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Renee HellerView profile

Professor

• Electric Vehicle Charging
• Energy Flexibility
• District Heating
• +3 more

Renee Heller is a Full Professor at the Faculty of Technology at Amsterdam University of Applied Sciences (AUAS), specializing in energy systems and innovation. Her research focuses on electric vehicle (EV) charging infrastructure, energy flexibility, and sustainable urban planning. She leads projects addressing smart grid integration, district heating, and low-energy residential solutions. Dr. Heller has been recognized with the HvA Research Prize 2021 and was nominated for the KennisDC Pearl 2023. Her academic contributions include collaborative work on EV charging hubs, optimal battery sizing for grid capacity, and predictive heating control using machine learning. She actively participates in conferences and media discussions, such as the 'SolarNL=SolarPeople' event and interviews on HeatNet NWE project insights. Her research emphasizes practical applications, evidenced by datasets on stakeholder analysis and agent-based modeling for EV charging resource allocation. Education: PhD in Energy Systems (inferred from role). Labs/Teams: Involved in the Amsterdam AUAS Applied Research Centre for Technology. Future Work: Expanding research on heat networks and net-zero city initiatives.

Melissa S.A.M. BeversView profile

Research Fellow

• Biomedical Engineering
• Orthopaedic Biomechanics
• Computed Tomography
• +3 more

Melissa S.A.M. Bevers is a Research Fellow at the School of Biomedical Engineering , Eindhoven University of Technology , specializing in Orthopaedic Biomechanics . Her work focuses on advanced imaging techniques for bone microarchitecture analysis. External affiliation: VieCuri Medical Center Contributions to UN Sustainable Development Goals: Good Health and Well-being Research Interests: Utilizing high-resolution peripheral quantitative CT (HR-pQCT) and photon-counting CT to study bone structure, strength, and remodeling. Key areas include motion correction algorithms, radiation dose optimization, and disease-specific bone analysis (e.g., osteogenesis imperfecta). Recent Publications: Advancements in CT imaging accuracy (2025), comparative studies on bone remodeling detection (2024), and clinical applications in fracture liaison services (2024). Collaborations: Active partnerships with institutions like VieCuri Medical Center and researchers in bone health and imaging.

• Rheumatoid Arthritis
• Inflammatory Arthritis
• Methotrexate
• +7 more

Prof. Dr. Mieke Hazes is a leading academic at Erasmus University Medical Center (Erasmus MC) specializing in Rheumatology . With over 258 research outputs and 39 supervised works, her career focuses on inflammatory arthritis, methotrexate efficacy, and patient-centered outcomes. Department: Rheumatology Key Research Areas: Rheumatoid Arthritis, Psoriatic Arthritis, Disease Activity Scores, Pharmacogenomics, Quality of Life Her recent work explores methotrexate response variability in psoriatic arthritis, cross-sectional impacts of joint complaints in inflammatory bowel disease, and economic evaluations of referral strategies for spondyloarthritis. These publications (2023–2025) highlight her interdisciplinary approach combining clinical practice with genomic and health economics research. While no specific awards or student names are listed here, her dataset collaborations on topics like DMARD de-escalation and digital referral algorithms underscore her leadership in advancing rheumatology care through empirical studies.

• Breast Cancer
• Proton Therapy
• Radiation Therapy
• +3 more

Dr. Margriet Sattler is a Researcher at Erasmus MC in the Radiotherapy department. Her work focuses on optimizing radiation therapy techniques to minimize long-term complications while improving cancer treatment outcomes. PhD in Medical Sciences External position at Holland Proton Therapy Center (Holland PTC) since March 2016 Research Interests: Dr. Sattler specializes in breast cancer radiotherapy , proton therapy applications , and radiation-induced cardiovascular risks . Her work explores: Advanced radiation delivery methods (VMAT, IMPT) Dose optimization algorithms Long-term survivorship effects Genetic factors in radiation toxicity (BRCA1/2) Collaborative Trends: Recent projects involve international teams analyzing radiation dose impacts, developing AI-driven treatment planning tools, and studying secondary cancer risks post-radiotherapy.

O.A.L. EikenbroekView profile

Assistant Professor

• Transport Engineering
• Applied Mathematics
• Computer Science Models
• +6 more

O.A.L. Eikenbroek is an Assistant Professor at the Department of Transport Engineering and Management within the Faculty of Engineering Technology at the University of Twente. His work integrates civil engineering, applied mathematics, and computer science to address transport optimization challenges. Education: BSc in Civil Engineering (University of Twente, 2013) MSc in Civil Engineering & Management (Cum Laude, 2016) MSc in Applied Mathematics (University of Twente, 2016) Research Expertise: His research focuses on service synchronization, genetic algorithms, dwell time analysis, and assignment problems in transport systems, with interdisciplinary applications in social sciences and public transport optimization. He is affiliated with the Digital Society Institute at the University of Twente.

• NMR Spectroscopy
• Nanobiotechnology
• Microfluidics
• +3 more

Sander Baas is an Education/Research Officer in the BioNanoTechnology department at Wageningen University. His role involves academic research and educational initiatives, focusing on developing innovative hardware solutions for NMR spectroscopy and microscopy. He holds a PhD from Wageningen University, awarded in 2024, for his thesis on DIY NMR systems, magnets, and hyperpolarization hardware. His academic career has been centered around interdisciplinary research at the intersection of engineering and life sciences. Education: Sander Baas completed his educational background at Wageningen University, where he earned his PhD in 2024. His academic journey includes: PhD in BioNanoTechnology (2024) Research Interests: Sander Baas’ research interests span NMR Spectroscopy, Nanobiotechnology, and Microfluidics. He is deeply involved in designing advanced transceiver ASICs for multinuclear NMR applications and optimizing magnet systems for enhanced spectral resolution. Additionally, his work explores the integration of CRISPR technology with microscopy frameworks for in vivo tracking and the repurposing of 3D printers into biomedical tools like programmable syringe pumps. His studies often bridge electronics engineering with molecular biology, aiming to create accessible and high-performance instrumentation for scientific research. Articles Overview: His recent publications (2021–2023) emphasize the development of affordable and versatile NMR instrumentation, including a 2 T magnet with high sensitivity and a syringe pump derived from a 3D printer kit. He also focuses on microfluidic applications, such as hyperpolarization techniques using CIDNP, and advancing ASIC-based transceiver systems for multinuclear NMR. Earlier work (2018–2019) highlights contributions to single-molecule localization microscopy and CRISPR/dCas9 tracking in live bacteria, demonstrating a consistent thread of innovation in both hardware and biological imaging technologies. Scientific Awards: No scientific awards mentioned. Advising & Grants: In his academic journey, Sander Baas was a PhD candidate in the NanoSpin project (2018–2024), supervised by Prof. A. Velders and co-supervised by Dr. V. Saggiomo. This project addressed challenges in NMR spectroscopy signal intensity and polarization transfer within nanobiotechnology. No formal grants or advising roles are explicitly listed in the provided texts. Labs & Teams: He contributed to the NanoSpin research initiative at Wageningen University, focusing on NMR spectroscopy and nanobiotechnology advancements. Collaborations include work with the Universidad de Castilla-La Mancha on microfluidic datasets and open-source hardware projects. His research also involves partnerships with institutions in Biomedical Engineering and Electronics Design.

• Medical Genetics
• Molecular Diagnostics
• Prenatal Genetics
• +5 more

Mark Drost is a Researcher in the Clinical Genetics department at Erasmus University Medical Center (Erasmus MC), Rotterdam. His work focuses on advanced genetic diagnostics with emphasis on prenatal and neurodevelopmental applications. His research spans Medical Genetics , Molecular Diagnostics , and Prenatal Genetics , with specific expertise in DNA methylation analysis, exome sequencing, and Lynch syndrome variant classification. Key methodologies include chorionic villus sampling optimization, trisomy detection protocols, and functional assay development for genetic variant interpretation. Analysis of his recent publications reveals strong focus on clinical implementation of genomic technologies , particularly in prenatal diagnostics (2020-2025). His work demonstrates increasing translation of research into clinical practice, with 2024-2025 publications emphasizing routine diagnostic applications of DNA-methylation signatures and exome sequencing. The research consistently addresses high-impact clinical challenges in trisomy confirmation and neurodevelopmental disorder diagnostics. No scientific awards were documented in the provided materials. Dr. Drost collaborates extensively across Erasmus MC's clinical genetics teams, with co-authorship spanning diagnostic laboratory staff, clinicians, and researchers. His work involves significant grant-supported projects in prenatal genomics and cancer predisposition syndromes, though specific grant details weren't provided. He operates within Erasmus MC's Clinical Genetics department infrastructure, contributing to diagnostic pipelines for trisomy detection, exome sequencing interpretation, and Lynch syndrome variant classification. His research integrates laboratory diagnostics with clinical applications through multidisciplinary teams focused on improving genetic diagnostic yield.

• Computational Science
• Biomedical Engineering
• Blood Rheology
• +5 more

Gábor Závodszky is an academic researcher at the University of Amsterdam's Faculty of Science, Mathematics and Computer Science within the Informatics Institute. His work primarily focuses on computational modeling of biological systems, particularly in the realm of hemodynamics and thrombosis. He specializes in developing advanced numerical methods like the lattice Boltzmann approach for simulating complex fluid-structure interactions in vascular systems. His research integrates multiscale modeling techniques to study blood flow dynamics, platelet behavior, and clot formation under various physiological conditions. Key contributions include the development of the HemoCell framework, a high-performance computational tool for simulating cellular-level blood flow phenomena. He has collaborated extensively on projects involving cerebral aneurysm hemodynamics, flow diverter stent efficacy, and the impact of diabetes on blood rheology. Závodszky's work bridges computational science with clinical applications, aiming to improve understanding of vascular pathologies and support medical device optimization. His research has been published in top-tier journals and conference proceedings, reflecting his expertise in both theoretical and applied computational biology.

• Horticulture
• Plant Physiology
• Vertical Farming
• +5 more

Prof. Leo Marcelis is a Professor and Chairholder of the Horticulture and Product Physiology Group at Wageningen University & Research, specializing in plant physiology and sustainable crop production systems. He leads major research initiatives such as the SKY HIGH vertical farming program and the 'LED it be 50%' energy-saving project. His work focuses on optimizing plant responses to light, environmental conditions, and resource use efficiency in controlled environments, including greenhouses and vertical farms. Marcelis holds editorial roles for Frontiers in Plant Science and advises institutions like the Leibniz Institute. His research bridges fundamental plant biology with applied horticultural practices, addressing global challenges in food security and sustainable agriculture. Education : Expertise in horticulture and plant physiology, with a focus on crop modeling and environmental control. Research Interests : Vertical farming scalability, LED lighting optimization, closed-system agriculture, and energy-efficient crop production. Projects : SKY HIGH (vertical farming innovation), LED it be 50% (energy reduction), and TIME SCALE (space agriculture). International Roles : Vice Chair of the Leibniz Institute’s Science Advisory Board and Dutch representative in the ISHS Council. Marcelis collaborates extensively with industry partners, including Philips, Unilever, and agricultural technology firms, translating research into practical solutions for growers and policymakers.

Wieke EgginkView profile

Research Fellow

• Pediatric Movement Disorders
• Dystonia
• Deep Brain Stimulation
• +3 more

Dr. Wieke Eggink is a Neurology Resident and Postdoctoral Research Fellow at the University of Groningen, affiliated with the Faculty of Medical Sciences and Department of Neurology. Her primary focus is on pediatric movement disorders, particularly dystonia, and the application of deep brain stimulation (DBS) therapies. She holds additional roles as a board member of the Vereniging Arts-assistenten Neurologie (VAAN) and Stichting Wetenschapsfonds Dystonie (SWD). Her research concentrates on dystonia etiologies, neuropsychological impacts of movement disorders, and optimizing clinical care through rating scales and interdisciplinary approaches. Key contributions include studies on myoclonus, genetic dystonia syndromes, and biomarkers for DBS efficacy. She has authored over 45 peer-reviewed articles, with recent work emphasizing pediatric neurology and neurocysticercosis case studies. Eggink’s work spans clinical practice and academic research, addressing both motor and non-motor aspects of movement disorders. She actively collaborates with European networks like ERN-RND to improve care standards for rare neurological conditions. Her multidisciplinary approach integrates genetics, neurophysiology, and neuropsychology to advance diagnosis and treatment strategies.

• Genetics
• Plant Science
• Genomics
• +3 more

Joao Caldas Paulo is a researcher at Biometris under the PE&RC Research School at Wageningen University & Research. His work focuses on plant genetics, genomic prediction, and computational agriculture. Research Interests : Genome-Wide Association Studies (GWAS) for crop traits SNP marker discovery in legumes like faba bean Genetic architecture of agronomic characteristics Deep learning applications in floriculture and phenotyping Natural capital modeling for sustainable ecosystems Supervised Research : Co-promoted PhD projects on faba bean off-flavors and Andean lupin biomass quality. Notable Collaborations : Involved in datasets for potato genomics, hemp transcriptomics, and cabbage leaf morphology analysis.

• Bioinformatics
• Plant Genomics
• Renewable Energy Systems
• +5 more

Jan-Peter Nap serves as an External employee in the BIOS Applied Bioinformatics group at Wageningen University & Research, holding a doctoral engineering title (dr.ir.). His interdisciplinary work bridges computational biology and sustainable energy systems through 123 research outputs including 71 articles, 17 reports, and 12 book chapters. Research Focus: His primary investigations span plant genomics (gene regulation in root nodule development, Solanaceous genome analysis), bioinformatics tool development (pyPaSWAS for GPU-accelerated sequence alignment), and renewable energy systems (economic/environmental analysis of bio-power-to-methane conversion). This tripartite approach integrates molecular biology with environmental engineering and high-performance computing. Publication Trends: Recent work (2017-2020) demonstrates dual specialization: computational biology publications focus on sequence alignment algorithms and plant phenotyping metadata standards, while energy research examines methane production feasibility. Both strands emphasize practical implementation with measurable environmental benefits and Levelised Cost of Energy metrics. Supervision & Projects: He co-supervised two major PhD projects: Low-cost high performance biocomputing (2013-2019) developing GPU-accelerated genomic analysis tools Solanaceous genome bioinformatics (2010-2014) examining gene family relationships in crop plants Research Infrastructure: As core member of BIOS Applied Bioinformatics, he contributes to Wageningen's computational biology ecosystem focusing on agricultural applications, with demonstrated impact through 17+ Scopus citations for his renewable energy work and adoption of phenotyping data standards.

• Urban Analytics
• Smart Charging Systems
• Electric Vehicle Infrastructure
• +5 more

Dr. Pieter Bons serves as a Senior Lecturer at the Faculty of Technology, Hogeschool van Amsterdam, where he teaches Applied Mathematics and Data Science. His academic work spans urban analytics, smart charging systems, and geospatial modeling, with significant contributions to electric vehicle infrastructure and climate adaptation research. His research focuses on applying data science to urban challenges, particularly in smart charging for electric vehicles and neighborhood typology classification . Bons specializes in extracting actionable insights from complex urban datasets while addressing critical issues like data bias, quality, and privacy. His work bridges theoretical data science with practical urban applications, notably through projects like the Rijkswaterstaat charging infrastructure study and nationwide neighborhood typology mapping. Recent publications reveal a clear trajectory from fundamental physics (2010-2017) to applied urban analytics (2020-present), with current work emphasizing energy grid optimization through smart charging AI-driven climate adaptation tools geospatial analysis for urban planning His fingerprint analysis highlights strong connections to Smart Charging (95%), Public Charging Stations (36%), and Electric Vehicles (54%). Award highlights: HvA onderzoeksprijs 2021 for collaborative urban research Nominatie KennisDC Parel 2023 for innovation in zero-emission infrastructure Bons actively enhances data literacy across the faculty through educational initiatives like Data Studio, integrating students into real-world research cases. His activities include stakeholder presentations for Rijkswaterstaat, knowledge clips on neighborhood typologies, and academic talks on walkability and zero-emission corridors. He contributes to datasets like the Wijktypologie Buurtniveau 2023, supporting national climate adaptation efforts. His work occurs at the intersection of urban planning, energy systems, and AI, with current projects focusing on balancing urban energy grids through flexible EV charging and developing nationwide neighborhood classification systems for climate resilience.

Marco GiuliniView profile

Researcher

• Computational Structural Biology
• Integrative Bioinformatics
• Protein-Protein Interactions
• +5 more

Marco Giulini is a postdoctoral researcher at Utrecht University , affiliated with the Biomolecular Sciences department under the Science school. His work focuses on advanced computational methods for modeling protein-protein interactions, leveraging techniques like machine learning, integrative bioinformatics, and coarse-grained simulations. Expertise in Software Development , Machine Learning , and Computational Structural Biology Key research areas: Protein Complex Modeling , Antibody-Antigen Interactions , and Mapping Entropy Contributed to tools like HADDOCK3 and ARCTIC-3D for biomolecular simulations His recent publications highlight applications of machine learning in structural biology, integrative modeling of biomolecular complexes, and AI-driven approaches for drug discovery. Giulini collaborates extensively with experts in computational biophysics and structural biology.

Judith KeijsperView profile

Lecturer

• Graph Algorithms
• Computational Biology
• Combinatorial Optimization
• +4 more

Judith Keijsper is a Lecturer at the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e) , where she has been affiliated since 2000. She works within the Combinatorial Optimization group, focusing on graph algorithms and their applications in computational biology. She teaches courses such as Graph Theory, Linear Algebra, and Discrete Dynamical Systems. Her research spans phylogenetic network reconstruction, haplotyping complexity, and discrete optimization. Key themes include Unrooted binary phylogenetic level-1/level-2 networks Polynomial time algorithms for NP-hard problems Applications of graph theory to biological data Linear equation systems over GF(2) Her publications demonstrate expertise in algorithm design for genetic analysis and evolutionary modeling. No scientific awards are explicitly mentioned in the provided texts.