Find Academic Supervisors

• Robotics
• Swarm Robotics
• Collective Decision Making
• +3 more

Eliseo Ferrante is an Assistant Professor at the Faculty of Science, Department of Artificial Intelligence, Vrije Universiteit Amsterdam. He is also affiliated with the Network Institute. His research focuses on swarm robotics, collective decision-making, and autonomous systems, contributing to UN Sustainable Development Goals. He teaches courses such as 'Learning Machines' and 'Collective Intelligence.' His research explores topics including robot swarms in challenging environments, evolutionary algorithms for adaptive robotics, and morphological evolution in robots. Key contributions include methods for robust swarming in GNSS-denied areas and optimized control strategies for evolvable morphologies. Dr. Ferrante has supervised 2 PhD theses and contributed to datasets on collective motion models and modular robotics. His work emphasizes practical applications of AI in robotics, with a focus on resilience and adaptability in complex systems.

Dennis MoekeView profile

Lecturer

• Patient Logistics
• Healthcare Logistics
• Data-driven Capacity Planning
• +4 more

Dennis Moeke is a Lecturer in Logistics and Alliances at HAN University of Applied Sciences, leading the Logistics and Alliances Lectorate. He holds a broad professional network spanning logistics, government, and academia, with a focus on healthcare logistics and sustainable urban development. His research addresses societal challenges such as affordable healthcare systems, smart logistics solutions, and livable cities through interdisciplinary collaboration. His expertise includes patient logistics, data-driven capacity planning, and optimization of healthcare processes. Key projects include the Healthy City Lab , exploring sustainable last-mile logistics in cities via two Living Labs (Campus Heijendaal and Buur & Zo), and the Living Labs Sustainable Supply Chain Management in Healthcare . He has secured significant funding, including a NWO grant (Project 439.18.457), to advance interdisciplinary research. Notable contributions include developing the Buur & Zo concept (home care concierge services) and optimizing hospital patient flows using process mining. He collaborates with organizations like Logistics Valley, Health Valley, CWZ Carinova, and Siza. His work emphasizes practical applications, translating academic insights into real-world tools for healthcare and logistics sectors. Publications span topics like home care scheduling optimization, sustainable urban logistics, and pandemic response logistics. He actively promotes the role of logistics in societal well-being through teaching and industry partnerships.

Islam S.M. KhalilView profile

Associate Professor

• Micro Robotics
• Healthcare Robotics
• Biomedical Engineering
• +3 more

Islam S.M. Khalil is an Associate Professor in Robotics and Mechatronics at the TechMed Centre. His research focuses on micro-robotics applications in healthcare, particularly developing millirobots for medical interventions like thrombus fragmentation and intravascular navigation. With an h-index of 24 and 2150 citations, he has contributed to 131 peer-reviewed publications. His work aligns with UN Sustainable Development Goals related to healthcare and well-being. Key Research Areas: Medical robotics, magnetic actuation, biomedical engineering Notable Projects: Wireless clot-busting millirobots, X-ray guided robotic clusters Media highlights include breakthroughs in navigating blood vessels using untethered robots. He actively participates in editorial roles for journals like IEEE Transactions on Robotics and Applied Physics Reviews.

Boudewijn van DongenView profile

Professor

• Process Mining
• Conformance Checking
• Business Process Management
• +3 more

Dr. Boudewijn van Dongen is a Full Professor at Eindhoven University of Technology's Department of Mathematics and Computer Science, chairing the Process Analytics group. His research focuses on conformance checking and process mining , particularly through alignment-based techniques. Develops ProM and CPN Tools frameworks Collaborates with Philips Research and Vanderlande Leads IEEE Task Force on Process Mining Research Interests : Specializes in aligning observed data with process models, addressing multi-case dependencies , privacy-aware mining , and stream processing . Project Highlights : • Strategic partnership with Philips on health data science • Logistics optimization with Vanderlande Industries • Foundational work in alignment theory and behavioral diagnostics

Ihor SmalView profile

Assistant Professor

• Image Analysis
• Smart Microscopy
• Artificial Intelligence
• +7 more

Ihor Smal is an Assistant Professor at the Department of Biology, Faculty of Science, Utrecht University. He has held previous positions at Erasmus MC (2009-2018) and TU Delft (2019-2020). His research bridges statistical image processing, smart microscopy, and explainable AI for biological motion analysis, with applications in automated real-time imaging systems. Education: M.Sc. in Physics and Electrical Engineering, Ivan Franko National University of Lviv (1999, cum laude) Professional Doctorate in Engineering (PDEng), Eindhoven University of Technology (2005) PhD in Biomedical Imaging, Erasmus University/MC (2009) His work focuses on developing AI-driven solutions for motion registration, particle tracking, and image understanding in biological systems. He leads the NWO IMAGINE! program's Tech Work Package 2, aiming to automate imaging experiments using explainable AI. The 15 most recent publications highlight his contributions to deep learning for CT segmentation, particle tracking, diffusive state modeling, and real-time imaging optimization. Key subfields include neural networks, biomedical signal processing, and automated microscopy. Scientific Awards: VENI grant Erasmus MC Fellowship NWO BBoL grant Students: Vincent Hellebrekers Daan te Rietmole His lab at Utrecht University, accessible via www.smal.ws, collaborates with institutions like Erasmus MC and TU Delft, leveraging facilities such as the Utrecht Biology Imaging Center.

George van VoornView profile

Associate Professor

• Socio-ecological Systems
• Resilience Analysis
• Agent-Based Modelling
• +7 more

Dr. George van Voorn is an Associate Professor in Applied Modelling & Machine Learning at Wageningen University & Research, affiliated with the Biometris department. His research focuses on developing and applying mathematical and computational models to study socio-ecological systems, resilience, and complex adaptive systems. He specializes in agent-based modelling (ABM), hybrid machine learning approaches, and dynamical systems analysis (e.g., stochastic differential equations). Van Voorn coordinates courses such as MAT15003 (Mathematics 3), SSB-30806 (Modelling in Systems Biology), and PhD-level modelling courses. He also leads projects on resilience quantification in socio-ecological systems, including agricultural and fisheries systems. His work addresses topics like tipping points, bifurcation analysis, and model validation methodologies for health-economic and environmental policy applications. Key research areas include: Resilience metrics for socio-technical systems Climate change adaptation strategies using ABM Machine learning integration with crop and ecological models Model validation frameworks (e.g., AdViSHE tool) He collaborates on interdisciplinary projects such as the 4TU DeSIRE initiative, focusing on systems resilience engineering. His recent publications emphasize model-based analysis of socio-environmental feedbacks, food system dynamics, and health-economic decision-making.

Boudewijn F. van DongenView profile

Professor

• Process Mining
• Business Process Management
• Conformance Checking
• +3 more

Boudewijn F. van Dongen is a Full Professor in computer science at Eindhoven University of Technology (TU/e), holding positions in Mathematics and Computer Science, Process Analytics, and strategic initiatives like EAISI Foundational, EAISI Health, and EAISI High Tech Systems. He chairs the Process Analytics group, focusing on conformance checking within Business Process Management and Process Mining. Academically, he earned his MSc and PhD in computer science from TU/e (2003 and 2007). His research develops techniques and tools to analyze large-scale systems for process misconformance, leveraging alignments in ProM framework. Key projects include collaborations with Philips Research, Vanderlande, and GDPR compliance initiatives. He teaches courses like Foundations of Process Mining and Data Analytics. Awards include the Best Paper Award BIS 2011. His work contributes to UN Sustainable Development Goals through process optimization in logistics and healthcare.

• Fish Ecology
• Marine Biology
• Aquatic Conservation
• +3 more

Erwin Winter is a Professor at Wageningen University & Research, specializing in marine and aquatic ecology with a focus on fish migration, elasmobranch behavior, and environmental conservation. He leads and co-supervises multiple PhD projects, including evaluations of ecological restoration measures for rheophilic fish in regulated rivers and overwintering behavior of zander in Dutch waters. His research spans topics such as the impact of offshore wind farms on marine species, electromagnetic field effects on elasmobranchs, and the conservation of migratory fish like European eel (Anguilla anguilla). Winter’s work bridges applied and theoretical research, often involving collaboration with environmental agencies and NGOs. He has organized workshops on fish passage evaluation and presented findings at conferences on Caribbean reef shark ecology and North Sea elasmobranch distributions. His projects address challenges like habitat restoration, acoustic telemetry for species tracking, and mitigating anthropogenic impacts on aquatic ecosystems. Education: Not explicitly stated in the provided texts. Grants & Projects: Over 18 active/funded projects including EU-funded initiatives on eel migration, offshore wind farm impacts, and river barrier management. Media Engagement: Featured in 40+ media outlets discussing fish conservation, eel migration barriers, and marine biodiversity. His lab focuses on applied solutions for aquatic connectivity challenges, integrating field observations with advanced tagging and telemetry technologies. Recent studies highlight the importance of mitigating electromagnetic disturbances from subsea cables and optimizing sluice-gate management to support migratory fish populations.

Sytze de BruinView profile

Associate Professor

• Spatial analysis
• Spatial statistics
• Uncertainty analysis
• +7 more

Sytze de Bruin is an associate professor in Geographical Information Science at Wageningen University & Research, affiliated with the Laboratory of Geo-information Science and Remote Sensing. He holds an MSc in Soil Science and a PhD in Geo-information Science from Wageningen University. Previously, he worked as an applied soil scientist in Central America (Costa Rica and Nicaragua) before returning to the Netherlands. His research focuses on spatial and temporal analysis, uncertainty quantification, precision agriculture, and geostatistical methods. Key areas include data acquisition, spatio-temporal interpolation, and the application of GIS in environmental and agricultural contexts. He has contributed to over 100 publications and serves on the editorial boards of the International Journal of Geographical Information Science and Spatial Statistics . Recent work includes projects like Fields2Cover (optimizing agricultural paths to reduce soil compaction) and Smart Emission 2 (citizen science for air quality monitoring). His expertise spans spatial analysis, remote sensing, and quantitative methods, with applications in land degradation assessment and precision agriculture. Teaching responsibilities include courses on spatial modeling, remote sensing integration, and MSc thesis supervision in geo-information science. His lab emphasizes translating data into actionable geo-information through interdisciplinary approaches.

Tayfun KucukyilmazView profile

Lecturer

• Web Search Engines
• Machine Learning
• Parallel and Distributed Systems
• +3 more

Dr. Tayfun Kucukyilmaz is a Lecturer at the Rotterdam School of Management, Department of Technology and Operations Management. Previously, he served as an Assistant Professor at the University of Turkish Aeronautical Association and TED University (Computer Engineering Departments) from 2012 to 2021. His expertise spans Web Search Engines, Machine Learning, and High Performance Computing. Educational Background: B.S. in Computer Science and Engineering (Bilkent University, 1995–2000) M.S. in Computer Engineering (Bilkent University, 2000–2003) Ph.D. in Computer Engineering (Bilkent University, 2006–2012) Research Focus: His work emphasizes optimizing search engine performance, developing metaheuristic algorithms, and enhancing information retrieval systems. Current research integrates machine learning techniques with parallel/distributed computing for real-world applications like healthcare diagnostics. Collaborations: Active collaborations span global institutions, particularly in areas of optimization algorithms and search engine efficiency.

• Bioinformatics
• RNA Folding
• Biospectroscopy
• +7 more

Anne de Jong is a researcher in the Molecular Genetics department at the University of Groningen, specializing in bioinformatics and computational biology. Her work focuses on developing user-friendly pipelines and web servers for integrating data mining and statistics, particularly in bacterial genetics and transcriptomics. She contributes to tools like BAGEL3, PePPER, and Genome2D, which aid in analyzing prokaryotic genome and transcriptome data. Her group utilizes Linux servers to manage large datasets from techniques such as Next Generation Sequencing and proteomics analysis. Her research interests include RNA folding, biospectroscopy, and translating big-data into biological knowledge. She has published extensively on bacteriocin detection, promoter prediction, and data visualization frameworks for prokaryotic systems biology.

• Traumatic Brain Injury
• Neurotrauma
• Nervous System Injury
• +5 more

Dana Pisica is an active Researcher in the Neurosurgery department at Erasmus Medical Center, with significant contributions to traumatic brain injury research. Her work focuses on neurotrauma classification systems, intracranial pressure monitoring, and mental health outcomes following brain injuries through large-scale collaborative studies including CENTER-TBI and TRACK-TBI. Her research interests span the critical domains of traumatic brain injury, neurotrauma, nervous system injury, cohort analysis, intracranial pressure management, and intensive care unit protocols. These areas reflect her focus on both the immediate neurological consequences and long-term psychiatric outcomes of brain trauma. Analysis of her recent publication trends reveals a strong emphasis on developing standardized classification systems for traumatic brain injury, creating predictive models for intracranial hypertension using advanced radiomic techniques, and investigating the complex relationship between brain trauma and subsequent mental health conditions including depression and PTSD. Her work bridges clinical neuroscience with data science methodologies. Dana Pisica actively participates in major international research consortia including CENTER-TBI and TRACK-TBI, contributing to large-scale collaborative efforts that involve multiple institutions across different countries. Her research has garnered significant attention with publications being picked up by 18 news outlets and shared across various social media platforms.

• Systems Biology
• Synthetic Biology
• Genomics
• +4 more

Jasper Koehorst is an Assistant Professor in Systems and Synthetic Biology at Wageningen University & Research. His research focuses on integrating computational and experimental approaches to study microbial genomics, metabolic engineering, and systems biology. He leads projects exploring genome-scale models for industrial biotechnology applications, such as syngas fermentation optimization and machine learning-based process control. His work also addresses fundamental questions in plant-microbe interactions, symbiotic relationships, and evolutionary genomics. Koehorst has contributed to initiatives like FAIR data standards for genomics and digital twin frameworks in life sciences. Education: He holds a PhD in Molecular Biology from Wageningen University (2019), with a thesis on necrotizing fasciitis pathogenesis. His postdoctoral research expanded into systems biology and synthetic microbial consortia. Research Interests: His group investigates microbial metabolic flexibility, computational modeling of biological systems, and applications in bioenergy and bioprocess engineering. Key areas include genome annotation pipelines, microbial community dynamics, and the development of open science resources like Wikidata integration for biological data. Publications: His recent work spans high-impact journals like Cell and Computational and Structural Biotechnology Journal , with a focus on interdisciplinary topics such as MLOps in fermentation, auxin signaling mechanisms, and genomic analyses of symbiotic microbes. Over 50 peer-reviewed articles highlight his contributions to microbial genomics and systems approaches. Grants & Awards: While no specific awards are listed, his projects have received institutional support through Wageningen University collaborations and EU-funded initiatives. He currently co-supervises three active PhD projects on microbiome dynamics, computational modeling, and bioindustry 4.0 applications. Labs/Teams: Koehorst is affiliated with the Systems Biology group and collaborates with the Bioinformatics & Systems Biology department at Wageningen. His team works closely with industry partners on bioprocess optimization and digital twin technologies.

Mark ScheperView profile

Professor

• Artificial Intelligence in Healthcare
• Ethical AI
• Rare Diseases in Children
• +5 more

Mark Scheper is a Professor at Macquarie University (Faculty of Medicine and Health Sciences) and Lecturer at Rotterdam University of Applied Sciences in the field of AI & Data-Supported Healthcare. He serves as Science Lead at HR Datalab Healthcare and co-founded the National Expertise Center for Ehlers-Danlos Syndrome at Erasmus MC. PhD in Pediatric Rare Diseases (University of Amsterdam, 2019) Specialist in Ehlers-Danlos syndrome and chronic fatigue Expert in ethical AI and data science for healthcare His research focuses on integrating artificial intelligence into clinical practice while addressing ethical implications and workforce readiness. He leads transdisciplinary projects like ACT4FATIGUE (chronic fatigue prediction) and Orange Babies (sports performance optimization), emphasizing responsible AI adoption. Recent publications analyze trends in digital healthcare ethics , AI-assisted diagnostics , and chronic pediatric conditions . His work spans from rare diseases in children to sports injury prevention, with particular attention to data quality and technology accessibility. Collaborates with Medical Delta, Health Holland, and national medical centers Develops learning communities through co-creation with professionals, patients, and policymakers Focuses on training healthcare workers for AI literacy and ethical deployment

Karine da Silva Miras de AraujoView profile

Assistant Professor

• Robotics
• Artificial Intelligence
• Evolutionary Computing
• +5 more

Karine da Silva Miras de Araujo is an Assistant Professor at Vrije Universiteit Amsterdam's Faculty of Science, affiliated with the Artificial Intelligence department and the Network Institute. Her research focuses on evolutionary robotics, digital organisms, and adaptive systems, emphasizing phenotypic plasticity, modular designs, and benchmarking frameworks. She teaches courses like Evolutionary Computing and Introduction to Artificial Intelligence. Her work explores topics such as controller architectures for arbitrary robot morphologies, lamarckian principles in robot evolution, and human-in-the-loop agent prototyping. Key contributions include the AMaze benchmark generator and studies on phenotypic plasticity costs in digital organisms. No scientific awards are explicitly listed. She has supervised one PhD thesis but specific student names are not provided. Her courses emphasize foundational AI concepts and evolutionary methodologies, reflecting her dual focus on theoretical advancements and practical applications in robotics.