جست‌وجوی استاد و پژوهشگر

• Applied Mathematics
• Numerical and Computational Mathematics
• Partial Differential Equations
• +۴ مورد دیگر

Prof. Vanessa Styles is a Professor and Head of the School of Mathematical and Physical Sciences at the University of Sussex. Her research focuses on mathematical and computational analysis of nonlinear partial differential equations, with applications in physical sciences, including materials science, fluid dynamics, and biological modeling. She specializes in numerical methods for evolving surfaces, phase field models, and free boundary problems. Her work often involves interdisciplinary collaborations, addressing challenges in lithium batteries, tumor growth, and cell migration. Prof. Styles has led major grants, including ModCompShock (EU) and Leverhulme-funded projects on cell migration mechanics. She teaches calculus courses and actively contributes to academic leadership. Her research interests span computational fluid dynamics, numerical analysis of PDEs, and mathematical biology. Recent work emphasizes tumor growth modeling via phase field approaches, crystal growth in batteries, and cell migration force estimation. She has published extensively in journals like Interfaces and Free Boundaries and Journal of Computational Physics , with a focus on rigorous error analysis and algorithm development. Grants include funding for modeling grain boundary motion (EPSRC), 3D cell migration (Leverhulme), and shock interface modeling (EU). Her research bridges theoretical analysis and practical applications, with contributions to both fundamental mathematics and engineering/medical fields.

Erik Thostensonمشاهده پروفایل

استاد

• Composites & Advanced Materials
• Nanotechnology
• Aerospace Engineering
• +۴ مورد دیگر

Erik Thostenson is a Professor in the Department of Mechanical Engineering at the University of Delaware, with an affiliated appointment in the Department of Materials Science and Engineering. He holds degrees from the University of Delaware (PhD/MS in Materials Science and Mechanical Engineering) and Winona State University (BS in Composite Materials Engineering, Summa Cum Laude). His research focuses on advanced composite materials, nanotechnology, and multifunctional sensor integration into composites. Dr. Thostenson's expertise spans composites processing, nanomaterials characterization (particularly carbon nanotubes), and structural health monitoring. His work emphasizes developing novel fabrication techniques like electrophoretic deposition for hierarchical composites, with applications in aerospace, civil infrastructure, and biomedical wearable sensors. Notable awards include the NSF CAREER Award, Air Force YIP Award, Elsevier Young Composites Researcher Award, and Hayashi International Memorial Award. He has pioneered methods for in situ sensing in composites using nanomaterials, enabling real-time damage detection and smart material systems. His research portfolio includes over 100 publications on topics like carbon nanotube-based sensors, additive manufacturing of composite tooling, and VR-integrated rehabilitation systems. He has also contributed to industry-relevant solutions such as scalable roll-to-roll composite manufacturing and structural repair methodologies.

• Electromagnetic Theory
• Applied Mathematics
• Numerical Methods
• +۳ مورد دیگر

Dario Bojanjac is an Assistant Professor at the Department of Wireless Communications, Faculty of Electrical Engineering and Computing, University of Zagreb. His research focuses on mathematical modeling of electromagnetic processes, numerical methods for Maxwell's equations, and applied mathematics techniques like asymptotic analysis. He holds a PhD in mathematics (2015) and electrical engineering (2009), with extensive visiting scholar experience at institutions such as École Polytechnique Fédérale de Lausanne (EPFL) and the University of Michigan. Education: PhD in Mathematics (2015), Faculty of Science, University of Zagreb PhD in Electrical Engineering (2009), Faculty of Electrical Engineering and Computing His research interests include electromagnetic wave scattering, homogenization of Maxwell's equations, and computational electromagnetism. Recent work explores ground-based SAR systems, deep learning applications in radar data analysis, and flood classification using multivariate approaches. He has received awards including the Swiss Government Excellence Scholarship and Croatian Government Fellowship. His projects include satellite electromagnetic field measurements and metamaterial-based invisibility cloak realization. He participates in lab initiatives like AOLAB2 and coordinates projects such as BODYSEN and HybridAccess. Awards: Swiss Government Excellence Scholarships CIME Foundation Fellowship European Science Foundation Fellowship Bojanjac has advised on multiple research projects and contributed to educational initiatives like the MILE interactive learning system. His lab collaborations include work on sensor systems and optical communication technologies.

• Stochastic Processes
• Financial Mathematics
• Statistics
• +۳ مورد دیگر

Alexandra Chronopoulou is a Clinical Associate Professor in the Department of Statistics at the University of Illinois. She is affiliated with the Coordinated Science Lab and the Center for Social & Behavioral Science, contributing to interdisciplinary research in both mathematical theory and healthcare applications. Her roles emphasize bridging statistical methodologies with practical challenges in diverse fields. Her research interests span stochastic processes, including fractional Brownian motion and volatility modeling, alongside healthcare systems analysis and medical diagnostics. She applies statistical techniques to study burnout among healthcare professionals, particularly in pandemic testing environments, and explores biomechanical factors in gastrointestinal disorders. Her work also intersects with finance, focusing on risk management and option pricing through advanced stochastic frameworks. In recent years, her articles highlight trends in volatility estimation, fractional processes simulation, and healthcare ergonomics. Earlier contributions include methodological advances in sequential Monte Carlo, community detection algorithms, and multiscale diffusions. No scientific awards were explicitly mentioned in the provided texts. Though no advising or grant information was listed, her research collaborations extend to international partnerships. She contributes to labs and centers that foster interdisciplinary innovation, including work at the Coordinated Science Lab and the Center for Social & Behavioral Science.

• Conservation Laws
• Finite Volume Schemes
• Discontinuous Galerkin Methods
• +۷ مورد دیگر

Professor Siegfried Müller is a full professor at the Institute for Geometry and Practical Mathematics within the Faculty of Mathematics, Computer Science and Natural Sciences at RWTH Aachen University. His research focuses on developing advanced numerical methods for solving complex fluid dynamics problems, with particular expertise in conservation laws, adaptive multiscale techniques, and multiphase flow modeling. He maintains an active research program with numerous publications in leading computational mathematics journals and collaborates extensively with researchers across multiple institutions. Professor Müller's research interests span a wide range of computational mathematics topics including Conservation Laws, Finite Volume Schemes, Discontinuous Galerkin Methods, Adaptive Multiscale Techniques, and specialized applications in Fluid Dynamics. His work demonstrates particular strength in developing numerical methods for two-phase flow systems, transpiration cooling applications, and surface lubrication phenomena. His research bridges theoretical mathematical analysis with practical engineering applications, particularly in aerospace and mechanical engineering contexts. His recent publications reveal a strong focus on advancing numerical techniques for hyperbolic conservation laws, with increasing emphasis on stochastic methods, multilevel approaches, and coupled system modeling. His work spans both theoretical developments in numerical analysis and practical applications in fluid dynamics, with particular attention to multiphase flow systems and cooling technologies. The publications show a clear progression toward more complex, high-dimensional problems and increasingly sophisticated numerical techniques to address computational challenges. Professor Müller has led and participated in numerous research projects funded by German research organizations including DFG Priority Programmes, BMBF projects, and DFG Research Training Groups. His projects have focused on hyperbolic balance laws, adaptive numerical methods, transpiration cooling, and textured surface lubrication. He has organized multiple workshops on multiresolution methods and active drag reduction, demonstrating leadership in his research community. Professor Müller's research group at RWTH Aachen collaborates closely with engineering departments and industry partners to apply advanced numerical methods to practical engineering challenges. His team has developed specialized computational tools for simulating complex fluid phenomena, particularly in aerospace applications where cooling technologies and fluid-structure interactions are critical. The group maintains strong connections with international research communities in computational mathematics and fluid dynamics.

Michael Millerمشاهده پروفایل

استاد

• Medical Imaging
• Computational Anatomy
• Pattern Theory
• +۳ مورد دیگر

Michael I. Miller is the Bessie Darling Massey Professor and director of the Department of Biomedical Engineering at Johns Hopkins University (JHU), where he also leads the Center for Imaging Science and co-directs the Kavli Neuroscience Discovery Institute. His work focuses on computational medicine, medical imaging, and computational anatomy, particularly in neurodegenerative diseases like Alzheimer’s, Huntington’s, and schizophrenia. Miller has pioneered cloud-based methods for brain image libraries and algorithms, co-founded four startups, and holds over 200 publications and two textbooks. He earned his BS from SUNY Stony Brook (1976) and MS/PhD from JHU (1978/1983). Education: Bachelor of Science, State University of New York at Stony Brook, 1976 Master of Science, Johns Hopkins University, 1978 Doctor of Philosophy, Johns Hopkins University, 1983 Research Interests: Miller’s research integrates advanced imaging technologies to study brain structure and function in health/disease. Key areas include: Functional and structural analysis of neurodegenerative diseases Development of computational tools for early disease detection Multiscale data integration (molecular to tissue) Translational applications in clinical diagnostics Awards: IEEE Biomedical Engineering Thesis Award (1982) Johns Hopkins Paul Ehrlich Thesis Award (1983) NSF Presidential Young Investigator Award (1986) Johns Hopkins Gilman Scholar (2011) Fellow, American Institute for Medical and Biological Engineering Labs/Teams: His lab at JHU develops cloud-based imaging tools and collaborates on translational research. Projects include the xIV-LDDMM Toolkit and STalign spatial transcriptomics alignment software.

• Computational Materials Science
• Molecular Dynamics
• Machine Learning
• +۲ مورد دیگر

Dr. Priya Vashishta is a Professor with joint appointments in Computer Science, Materials Science, and Physics at the University of Southern California. His research integrates computational methods across multiple scales to address fundamental challenges in materials science and nanotechnology. Research focuses on multiscale simulation frameworks combining quantum molecular dynamics, machine learning interatomic potentials, and high-performance computing. Key areas include: energy storage materials, 2D materials characterization, catalytic processes, and AI-driven materials discovery. Publication trends reveal consistent development of computational methodologies: machine learning potentials for materials simulation, neural network quantum dynamics, GPU-accelerated computing, and multiscale modeling techniques. Recent work emphasizes practical applications in energy storage, nanoscale electronics, and advanced manufacturing. Research group activities include development of open-source simulation packages (PND, Allegro) and leadership in the MAGICS computational materials center. Contributions span fundamental theoretical frameworks to applied materials engineering.

• Multi-scale Mechanics
• Metamaterials
• Material Science
• +۳ 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.

Anaïs Couasnonمشاهده پروفایل

پژوهشگر

• Flood Risk Management
• Climate Change
• Environmental Science
• +۳ مورد دیگر

Anaïs Couasnon is a PhD researcher at the Department of Water and Climate Risk, Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, part of the Faculty of Science. Her research focuses on compound flood risk modeling, probabilistic methods, and global hazard assessment under climate change. She is supervised by Dr. Philip Ward and Dr. Hessel Winsemius as part of a VIDI project. Education: MSc in Hydraulic Engineering (TU Delft, 2017); BSc in Civil Engineering (McGill University, 2010). Research interests include probabilistic modeling, multivariate dependence analysis, flood risk management, and climate impacts on coastal-riverine interactions. She contributes to global datasets like COAST-RP and socio-hydrological benchmarking. Key activities include: Developing frameworks for compound flood risk assessment Modeling extreme sea-level events and storm surges Collaborating on global hazard frameworks and disaster risk reduction strategies Contributions to datasets include: COAST-RP dataset Panta Rhei socio-hydrological benchmark dataset

Claes Lundströmمشاهده پروفایل

استاد مدعو

• Medical Imaging
• Artificial Intelligence
• Digital Pathology
• +۴ مورد دیگر

Claes Lundström is an Adjunct Professor at Linköping University's Department of Science and Technology (ITN), affiliated with the Media and Information Technology (MIT) school. His primary research focuses on medical imaging, integrating machine learning, visualization, and human-computer interaction in clinical settings. He leads the technical side of digital pathology research at the Center for Medical Image Science and Visualization (CMIV), directing national-scale grants and serving as Arena Director for the Analytic Imaging Diagnostics Arena (AIDA). Since 2010, he has held dual roles as Research Director at Sectra AB and academic researcher, driving innovations that translate into commercial healthcare solutions. Lundström's work spans AI-driven diagnostics, uncertainty visualization, and precision orthopedics, with contributions recognized through leadership in major projects like the €70M BIGPICTURE initiative. His academic credentials include a PhD (2007) and Docent degree (2014), alongside extensive industry collaboration. Education: PhD in 2007 and Docent degree in 2014 from Linköping University. PhD: 2007 Docent: 2014 Research interests emphasize AI integration in diagnostics, particularly digital pathology and medical imaging workflows. His work addresses challenges like domain adaptation in AI models, uncertainty quantification in segmentation tasks, and interactive visualization tools for clinicians. Recent projects include the VAI-B platform for AI validation in breast imaging and the BigPICTURE collaboration for global pathology data sharing. Key grants include leadership roles in national-scale projects, such as the AIDA arena and SCAPIS study-based AI lab. His contributions to AI ethics and clinical adoption include studies on human-AI collaboration and quality assurance frameworks. Lundström also oversees labs like CMIV and AIDA, fostering cross-disciplinary research in medical imaging and AI.

Mark Goldmanمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Circuits
• Synaptic Plasticity
• +۴ مورد دیگر

Mark Goldman is a Professor in the Department of Neurobiology, Physiology and Behavior at the University of California, Davis. His research focuses on computational neuroscience, neuroengineering, and the study of neural circuits underlying memory, learning, and sensorimotor control. He is affiliated with the Center for Neuroscience and the Ophthalmology and Vision Science program. His work integrates mathematical modeling with experimental data to understand neural mechanisms in systems such as the cerebellum, oculomotor systems, and reinforcement learning circuits. Key research themes include synaptic plasticity rules, dynamics of neural circuits during memory consolidation, and the interplay between circuit architecture and adaptive behavior. Recent studies explore closed-loop systems, oscillatory mechanisms in short-term memory, and context-dependent neural control. His computational frameworks bridge theoretical neuroscience with experimental observations in both vertebrate and microbial systems. Goldman has contributed to education through innovative course-based research programs combining microbial biology with mathematical modeling. His publications reflect a deep engagement with interdisciplinary methods, including systems theory, machine learning, and biophysical modeling.

• Materials Science
• Mechanical Engineering
• Computational Mechanics
• +۳ مورد دیگر

Antoine Sanner is a Researcher affiliated with the Institute of Construction Materials (Institute of Building Materials) at ETH Zurich, part of the College of Architecture, Civil and Environmental Engineering. His work focuses on computational mechanics of building materials, surface topography analysis, and adhesion science. He co-developed the dtool and dserver systems to enhance FAIR data practices in research. Research interests include the structural behavior of cement-based materials, mechanisms of material adhesion under varying surface conditions, and multiscale analysis of surface roughness effects. He has also contributed to engineering tools for characterizing surface topography across scales, emphasizing the creation and use of 'digital surface twins' for material studies. His publications consistently explore topics at the intersection of materials science and mechanical engineering, with recent work advancing understanding of surface adhesion dynamics and cement curing processes. No scientific awards are explicitly mentioned in the provided texts. As part of the Professorship for Computational Mechanics of Building Materials, Antoine contributes to research infrastructure and computational methods development. He has no listed advisees or grants, and his role appears to be full-time with no indication of part-time status. He collaborates on projects involving advanced materials characterization, particularly in polycrystalline diamond coatings and bearing component analysis, leveraging both experimental and computational methodologies.

• Tidal Energy
• Hydrodynamics
• Renewable Energy Systems

Brian Sellar is a Reader at the University of Edinburgh's School of Engineering, focusing on tidal energy, hydrodynamics, and turbine performance. He holds a PhD and accepts PhD students. His research includes validating tidal turbine models, multi-scale coastal ocean modeling, and turbulence analysis for renewable energy sites. He received the MDPI Energies Editor’s Choice Award in 2021. His work contributes to optimizing tidal energy systems and advancing ocean engineering methodologies.

Joseph Robsonمشاهده پروفایل

استاد

• Physical Metallurgy
• Alloys for Extreme Environments
• Microstructural Modeling
• +۸ مورد دیگر

Prof. Joseph Robson holds the RAEng-DSTL Chair in Alloys for Extreme Environments and is a Professor of Physical Metallurgy at the University of Manchester. His research focuses on microstructural evolution in industrial alloys, particularly aluminum, magnesium, and zirconium, using advanced modeling techniques like Calphad-based thermodynamic and kinetic models. He leads the Light Alloy Processing group and collaborates with institutions like the Henry Royce Institute. Key projects include optimizing microstructures for aerospace, automotive, and nuclear applications through processes like friction stir welding and thermomechanical treatment. Education: BSc in Natural Sciences (Cambridge, 1993), PhD in Metallurgy (Cambridge, 1996). Professional memberships include the Institute of Materials, Minerals and Mining (Fellow, Light Metals Division board member). Research interests span dynamic precipitation behavior, irradiation effects on zirconium alloys, and magnesium alloy strengthening. He has pioneered studies on discontinuous precipitation and its impact on material properties. Awards include the Hume Rothery Award (2015), Grunfeld Medal (2011), and Champion H. Matthewson Award (2017). Advising and grants: Leads major projects like LightForm (EPSRC) and NEWAM (innovative manufacturing). His work addresses challenges in alloy design for extreme environments, with a focus on sustainable materials and advanced processing techniques. Labs/Teams: Active in the Materials Performance Centre and collaborates with industry partners such as Magnesium Elektron and Westinghouse on nuclear materials research.

• Subsurface Physics
• Carbon Capture and Storage (CCS)
• Reservoir Engineering
• +۵ مورد دیگر

Professor Ann Muggeridge holds the Proconsul & Chair in Subsurface Physics at Imperial College London's Department of Earth Science & Engineering (Faculty of Engineering). Her research focuses on subsurface fluid flow dynamics, particularly CO2 storage security and reservoir physics. She has held prestigious roles including Chair of the Norwegian IOR Centre's Scientific Advisory Committee (2016-2021) and Technical Committee member for SPE Reservoir Simulation Conferences. Education: D.Phil. in Atmospheric Physics from University of Oxford (1983-1986), B.Sc. (Hons) in Physics from Imperial College London (1980-1983). Professional milestones include BP Technology Fellow (2006-2008) and keynote addresses at major geoscience conferences. Research interests span CO2 geological storage, reservoir heterogeneity effects, and enhanced oil recovery (EOR). Key contributions include dynamic risk mapping for CO2 sites and pore-scale observations of low salinity flooding. Her work integrates computational modeling with field-scale studies to address energy transition challenges. Awards: EAGE IOR Symposium Chair (2013-2019), SPE Technical Committee Member, BP Technology Fellow Labs & Teams: NORMS (Novel Reservoir Modelling & Simulation), Energy Futures Lab Affiliate Grants & Advising: Leads Imperial's Subsurface Physics research group; no listed advisees but mentors through collaborative projects Active in academia as Imperial's Faculty of Engineering Ambassador for Women and Departmental Athena SWAN coordinator, advancing gender equity in STEM.