جستجوی استاد راهنمای دانشگاهی

• Wildlife Ecology
• Animal Behavior
• Conservation Biology
• +۳ مورد دیگر

Henjo de Knegt is a Researcher in the Department of Wildlife Ecology and Conservation at Wageningen University & Research. His work focuses on animal movement ecology, conservation biology, and the application of technology in ecological studies. He has contributed to projects on poacher detection using animal movement patterns, UAV-based anti-predator strategies in African savannas, and pest-control solutions inspired by insect behavior. De Knegt co-supervises multiple PhD candidates, including studies on collective decision-making in wildlife, anti-predator strategies, and sensor technology for livestock health monitoring. Research interests include stopover sites, golden jackals, quagga behavior, and the integration of sensor technology with ecological research. His recent publications explore agent-based models for animal group dynamics, edge computing in wildlife tracking, and flight activity in pied flycatchers. Collaborations span institutions globally, addressing topics like pest moth escape maneuvers and the impacts of environmental stressors on animal behavior. De Knegt’s work bridges theoretical ecology with applied solutions, such as using animal behavior to improve conservation strategies and agricultural pest management. He has been involved in datasets related to poacher detection and elephant-mediated ecological cascades, emphasizing interdisciplinary approaches.

• Statistical Genetics
• Graphical Models
• Genomics
• +۵ مورد دیگر

Pariya Behrouzi is an Assistant Professor in the Department of Mathematical and Statistical Methods - Biometris at Wageningen University & Research. She specializes in developing statistical methodologies with applications in genetics, genomics, and nutrition science. Her research focuses on graphical models, copula theory, and Bayesian approaches to analyze complex biological systems. Behrouzi leads or collaborates on projects such as SignAphy (plant signaling dynamics) and Sensing Age (epigenetic aging studies). She co-developed the netgwas R package for network-based genome-wide association studies. Her work bridges statistical theory with practical applications in agriculture, nutrition, and computational biology. Education: PhD in Statistics (as indicated by title) Key Research Tools: Copula graphical models, spatial statistics, and Bayesian networks Current Projects: Multi-omics network reconstruction, resilience in lettuce crops, and microbiota systems analysis Her recent publications explore topics like meat analogue texture optimization, telomere length dietary correlations, and plant disease resistance mechanisms. Behrouzi advises four PhD candidates and collaborates with international teams on interdisciplinary research.

• Climate Change Adaptation
• Climate Policy
• Environmental Governance
• +۴ مورد دیگر

Robbert Biesbroek is a Personal Professor at the Public Administration and Policy Department of Wageningen University & Research, part of the Wageningen School of Social Sciences (WASS). His work focuses on climate change adaptation, environmental policy, and governance, with a particular emphasis on bridging theory and practice. He has received international recognition, including the 2022 Gulbenkian and North-South Prizes (as an IPCC author) and the Lasswell Prize for Policy Sciences. His research explores adaptation pathways, policy integration, and the role of machine learning in tracking climate action. Biesbroek advises multiple PhD candidates on topics like climate adaptation governance, rural resilience, and public space management. He actively contributes to global assessments, such as the European Climate Change Risk Assessment (EUCRA) and the IPCC’s Sixth Assessment Report. His editorial roles include Springer’s peer-review processes and the World Adaptation Science Programme (WASP). Recent work highlights include evaluating climate services, analyzing adaptation progress via machine learning, and addressing governance gaps between policy and implementation. His awards reflect both academic excellence and impactful contributions to global climate efforts.

• Food Engineering
• Packaging Materials
• Sustainability
• +۴ مورد دیگر

Dr. Deniz Turan-Kunter is an Assistant Professor in Food Quality and Design at Wageningen University & Research. She holds a B.Sc. and Ph.D. in Food Engineering from Istanbul Technical University, with a postdoctoral focus on digital twin applications for fresh produce cold chains. Her research bridges food packaging, smart supply chains, and sustainability, addressing food waste reduction through innovative materials and data-driven models. She leads projects on ventilated packaging design for strawberries and physics-based digital twins for refrigerated logistics. Education: B.Sc. (Distinction) and Ph.D. in Food Engineering from Istanbul Technical University (2010 and 2015). Her Ph.D. work on thermosensitive polymers earned the TUBITAK grant and Nestlé Young Scientist Award. She specializes in macromolecular chemistry, machine learning, and sustainable packaging solutions. Research Interests: Food packaging materials, digital twin technology, cold chain optimization, and strawberry quality preservation. She explores machine learning for predictive analytics in food systems and edible coatings from coffee by-products. Scientific Contributions: Over 15 peer-reviewed articles, including work on hygrothermal modeling, ventilated packaging, and smart materials. Key projects include optimizing refrigerated container shipments and developing edible coatings from cascara. Teaching: Coordinates MSc thesis and internship supervision in Food Quality and Design, including courses like Food Data Science and Packaging Design. She integrates industry-relevant challenges into academic training. Labs/Teams: Active in Wageningen’s Food Quality and Design division, collaborating on digital twin applications and sustainable packaging innovations.

• Metabolomics
• Mass Spectrometry
• Gene Cluster Analysis
• +۳ مورد دیگر

Justin van der Hooft is an EPS Assistant Professor in Bioinformatics (BIF) at Wageningen University & Research. His research focuses on metabolomics, mass spectrometry, and computational approaches to natural product discovery. He leads efforts in gene cluster analysis, molecular networking, and AI-driven data integration. His work emphasizes open science and collaboration, as highlighted by the Lighthouse Award 2022 and contributions to tools like antiSMASH and MIBiG. Research interests include advancing computational methods for metabolite identification, optimizing mass spectrometry workflows, and leveraging AI for natural product discovery. Key projects involve linking biosynthetic gene clusters to metabolites, developing scalable data platforms, and exploring plant and microbial specialized metabolomes. Recent articles highlight advancements in mass spectrometry data patterns, AI integration, and community-driven curation of biosynthetic gene clusters. His contributions span over 130 publications, emphasizing metabolomics, gene cluster analysis, and computational biology. Advising: Co-promotor for PhD students in metabolomics, bioinformatics, and microbial ecology projects. Grants/Projects: Active in food safety analysis, natural product discovery, and integrative omics studies. Labs/Teams: Collaborates with global networks on antiSMASH, MIBiG, and molecular networking initiatives.

• Cardiovascular Imaging
• Coronary Artery Disease
• Medical Imaging Technologies
• +۳ مورد دیگر

Adriaan Coenen is a Researcher at Erasmus MC, affiliated with the Department of Radiology & Nuclear Medicine. His research focuses on cardiovascular imaging, particularly in coronary artery disease and diagnostic techniques such as computed tomography (CT). He completed his doctoral thesis in 2023 on CT-derived fractional flow reserve and myocardial perfusion imaging. His work emphasizes quantitative imaging methods, machine learning applications, and the integration of advanced imaging technologies for clinical decision-making. Collaborations span international teams in cardiology and imaging sciences. Key research interests include coronary artery stenosis, atherosclerosis, and the development of non-invasive diagnostic tools. His recent publications highlight advancements in CT perfusion imaging, machine learning-driven diagnostic performance, and lipid-rich plaque characterization using near-infrared spectroscopy. These studies aim to improve accuracy and efficiency in diagnosing cardiovascular conditions.

Gerald Corzo Perezمشاهده پروفایل

مدرس

• Hybrid Machine Learning
• Process-Based Modelling
• Spatiotemporal Analysis
• +۵ مورد دیگر

Gerald Corzo Perez is a Lecturer and researcher specializing in hybrid machine learning and process-based modeling at IHE Delft Institute for Water Education. His work focuses on spatiotemporal analysis of extreme climate events, hydrological modeling, and AI applications in water resources management. He has coordinated major projects including the Dominican Republic's national climate change atlas and contributed to drought risk assessments in Central America and Ethiopia. His research integrates remote sensing, citizen science, and social media data for disaster detection and management. Research Interests: Machine learning for hydrological forecasting Climatic impacts on water resources Spatiotemporal drought dynamics Natural language processing for environmental monitoring Reservoir optimization under climate change Key Achievements: Recipient of the 2012 Tison Award (IAHS) Lead developer of the 'intelligent serious game' for citizen science data collection Authored over 40 high-impact journal publications and multiple book chapters Collaborations: Maintains a global network through projects in Vietnam, Colombia, Ecuador, Nicaragua, and Kazakhstan. Active in EU-funded initiatives like the WATCH program and the Hatillo Reservoir optimization project.

Frans Cruijssenمشاهده پروفایل

استاد

• Sustainable Development
• Food Security
• Logistics Sustainability
• +۴ مورد دیگر

Prof. Frans Cruijssen is a Professor of Analytics for Sustainable Development at Tilburg University's Tilburg School of Economics and Management (TiSEM), leading the Zero Hunger Lab. His research focuses on food security, sustainable logistics, and AI applications in supply chains. He bridges academia and industry through applied research, addressing food waste reduction, horizontal collaboration in logistics, and AI-driven solutions. Academically, he holds a TS Economics and Management degree and has contributed to over 40 peer-reviewed publications. Key projects include the 'Warehousification' study on Dutch warehouses, the Zero Waste initiative, and collaborations on coalition formation dynamics in transport sectors. His courses include the Improving Society Lab for EOR and Professional Business Analytics Skills. Research highlights involve optimizing food bank networks, forecasting malnutrition using machine learning, and analyzing coalition trust mechanisms. He leads initiatives like the Tilburg Initiative for Future Logistics (TIFL) and the Digital Dignity Initiative to enhance food system resilience. His work emphasizes practical solutions for sustainability challenges in logistics and food systems.

• Statistics
• Data Science
• Biostatistics
• +۳ مورد دیگر

Prof. Katrijn Van Deun is a Full Professor in the Department of Methodology at the Tilburg School of Social and Behavioral Sciences, Tilburg University. Her research focuses on statistical methodology, data science, and their applications in health and behavioral sciences. She leads projects such as the WaTCh study, exploring determinants of quality of life in thyroid cancer patients. Her work bridges methodological innovation with practical applications in fields like HR analytics, rheumatoid arthritis treatment, and biostatistics. Key research interests include multivariate analysis, sparse PCA, meta-analyses, and health outcomes research. She has published extensively on topics such as structural equation modeling, infection risks in rheumatoid arthritis, and predictive analytics in HRM. Her contributions address complex data challenges, integrating high-dimensional data with traditional methodologies to uncover meaningful patterns. Prof. Van Deun collaborates across disciplines, involving teams in psychology, medicine, and computer science. Her work emphasizes methodological rigor and translational research, aiming to improve clinical decision-making and patient outcomes. She is actively involved in developing statistical tools and frameworks to handle big data and interdisciplinary research challenges.

I.J. de Jongمشاهده پروفایل

استاد

• Urologic Oncology
• Reconstructive Urologic Surgery
• Molecular Imaging
• +۳ مورد دیگر

Prof. I.J. de Jong is a Professor in Urology and Head of the Department of Urology at the University of Groningen's Faculty of Medical Sciences. He holds a visiting professorship at St. Petersburg Pavlov First Saint Petersburg State Medical University. His expertise spans Urologic Oncology, Reconstructive Urologic Surgery, and Molecular Imaging, with a focus on prostate cancer research and clinical advancements. He has contributed to over 170 publications, including studies on radium-223 therapy, deep learning models for prostate cancer prediction, and imaging techniques like PSMA PET/CT. His work emphasizes translational research and methodology development in urology. Education includes a University Teaching Qualification from the University of Groningen (2014). He leads the Personalized Cancer Treatment (PCT) and BRIDGE research groups, focusing on clinical trials (e.g., RECOVER, PERYTON) and innovative imaging applications. Media coverage highlights his contributions to prostate cancer management and surgical advancements.

Claudine Lamothمشاهده پروفایل

استاد

• Healthy Aging
• Wearable Technology
• Movement Analysis
• +۶ مورد دیگر

Prof. Claudine Lamoth is Professor of Movement Analysis & Smart Technology in Aging at the University of Groningen's Faculty of Medical Sciences. She leads the Centre of Human Movement Sciences and serves as Program Leader for the Digital Healthcare program at PRECISION Research Institute. Her work focuses on integrating wearable technology with data science to improve aging-related health outcomes. Lamoth holds adjunct roles as Section Editor for the Journal of Human Movement Science and chairs the Sensing Monitoring workgroup at UMCG. Education includes a Master's (cum laude) and PhD in Human Movement Sciences from VU University Amsterdam. Her career spans clinical physical therapy (1986-2003) and academic roles including Associate Professor (2014-2020) and current professorship since 2020. Key research areas include gait analysis, frailty assessment, and smart healthcare technologies. Recent research emphasizes machine learning applications for mobility analysis, biomarker monitoring via wearable devices, and interdisciplinary approaches to healthy aging. Her work addresses UN SDGs related to healthy aging and sustainable cities through initiatives like Healthy Living as a Service (HLAS.nl), promoting lifestyle interventions using smart technology. Key Awards: 2018 Teacher of the Year, 2013 Best Presentation Award, 2022 ELSA Fellowship Leadership Roles: Scientific Director HTRIC (2023), General Director SPRINT (2021-2022) Collaborations span engineering, data science, and clinical medicine to develop innovative solutions for mobility impairments and chronic disease management.

Tolga Caskurluمشاهده پروفایل

استادیار

• Corporate Finance
• Patent Law
• Entrepreneurial Finance
• +۳ مورد دیگر

Tolga Caskurlu is Assistant Professor of Finance at the University of Amsterdam Business School. His research examines corporate finance interactions with patent law, M&A, and innovation. Current projects analyze how patent rights influence acquisition strategies and small firm R&D incentives. He holds a Ph.D. in Finance from University of Illinois Urbana-Champaign and previously worked at DuPont. Methodologies include machine learning analysis of patent lawsuits and instrumental variable approaches. Published in Journal of Finance and Journal of Financial Economics. Professional activities include program committees for EFA and FMA conferences. Teaches courses in entrepreneurial finance and corporate financial strategies.

• Explainable Artificial Intelligence
• Feature Selection
• Analytic Hierarchy Process
• +۳ مورد دیگر

Dr. Majeed Mohammadi is a Visiting Professor at the Faculty of Science, Department of Artificial Intelligence at Vrije Universiteit Amsterdam. He also holds visiting fellow roles at the Network Institute and Artificial Intelligence research groups within the same university. His research focuses on Explainable AI, feature selection, decision analysis, and sustainable urban mobility. Key methodologies include the Analytic Hierarchy Process, Quadratic Programming, and Game Theory applications. His recent work bridges transportation systems and AI through stakeholder engagement frameworks. He has published on causal explanation techniques (CAGE), high-order feature interaction detection, and fallacies in group decision-making processes. Collaborations span international teams addressing interdisciplinary challenges in AI explainability and decision science. His academic contributions include peer-reviewed articles in journals like Group Decision and Negotiation and conferences such as AAAI. Research outputs emphasize both theoretical advancements (e.g., Möbius representation algorithms) and practical applications in urban mobility and feature engineering.

Kevin Godin-Duboisمشاهده پروفایل

پژوهشگر

• Reinforcement Learning
• Human-AI Interaction
• Evolutionary Robotics
• +۳ مورد دیگر

Kevin Godin-Dubois is a Researcher at the Faculty of Science, Vrije Universiteit Amsterdam (VU), with affiliations to the Network Institute. His work focuses on advancing artificial intelligence (AI) through interdisciplinary research, particularly in reinforcement learning, human-AI interaction, and evolutionary robotics. He leads projects involving modular frameworks for AI experiments and benchmark generators for agent prototyping. Research Interests: His primary areas include reinforcement learning frameworks, human-AI collaboration systems, neuroevolutionary techniques, and embodied evolution in robotics. His work bridges theoretical AI advancements with practical applications in socially adept agents and modular system design. Recent Trends: His 2024-2025 publications emphasize modular frameworks (e.g., SHARPIE and AMaze), which enable scalable experimentation and benchmarking of AI agents. Earlier work (2017-2020) explored long-term evolutionary dynamics in artificial ecosystems and plant communities, showcasing adaptability in changing environments. Collaborations: Active in international workshops (e.g., ALIFE 2024) and open-source projects (ci-group/revolve2), emphasizing reproducibility and community-driven AI development.

Sebastian Kraulمشاهده پروفایل

استادیار

• Operations Research
• Healthcare Operations Management
• Scheduling Algorithms
• +۳ مورد دیگر

Sebastian Kraul is an Assistant Professor in the Department of Operations Analytics at the School of Business and Economics , Vrije Universiteit Amsterdam. He holds a PhD in Business and Economics from the University of Augsburg (2021) and has postdoctoral experience in Health Care Operations Management. His research focuses on Operations Research , Healthcare Operations Management , and Optimization Algorithms , with applications in healthcare scheduling, resource allocation, and machine learning integration in operational problems. He teaches courses such as Sustainable Management of Global Supply Chains . Education: PhD in Business and Economics, University of Augsburg (2021) Master's in Business Administration, RWTH Aachen University (2015) Bachelor's in Business and Economics, Technical University Dortmund (2013) Research interests include optimizing healthcare processes (e.g., sterilization, physician scheduling) and developing robust frameworks for resident scheduling. His work employs methods like GRASP, column generation, and machine learning to tackle operational challenges in healthcare systems. For instance, his 2023 study on stable annual scheduling uses prioritized training schedules to address uncertainty in medical residency programs. His publications highlight trends in healthcare operations optimization, emphasizing resilience, resource efficiency, and continuity of care. He has received the Dissertation Award of the GOR (2022) for his doctoral work. Dr. Kraul actively participates in peer review for journals like European Journal of Operational Research and Omega . He currently teaches Business Mathematics , Operations and Supply Chain Management , and Sustainable Management of Global Supply Chains .