جستجوی استاد راهنمای دانشگاهی

Dr. Guanna Li is an Assistant Professor in the Biobased Chemistry and Technology group at Wageningen University & Research. Her research focuses on catalyst design and reaction mechanism studies in heterogeneous catalysis, leveraging advanced computational methodologies such as DFT, ab initio molecular dynamics (AIMD), and machine learning. She investigates dynamic catalyst behavior under reaction conditions and aims to establish structure-activity relationships for rational catalyst design. Key areas include biomass conversion, CO2 hydrogenation, and plastic upcycling. Dr. Li holds a dual PhD from Eindhoven University of Technology (TU/e) and Dalian Institute of Chemical Physics, with postdoctoral experience at TU/e and Delft University of Technology, supported by a VENI Talent Programme grant (NWO, 2016). She collaborates closely with experimental groups to bridge theory and practice in catalytic processes. Education: PhD in Heterogeneous Catalysis (TU/e), PhD in Raman Optical Activity (DICP), postdoctoral research at TU/e and Delft University of Technology. Research Interests: Multiscale modeling of catalytic reactions, transition metal carbide catalysts, CO2 hydrogenation to methanol, plastic upcycling via mechano-catalysis, and surface reaction dynamics. Her methodologies include DFT, AIMD, and machine learning for mechanistic insights. Projects: Transition metal carbide catalyst design, CO2 hydrogenation collaborations with DICP, and plastic upcycling initiatives. These projects emphasize synergy between computational and experimental approaches. Awards: VENI Talent Programme Grant (2016). Grants/Advising: Supervises MSc/PhD students and postdocs on catalysis and computational chemistry projects. Open to collaborations and applications for research positions. Labs/Teams: Leads a research team in Wageningen’s Biobased Chemistry and Technology group, emphasizing computational catalysis and sustainable chemical processes.

• Catalysis
• Computational Chemistry
• Heterogeneous Catalysis
• +۳ مورد دیگر

Dr. Soheil Solhjoo is an Assistant Professor at the University of Groningen (UG) within the Engineering Systems and Design (ESD) group, part of the Engineering and Technology Institute Groningen (ENTEG) at the Faculty of Science and Engineering. His research focuses on model-based engineering design, physics-based deep learning, and digital twins, with expertise in constitutive modeling, molecular dynamics simulations, contact mechanics, and physics-informed neural networks. Prior to UG, he conducted postdoctoral research in European projects like VMAP and UPSIM, contributing to multiscale material modeling and hyperelastic material development for soft biological tissues. He holds a PhD from the University of Groningen (2017), where his thesis addressed nanotribological studies, including contact area measurement in atomistic simulations and continuum mechanics applications in nanocontacts. Academic Role: Assistant Professor (since 2024) Institution: University of Groningen Department: Engineering Systems and Design (ESD) Research Interests Dr. Solhjoo's research spans materials science and mechanical engineering, emphasizing: Constitutive modeling of metallic materials Molecular dynamics and statics simulations Contact mechanics at atomic and macro scales Integration of physics-based principles into neural networks Multiscale material characterization Publications Trends His articles predominantly address material deformation mechanisms, constitutive model validation, and nanoscale contact analysis. Key themes include hot deformation behavior of metals, computational methods for material characterization (e.g., HDFT tool), and bridging atomistic simulations with continuum mechanics. Awards & Grants No specific awards listed, but contributions to collaborative EU projects (VMAP, UPSIM) highlight his grant-funded research activities. Actively involved in educational grants for mechanical and industrial engineering curriculum innovation. Labs & Teams Part of the ESD group and ENTEG, collaborating with academic and industrial partners in EU frameworks. Maintains a research portal with open-access tools like the Hot Deformation Fitting Tool (HDFT).

• Materials Science
• Multidisciplinary Engineering
• Mechanical Metallurgy
• +۵ مورد دیگر

Dr. Zhiming Zhao is an Associate Professor and Chair of the Multiscale Networked Systems (MNS) research group at the Informatics Institute (IvI), University of Amsterdam (UvA). He serves as the technical manager of the Virtual Lab and Innovation Center (VLIC) of LifeWatch ERIC, a European research infrastructure for ecology and biodiversity science. Zhao holds an IEEE Senior Member designation and is the Managing Editor of the Journal of Cloud Computing . He earned his Ph.D. in Computer Science from UvA in 2004. His research focuses on quality-critical distributed computing, data-intensive workflows, virtual research environments, and digital twins. He leads projects such as LTER-LIFE (Dutch research infrastructure for digital twins) and coordinates UvA contributions to EU initiatives like ENVRI-HUB Next , EVERSE , and BlueCloud-2026 . Zhao’s work spans technical development in EU projects (e.g., ENVRI-FAIR , ARTICONF , CLARIFY ) and leadership roles in international workshops and conferences. His team develops frameworks like NaaVRE (Jupyter-based collaborative environments) and CloudsStorm (dynamic infrastructure planning). Current research emphasizes trustworthy AI in cloud systems, federated learning, and edge-cloud resource optimization. Key achievements include over 150 peer-reviewed publications, supervision of numerous PhD students, and contributions to open science initiatives. His lab actively explores interdisciplinary applications in environmental science, medical imaging, and blockchain-based decentralized systems.

• Distributed Systems
• Cloud Computing
• Data-Intensive Workflow Management
• +۵ مورد دیگر

Wouter M. Koolen-Wijkstra is a Professor of Mathematical Machine Learning at the University of Twente (Statistics group) and a Scientific Staff Member at Centrum Wiskunde & Informatica (CWI), Amsterdam, in the Machine Learning department. His research bridges theoretical machine learning, game theory, and statistics, with active projects on multi-armed bandits, online learning, and safe inference methodologies. He co-leads INRIA-CWI associate teams (6PAC and 4TUNE) and is an ELLIS Scholar. His work emphasizes provable guarantees in learning algorithms, including: Regret minimization under risk-averse scenarios Multi-scale adaptation in online decision-making Game-theoretic equilibria computation Anytime-valid statistical inference via e-processes Recent publications demonstrate a focus on robust learning frameworks , particularly in bandit problems, hypothesis testing, and Nash equilibrium characterization, often leveraging information-theoretic and optimization principles. Awards include: Veni Grant (2015) for 'Learning at the Intrinsic Task Pace' QUT Vice-Chancellor's Fellowship (2013) for multitask learning Rubicon Grant (2010) for game-theoretic online learning ELLIS Scholar recognition He teaches graduate courses on Machine Learning Theory and Graphical Models at CWI. Current grants include collaborations with INRIA (4TUNE and 6PAC teams) and industry partnerships (e.g., PPS Booking.COM).

• Machine Learning Theory
• Game Theory
• Information Theory
• +۵ مورد دیگر

Victorita Dolean-Maini is Professor at University of Strathclyde and Visiting Professor at University of Strathclyde (2023-2026). She specializes in domain decomposition methods for PDEs, high-performance computing, and scientific machine learning. Her work develops fast algorithms for wave propagation problems and complex systems. She co-authored the reference work 'Domain Decomposition Methods' (SIAM 2015) and received the Bull-Joseph Fourier Prize for stroke simulation using HPC. Current research explores physics-informed neural networks with domain decomposition architectures and their application to medical digital twins. She serves on the editorial board of SIAM Journal on Scientific Computing and collaborates with industrial partners on scientific machine learning projects. Recent publications focus on neural network architectures combining domain decomposition with physics-informed learning, multilevel methods, and efficient coarse spaces for partial differential equations.

• Domain Decomposition Methods
• High Performance Computing
• Wave Propagation
• +۲ مورد دیگر

Jack Yang is an Assistant Professor in the Department of Food Science at Wageningen University & Research, specializing in the Physics and Physical Chemistry of Foods. His research focuses on interfacial phenomena in food systems, particularly plant protein functionalization, oleosome membrane mechanics, and foam/emulsion stabilization. He leads multiple interdisciplinary projects combining physics, data science, and food technology. Key research interests include: Interfacial rheology of plant proteins and phospholipids Stabilization mechanisms in food foams and emulsions Utilization of plant-based ingredients (rapeseed, mung bean, asparagus) Development of sustainable food processing methods Recent work emphasizes protein-phenolic interactions, AI-driven food system modeling, and valorization of agricultural by-products. He collaborates extensively with industry partners on plant protein innovation and has pioneered methods for high-yield oleosin extraction. Current projects include large language model applications in food product development and physics-encoded neural networks for prediction of complex food systems. As a co-promotor for seven PhD candidates, Yang supervises research on topics like functional protein-extract interactions, microstructure imaging of protein interfaces, and combining physics with data science for functionality prediction. His work bridges fundamental colloid science with practical food formulation challenges.

• Food Colloids
• Interfacial Rheology
• Plant Protein Functionalization
• +۳ مورد دیگر

Prof. Mangala Srinivas is a Full Professor and Chair of Cell Biology and Immunology at Wageningen University & Research (WUR, Netherlands). She is also a Chief Scientific Advisor to the European Commission, the first WUR appointee to this prestigious role. Her research focuses on multifunctional nanoparticles for in vivo imaging and immunomodulation, pioneering 19F MRI for cell tracking and developing translational diagnostic/therapeutic platforms. Her work involves integrating imaging modalities like fluorescence, MRI, and photoacoustics in cancer and cardiovascular disease studies. Key achievements include winning the Dutch Venture Challenge 2015 (leading to spin-off Cenya Imaging B.V.) and securing major grants including ERC, NWO VENI, and EU H2020 funding. She oversees a department of ~30 staff impacting 2000+ students annually and contributes to WUR's sustainability/inclusion policies. Beyond academia, she chairs initiatives on Open Science and gender equity through the Young Academy of Europe, speaking globally at UNESCO and EuroScience events. Education: PhD: Carnegie Mellon University (USA) BSc (Hons): National University of Singapore Research Interests: Multifunctional nanoparticle design for imaging and therapy 19F MRI and multimodal imaging techniques Immune cell tracking in disease models Grants & Awards: ERC Proof of Concept Grants (2019-2024) H2020-MSCA-ITN (€4.05M coordination) NWO Take-off Phase II (€250k) Policy Impact: EU Scientific Advice Mechanism (SAM) member Advocacy for researcher equity and Open Science Her lab integrates cutting-edge imaging technologies with clinical translation, emphasizing nanoparticle stability and safety. Recent work explores force sensing hydrogels and long-term nanoparticle stability, advancing personalized medicine applications. Collaborations span academia, industry (e.g., Cenya Imaging), and policymakers to bridge research and societal impact.

• Nanoparticle Engineering
• Medical Imaging (MRI/PET/Fluorescence)
• Immunomodulation
• +۳ مورد دیگر

Dr. Marieke Klijn is an Assistant Professor at the Department of Biotechnology, Faculty of Applied Sciences, Delft University of Technology. Her research focuses on data-driven bioprocess development, leveraging process analytical technology (PAT) to enhance real-time monitoring and control of bioprocessing strategies across industries. She leads the Marieke Klijn Group, which develops frameworks for integrating data from process analyzers to improve process understanding and product quality in continuous and intensified bioprocessing environments. Her work emphasizes flexibility in bioprocessing approaches, including monitoring, control, and technology development. Recent studies highlight applications in stem cell culture bioreactors, synthetic co-culture systems, and PAT miniaturization for biopharmaceuticals. She advises multiple PhD candidates researching topics like CFD modeling, off-gas measurements, and microbial cell factories for cellular agriculture. Key research directions include optimizing bioreactor designs, enhancing Raman spectroscopy models for fermentation monitoring, and predicting protein behavior in chromatography. Her group collaborates on projects funded by industry and academic partnerships, addressing challenges in bioprocess scalability and real-time quality assessment.

• Bioprocess Engineering
• Process Analytical Technology
• Data-Driven Biotechnology
• +۳ مورد دیگر

Dr. Amin Askarinejad is an Associate Professor of Experimental Soil Mechanics at Delft University of Technology (TU Delft), specializing in geotechnical safety and renewable energy foundations. He holds a PhD from ETH Zurich (2013) and previously worked as a postdoctoral researcher at ETH Zurich before joining TU Delft in 2014. He currently serves as Director of the Research Programme at the Dams Safety Section of the Swiss Federal Office of Energy (SFOE). Research Focus: seismic safety of embankment dams, landslide early warning systems, soil-structure interaction for renewable energy structures Projects: BLUE Piling, MIDAS, GEOLAB, MAGIC, TRAMM, SafeLand, COST Action TU1202 Leadership Roles: President ad interim of ICOLD working group on small dams, Technical Committee member of ISSMGE (TC208 and TC104) His research integrates geotechnical physical modelling, advanced sensing, and numerical methods. Recent work examines offshore wind turbine foundations, monopile behavior in sand, and flood protection dam seepage. He has contributed to EU-funded projects and large-scale experiments like the Dutch Dike failure test in 2014. Scientific Awards: George Stephenson Medal (2022) R.M. Quigley Award (2019) Bright Spark Lecturer award (2018) Best Teacher Awards (2017-2018) Best Paper Award (2019) Dr. Askarinejad serves on editorial boards for the Journal of Landslides (Springer) and the International Journal of Physical Modelling in Geotechnics (ICE UK). His work aligns with UN Sustainable Development Goals related to climate resilience and sustainable infrastructure.

• Geotechnical Engineering
• Soil Mechanics
• Natural Hazards
• +۳ مورد دیگر

Dr. Erika Tsingos serves as an Assistant Professor in the Department of Theoretical Biology and Bioinformatics at Utrecht University's Faculty of Science. She leads the Computational Animal Development Group focusing on computational approaches to developmental biology questions. Her research spans animal developmental biology with emphasis on Computer modeling of cell fate decisions Pattern formation in tissues Cell migration mechanics Thymus development and leukemogenesis C. elegans developmental precision She employs diverse modeling approaches including ordinary differential equations and multiscale cell-based models using cellular Potts or center-based formalisms. Analysis of her 15 most recent publications reveals strong focus on computational modeling of developmental processes, particularly examining extracellular matrix effects on cell migration, thymic niche architecture in leukemia development, and precise cell fate specification in C. elegans. Her work consistently bridges computational modeling with experimental validation through collaborations. Scientific recognition includes: NWO grant VI.Veni.222.323 for research on extracellular matrix effects on cell migration Dr. Tsingos actively mentors the next generation of computational biologists through supervision of postdoctoral researchers and students. Current team members include Benjamin Planterose Jiménez (post-doc modeling C. elegans development), Saber Shakibi (post-doc developing hybrid migration models), and Nikki Landzaat (Master's student studying mesoderm cell state transitions). Former students include Bidayatul Masulah (Master's in Applied Mathematics) and Heleen van Osch (bachelor researcher). Her research group operates within Utrecht University's Department of Theoretical Biology and Bioinformatics, collaborating extensively with the Ten Tusscher group and experimental labs. Current projects investigate how extracellular matrix affects cell migration phenotypes in cancer and the molecular control mechanisms behind C. elegans' precise cell division patterns.

• Computational Biology
• Animal Developmental Biology
• Multiscale Modeling
• +۴ مورد دیگر

John van Duynhoven is a Professor of Biophysics at Wageningen University and Research. His work bridges advanced imaging techniques and food science, focusing on lipid oxidation, protein processing, and emulsion structure. Affiliation: Wageningen University and Research Academic Rank: Professor Research Interests: He investigates food structure and stability using NMR spectroscopy, super-resolution microscopy, and magnetic resonance imaging. Key areas include lipid oxidation pathways, plant-protein extrusion, and granular flow dynamics. Scientific Contributions: Supervised multiple PhD projects on multiscale protein modeling, emulsion oxidation, and infant nutrition protein digestion. His recent articles highlight innovations in quantifying anisotropic food structures and oxidation products. Collaborations: Partnerships span imaging techniques, X-ray scattering, and food technology. Active projects include lipid oxidation mapping and protein extrusion modeling.

• Food Science
• Biophysics
• Lipid Oxidation
• +۵ مورد دیگر

Johannes Hohlbein is an Associate Professor in Biophysics at Wageningen University & Research , with a focus on interdisciplinary research bridging food science, molecular biology, and advanced microscopy techniques. His work spans structural analysis of protein-based food materials and single-molecule studies of biomolecular processes. Interdisciplinary Research : Food Science, Biophysics, Molecular Biology Methodologies : Super-resolution microscopy, cryo-CLEM, Fourier transform analysis, single-particle tracking Scientific Contributions include: Structural anisotropy in soy protein extrudates Heterogeneity in food emulsions Lipid oxidation mechanisms DNA-targeting enzyme dynamics Statistical tools for nanoparticle tracking Supervised PhD Projects : Measurement and Modeling of Multiscale Protein Products (MP3) Biomolecule Localization in Food Matrices Food Oxidation Studies via Cryo-CLEM Single-Nanoparticle Diffusometry Plant Hormone Response at Single-Molecule Level

• Biophysics
• Food Science
• Biochemistry
• +۸ مورد دیگر

Simon J. Watson is a Professor in the Faculty of Aerospace Engineering at Delft University of Technology, specializing in Wind Energy through the TU Delft Wind Energy Institute (DUWIND). His work focuses on advancing wind turbine technology, wind farm optimization, and renewable energy integration within the university's aerospace framework. His research spans wind turbine engineering, condition monitoring systems, atmospheric effects on energy production, and wind farm design. Key investigations include damage detection in turbine components (blades, drivetrains), simulation of atmospheric gravity waves for improved energy forecasting, and hybrid wind-storage systems for grid stability. Recent work emphasizes machine learning applications for predictive maintenance and high-fidelity modeling of boundary layer conditions. Professor Watson's 2025 publications reveal a strong trend toward AI-driven condition monitoring and refined atmospheric simulations, with consistent focus on operational reliability and damage detection across wind energy systems. His work bridges computational fluid dynamics, structural health monitoring, and energy storage integration. He actively supervises students and leads the €4.2M MERIDIONAL project (2022-2026) on multiscale wind farm modeling, developing advanced toolchains for performance assessment and load prediction. This EU-funded initiative involves collaboration with Siemens Gamesa, Vestas, and ENEL. As a core member of DUWIND, he co-develops industry partnerships and experimental facilities including wind tunnel testing and field monitoring systems for offshore wind farms. His team maintains close ties with the Netherlands Wind Energy Association and European Wind Energy Technology Platform.

• Wind Energy
• Wind Turbine Engineering
• Condition Monitoring
• +۳ مورد دیگر

Daan Crommelin holds a part-time professorship in Numerical Analysis and Dynamical Systems at the KdV Institute for Mathematics, University of Amsterdam, and is a senior researcher at CWI Amsterdam's Scientific Computing group. He serves on CWI's management team and previously led its Scientific Computing group (2013–2021). His research focuses on stochastic modeling of multiscale systems, uncertainty quantification, and rare event analysis, with applications in climate science, renewable energy, and fluid dynamics. Crommelin combines methods from scientific computing, applied probability, and dynamical systems to address challenges in atmosphere-ocean-climate modeling. He has contributed to projects like the EU-funded VECMA initiative for exascale computing and collaborated on superparameterization techniques for climate models. His work also extends to epidemic modeling and computational chemistry. Crommelin earned his PhD in 2003 from Utrecht University, with a thesis co-supervised by KNMI, and holds an MSc in theoretical physics and an MA in philosophy from the University of Amsterdam.

• Uncertainty Quantification
• Stochastic Modeling
• Data-Driven Modeling
• +۶ مورد دیگر

Varvara G. Kouznetsova is an Associate Professor in Multi-scale Mechanics of Solids at the Department of Mechanical Engineering of Eindhoven University of Technology (TU/e). Her roles include leading the Mechanics of Materials group and teaching courses such as Advanced Computational Continuum Mechanics and Material Models. She holds a PhD in Mechanical Engineering from TU/e and a degree in Applied Mathematics from Perm State Technical University, Russia. Prior to her current position, she was a Research Fellow at NIMR and M2i institutes and an Assistant Professor at TU/e from 2006 to 2018. Her research focuses on developing multi-scale techniques for materials ranging from advanced steels to metamaterials, emphasizing emergent phenomena across scales. Key interests include computational homogenization, wave propagation, and fracture mechanics. She has supervised 54 academic works and contributed to 160+ research outputs, including influential studies on metamaterials and multiscale analysis. Her recent articles explore topics like reduced-order modeling for elastomeric metamaterials, multiscale FEM-MD coupling for nanocrystalline metals, and acoustic metamaterial transient analysis. She collaborates internationally and maintains datasets on platforms like 4TU.Centre for Research Data. Courses taught include Computer-Aided Engineering and Composite Materials Design.

• Multi-scale Mechanics
• Metamaterials
• Material Science
• +۳ مورد دیگر