interests include game theory applications in conflict scenarios, agent-based modeling of social dilemmas, and evolutionary dynamics of cooperation. Recent work addresses genomic surveillance strategies and universal cooperation frameworks. His publications span interdisciplinary topics from political conflict analysis to behavioral economics. No scientific awards are explicitly mentioned. Teaching and advising activities include weekly office hours and contributions to academic programs in economics and data science.

• International Monetary Economics
• Foreign Exchange Rate Determination
• Financial Markets Risk
• +3 more

Casper G. de Vries is a Professor holding the Witteveen Chair of Monetary Economics at the Erasmus School of Economics , Erasmus University Rotterdam. He is affiliated with the Tinbergen Institute and serves on the Scientific Council for the Dutch Government (WRR), advising two Dutch pension funds. His career includes positions at Purdue University, Texas A&M University, and KU Leuven, with visiting roles at institutions like Chapman University. Education: PhD in Economics, Purdue University Postdoctoral positions at Texas A&M University and KU Leuven Research Interests: International monetary policy and exchange rate dynamics Financial risk analysis using extreme value theory Applied game theory in lobbying and auction design Systemic risk in financial systems His work bridges theoretical frameworks with empirical analysis, emphasizing extreme event modeling and policy implications. Articles: Over 50 peer-reviewed publications in top journals (e.g., Journal of Economic Theory , Journal of Econometrics , American Economic Review ). Recent work focuses on systemic risk diversification, internet auction dynamics, and policy-relevant financial stability issues. Scientific Awards: Fellow of the Tinbergen Institute Teaching and Roles: PhD courses on monetary economics at the Tinbergen Institute Former Vice Dean of Research and Education at Erasmus School of Economics Advisor to Dutch socio-economic councils (SER) Labs/Teams: Active in the Erasmus School of Economics' research groups on financial markets and monetary policy.

• Computer Science
• Big Data
• Distributed Computing
• +6 more

Eliya Buyukkaya is a researcher active in the fields of Computer Science , Big Data , and Distributed Computing . Their work focuses on scalable systems, environmental informatics, and data compression techniques. 2025: Crop growth simulations using big data 2021: Bit Plane Slicing for clustering 2018: Video streaming optimization for games 2017: Clustering anomaly detection 2015: Cloud resource selection for HPC Research spans Big Data Analytics , Collaborative Algorithms , and Latency Optimization , emphasizing scalability and efficiency. Their work impacts Environmental Informatics , Game Networking , and High-Performance Computing . Collaborations include experts in Earth Observation and Computer Science , with publications in top-tier venues like Computers and Electronics in Agriculture and PLoS ONE .

• Systems Biology
• Synthetic Biology
• Machine Learning in Biology
• +5 more

Robert Smith is a researcher specializing in Systems and Synthetic Biology with a focus on integrating computational approaches with biological systems. He holds a PhD and serves as a faculty member with research and teaching responsibilities, evidenced by his role as Co-promotor for PhD candidates. His research spans multiple cutting-edge areas: Systems Biology and computational modeling of biological processes Synthetic biology applications, particularly in optogenetics and phytochrome research Integration of machine learning with mechanistic biological modeling Development of safety frameworks for biological diagnostics Metabolic engineering and model reduction techniques Smith's recent publication trend shows increasing interdisciplinary work combining AI with biological systems. His 2024-2021 publications reveal expertise across theoretical modeling, medical diagnostics, and educational methodology, with significant citation impact particularly in metabolic engineering research. As an academic mentor, Smith serves as Co-promotor for PhD research on plant pathogenic fungi infection structures, guiding next-generation researchers in systems biology approaches. His educational contributions include developing research-driven curricula that bridge theoretical concepts with practical laboratory applications. Current research activities include active leadership on the project 'Systems biology analysis of infection structure development in a plant pathogenic fungus' (since November 2023), building on previous work in phytochrome manipulation through synthetic biology (2014-2016).

• Computational Mechanics
• Metal Forming
• Optimization
• +3 more

Gosse Tjipke Havinga serves as an Assistant Professor in Nonlinear Solid Mechanics at the University of Twente's Faculty of Engineering Technology. His research spans computational mechanics with emphasis on metal forming, optimization, and simulation techniques, leveraging advanced mathematical modeling for industrial applications. Research interests focus on computational homogenization , metal forming processes , and model order reduction . His work integrates asymptotic methods for magnetic composites, radial basis function interpolation for nonlinear simulations, and shell finite element modeling for sheet rolling instabilities. Recent publications demonstrate strong interdisciplinary connections between mechanical engineering and materials science. Publications since 2022 reveal a concentrated focus on Efficient thermomechanical modeling for additive manufacturing Homogenization techniques for magnetic composites Real-time optimization of metal forming processes with consistent application of numerical methods to solve industrial-scale engineering challenges. Professional activities include supervision of doctoral research and industry collaboration through invited talks on smart manufacturing, such as the 2020 presentation 'Smart factories: improving process models using real-time data'. His laboratory work centers on developing computational frameworks for Large-scale metal additive manufacturing Sheet metal forming simulations Magnetic property prediction in composites with practical applications in industrial production environments.

Min WuView profile

Assistant Professor

• Photoacoustic Imaging
• Ultrasound Imaging
• Biomedical Engineering
• +7 more

Min Wu is an Assistant Professor in the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), where she conducts research in the Photoacoustics and Ultrasound Laboratory. Her work focuses on advancing biomedical imaging technologies, particularly in photoacoustic and ultrasound imaging, with applications in tissue characterization and disease diagnosis. Assistant Professor, Biomedical Engineering, TU/e Research in Photoacoustic and Ultrasound Imaging Contributor to UN Sustainable Development Goals in health Active publication record from 2019 to 2025 Her research interests span photoacoustic imaging, ultrasound signal processing, biomedical simulations, and transducer design. She investigates methods to enhance imaging depth, resolution, and signal-to-noise ratio in complex biological tissues. Her work integrates computational modeling with experimental validation, particularly in cartilage and vascular imaging. The recent articles demonstrate a strong trend toward improving imaging fidelity in biomedical systems. Her research emphasizes signal enhancement , realistic simulation environments , and clinical translation of imaging technologies . Topics include dichroism-sensitive imaging, multi-aperture encoding, and cartilage damage assessment, indicating a focus on both hardware and algorithmic innovations in medical imaging. Min Wu has contributed to professional commentary in press and media, particularly related to advancements in ultrasound simulation and imaging technologies. While no formal awards are listed, her work has been recognized through media coverage and citations. She advises students and collaborates on research projects, as indicated by her involvement in 13 supervised works. She teaches courses such as Advanced Topics in Ultrasound Imaging and Blood Oxygenation Imaging with Sound and Light , contributing to graduate and undergraduate education in biomedical engineering. Her lab, the Photoacoustics and Ultrasound Laboratory, serves as a hub for interdisciplinary research in biomedical imaging.

Guang HuView profile

Assistant Professor

• Machine Learning-Assisted Modeling
• Multi-Scale Modeling
• Sustainable Energy Applications
• +7 more

Guang Hu is an Assistant Professor in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e), affiliated with the Energy Technology group, EIRES, and EAISI. His research integrates computational modeling, machine learning, and sustainable energy systems to address urban environmental challenges. Ph.D. in Nuclear and New Energy Technology, Tsinghua University (2019) Postdoctoral Researcher, Karlsruhe Institute of Technology, Germany Researcher, Paul Scherrer Institut (PSI), Switzerland Guang Hu's research focuses on machine learning-assisted modeling , multi-scale modeling , and sustainable energy applications , particularly in thermal and nuclear energy systems . His work aims to enhance urban resilience and energy efficiency through data-driven and physics-informed computational methods. He is actively involved in advancing solutions for nuclear waste management, solar energy integration in aging urban environments, and thermal-hydraulic process optimization. The recent publications highlight a strong trend in applying machine learning and surrogate modeling to complex energy systems, especially in nuclear waste management and urban solar energy . His work bridges computational efficiency with real-world sustainability challenges , emphasizing practical applications in full-scale experiments and geochemical processes . The interdisciplinary nature of his research spans nuclear engineering , urban sustainability , and artificial intelligence . Scientific Awards and Recognition: Ph.D. with distinction, Tsinghua University Active reviewer for leading journals in computational modeling and energy Contributor to UN Sustainable Development Goals (SDGs) in clean energy and sustainable cities Guang Hu actively mentors students and collaborates internationally, though specific advisees are not listed. He has participated in significant research collaborations with institutions in Germany and Switzerland and contributes to major conferences such as ICONE and EU PVSEC. His work is supported by ongoing research activities within TU/e’s energy and AI institutes. While specific grants are not detailed, his funding is inferred through sustained research output and international partnerships. He is associated with research initiatives including digital twin development for nuclear waste, surrogate modeling for geochemical processes, and performance assessment of solar systems in Dutch urban contexts. These efforts are part of broader teams at TU/e focused on energy transition, AI for engineering, and sustainable infrastructure.

Karline SoetaertView profile

Professor

• Marine Biogeochemistry
• Environmental Modelling
• Hydrodynamics
• +5 more

Karline Soetaert is a Professor at Utrecht University's Geosciences Department and a Research Leader at the Royal Netherlands Institute for Sea Research (NIOZ). Her work bridges biogeochemistry, ecology, and computational science to model marine and estuarine systems. PhD in Biology (1988), Ghent University Master in Zoology (1983) and Computer Sciences (1985), Ghent University Her research focuses on sediment-water interactions, environmental modeling , and open-source software development , particularly using R. She investigates impacts of human activities like pulse fishing and offshore wind farms on marine ecosystems through hydrodynamic models and field observations . Recent publications highlight biogeochemical software integration and macroalgal bloom prediction . She advocates for open science , creating 20+ R-packages for oceanographic data analysis. Scientific Awards: Member, Academia Europaea (2024) She teaches environmental modeling at Ghent University and leads projects such as Greenland Fjords Ecosystem Modeling and North Sea Carbon Cycling . Her work emphasizes reproducible research through R Markdown and literate programming .

Chaobo ZhangView profile

Researcher

• Building Physics
• Smart Building Energy Management
• Artificial Intelligence in Building Systems
• +5 more

Chaobo Zhang is a postdoctoral researcher at the Eindhoven University of Technology, specializing in fast building performance simulation and smart building energy management. He belongs to the Building Performance Group within the Department of the Built Environment. Education: Bachelor in Heating, Ventilation and Air Conditioning, Harbin Institute of Technology (2017) PhD in Refrigeration and Cryogenic Engineering, Zhejiang University (2022) His research integrates artificial intelligence technologies into building systems to enhance energy efficiency and fault detection. Key areas include generative pre-trained transformers (GPT) for energy load prediction, convolutional neural networks for computational fluid dynamics, and domain-specific large language models for HVAC fault diagnosis. The 15 most recent publications highlight trends in AI-driven building energy management, focusing on technologies like graph convolutional networks for uncertainty quantification, hybrid data-driven physics-based cooling demand models, and self-attention variational autoencoders for digital twin parameter imputation. His work addresses challenges such as data imbalance, federated learning for data silos, and real-time anomaly detection. Scientific Awards: 2020 Best Paper Award, Energy and Built Environment Chaobo collaborates internationally and contributes to UN Sustainable Development Goals through energy-efficient building technologies. His expertise spans fault detection, machine learning, and computational optimization in building systems.

Alexander NolteView profile

Assistant Professor

• Software Engineering
• Human-Computer Interaction
• Open Source Software
• +7 more

Alexander Nolte is an Assistant Professor at the Mathematics and Computer Science school of Eindhoven University of Technology and an Adjunct Associate Professor at Carnegie Mellon University since 2020. His work bridges software engineering , human-computer interaction , and collaborative innovation , with a focus on hackathons , open source , and business process management . Key research themes include: Hackathon Impact : Analyzing collaboration patterns, creativity, and project sustainability in software startups and open source. Process Analytics : Developing tools for prescriptive monitoring and explainable AI systems. Acoustic Software : Building open-source platforms for room acoustics research. Diversity Initiatives : Creating inclusive environments in technical teams. His 15 most recent publications highlight trends in large language models , collaborative event design , and software diversity . Awards include multiple best paper and demo awards from 2021 to 2024. Nolte actively contributes to scientific datasets and collaborates on interdisciplinary projects, particularly in open-source room acoustics software with TU/e and Zenodo. He teaches Human-Computer Interaction and Software Development for Engineers , emphasizing practical, event-driven learning.