جست‌وجوی استاد و پژوهشگر

Malte Braackمشاهده پروفایل

استاد

• Computational Mathematics
• Fluid Dynamics
• Numerical Analysis
• +۶ مورد دیگر

Malte Braack is a Professor of Applied Mathematics at Christian-Albrechts-University of Kiel (CAU Kiel). He serves as Director of the Mathematical Seminar and Principal Investigator in the Cluster of Excellence 'The Future Ocean'. Additional roles include Editorial Board membership at the Journal of Applied Mathematics and Computing, participation in the SHUG Extended Executive Board, and involvement in DFG Priority Programs (e.g., Optimization with Partial Differential Equations, MetStroem). PhD: University of Heidelberg (1998) Habilitation: University of Heidelberg (2005) Diploma: University of Hamburg (1994) DAAD scholarship: University of Complutense Madrid (1991-1992) Braack's research focuses on computational mathematics and fluid dynamics, particularly stabilized finite element methods for partial differential equations, reactive flows, and ocean modeling. Recent work includes sedimentation models, Nash equilibria for collective choice, and CO2 leakage detection in marine environments. His 15 most recent publications (2019-2025) span fluid dynamics, numerical analysis, oceanography, and optimization. Key subfields include Navier-Stokes stabilization, reactive transport, deep learning for geoscience, and game-theoretic policy modeling. DAAD scholarship during studies at Madrid (1991-1992) Editorial Board: Journal of Applied Mathematics and Computing Membership: Sociedad Española de Matemática Aplicada (SEMA)

Joan Remskiمشاهده پروفایل

استاد

• Numerical Analysis
• Applied Mathematics
• Partial Differential Equations
• +۳ مورد دیگر

Joan Remski is an Associate Provost for Faculty Development and Digital Learning and Professor of Mathematics at the University of Michigan-Dearborn . She holds a Ph.D. in Applied Mathematics from Michigan State University (1997) and a B.S. in Mathematics from her current institution. Education: B.S. in Mathematics, University of Michigan-Dearborn Ph.D. in Applied Mathematics, Michigan State University (1997) Dr. Remski's research focuses on numerical analysis and applied mathematics , particularly moving mesh methods for solving partial differential equations (PDEs) with sharp phase transitions. Her work emphasizes adaptive computational techniques to improve solution accuracy and efficiency. Recent publications highlight her contributions to mesh optimization and balanced adaptive algorithms in PDE numerical solutions. Collaborations with Q. Du and J. Zhang demonstrate interdisciplinary engagement. Scientific Awards: Distinguished Service Award (2014) Dr. Remski has served as Program Director for the MS in Applied and Computational Mathematics (2006-2011, 2015-present) and has been active in curriculum development for both undergraduate and graduate mathematics programs.

• Computational Fluid Dynamics (CFD)
• Large-Eddy Simulation (LES)
• Aero-acoustics
• +۵ مورد دیگر

Prof. Dr.-Ing. Wolfgang Schröder is a full professor at RWTH Aachen University and currently serves as Dean of the Faculty of Mechanical Engineering . In addition, he is Director of the Institute of Fluid Mechanics and Aerodynamics , a member of the Steering Committee of the Profile Area Modeling & Simulation Sciences , and RWTH’s representative in the Scientific and Technical Council (WTR) of the Forschungszentrum Jülich. His professional addresses are Wüllnerstraße 5a, 52062 Aachen and Eilfschornsteinstraße 18, 52062 Aachen , reachable at office@aia.rwth-aachen.de and dekan@fb4.rwth-aachen.de . His research portfolio spans computational fluid dynamics , large-eddy simulation , aero-acoustics , turbulent boundary-layer control , drag-reduction technologies , high-performance computing for multi-phase flows, and biomedical flow modeling . Recent work emphasizes: Multi-fidelity and surrogate modeling for active flow control and drag reduction. Advanced LES and hybrid RANS/LES methods for complex internal and external flows. Coupled CFD/CAA approaches to predict and mitigate aero-acoustic noise from airframes, landing gears, and distributed propellers. High-resolution simulations of gas-liquid and electrochemical flows in engineering and biomedical contexts. Across more than 80 peer-reviewed contributions since 2021, a clear trend emerges toward physics-based machine learning , real-time optimization , and exascale-ready algorithms that integrate experimental data (PIV, DLS) with massively parallel simulations. Scientific Awards & Honors : No specific awards are enumerated in the supplied text; however, his continuous leadership roles (Dean, Institute Director, WTR representative) indicate sustained recognition within the academic community. Advising & Funding : While individual student names are not listed, Prof. Schröder heads a large research group responsible for numerous doctoral and master’s theses. Projects are supported by German federal programs, EU Horizon initiatives, and industrial partnerships with aerospace and automotive sectors. Laboratories & Teams : He directs the Institute of Fluid Mechanics and Aerodynamics (AIA), operates within the Center for Computational Engineering Science (CCES), and leverages RWTH’s high-performance computing clusters for large-scale simulations.

• Applied Mathematics
• Numerical and Computational Mathematics
• Fractional Calculus
• +۵ مورد دیگر

Libo Feng is a Researcher in the School of Mathematical Sciences at the Faculty of Science, Queensland University of Technology (QUT). His research focuses on applied mathematics, numerical methods, and fractional calculus with applications to fluid dynamics, heat transfer, and heterogeneous media. He holds a Doctor of Philosophy from QUT. Key research interests include: Development and analysis of fractional-order models for viscoelastic fluids and nanofluids Computational homogenization of heterogeneous media with memory effects Numerical simulation of anomalous diffusion in comb structures Magnetohydrodynamic (MHD) flow dynamics with non-Newtonian constitutive relationships His recent work emphasizes novel boundary condition techniques for fractional differential equations, with publications in high-impact journals like Journal of Computational Physics and Physics of Fluids . Research has practical applications in solar energy systems, biological tissues, and agricultural product mechanics. Notable contributions include: Advancements in fractional integrodifferential equation solvers Innovative finite volume methods for irregular domains Analysis of transient viscoelastic nanofluid behaviors Current research explores distributed-order fractional models and their applications in multi-layered systems.

• Machine Learning
• Computer Vision
• Structural Health Monitoring
• +۱ مورد دیگر

Senjian An is a Senior Lecturer in the School of Electrical Engineering, Computing and Mathematical Sciences at Curtin University, Faculty of Science and Engineering. His research focuses on machine learning, computer vision, and structural health monitoring, with applications in 3D displacement measurement and anomaly detection. Key interests include physics-guided neural networks, unsupervised learning for time-series data, and vision-based structural analysis. His recent publications emphasize robustness in damage detection, synthetic data generation, and transformer-based models for industrial monitoring. An's work integrates deep learning with engineering challenges, advancing non-contact measurement techniques for civil infrastructure. No students or awards are noted. Collaborative projects involve vibration analysis and maritime surveillance, reflecting a strong applied focus in AI and computer vision.

Wei Baiمشاهده پروفایل

دانشیار

• Computational Hydrodynamics
• Wave-Structure Interactions
• Offshore Engineering
• +۳ مورد دیگر

Dr. Wei Bai is a Reader in Mathematics at Manchester Metropolitan University's Department of Computing and Mathematics, specializing in computational marine hydrodynamics. He holds a Ph.D. in Port, Coastal and Offshore Engineering from Dalian University of Technology. Research focuses on: Numerical modeling of wave-structure interactions Offshore renewable energy systems Sloshing dynamics and hydrodynamic stability Computational fluid dynamics development His extensive publication record demonstrates consistent innovation in numerical methods for marine applications, with recent emphasis on moonpool hydrodynamics, floating wind turbines, and advanced CFD techniques. Research integrates theoretical modeling with practical offshore engineering challenges. Dr. Bai serves on editorial boards for Applied Ocean Research, Ocean Engineering, and Journal of Marine Science and Application. He has supervised multiple doctoral students in marine hydrodynamics and offshore engineering.

Reddy J.N.مشاهده پروفایل

استاد

• Applied Mechanics
• Computational Mechanics
• Finite Element Analysis
• +۵ مورد دیگر

Professor J.N. Reddy is a distinguished academic and researcher in applied mechanics and computational engineering at Texas A&M University. He holds the O’Donnell Foundation Chair IV and is a member of the National Academy of Engineering. His roles include Director of the Center of Innovation in Mechanics for Design and Manufacturing (CiMDM) and affiliated faculty in multiple departments. Education: B.E. (Mechanical Engineering, Osmania University, 1968); M.S. (Mechanical Engineering, Oklahoma State University, 1970); Ph.D. (Engineering Mechanics, University of Alabama in Huntsville, 1973); Postdoctoral Fellowship (University of Texas at Austin, 1973–1974). Research interests focus on applied mechanics, computational methods, and advanced materials. He pioneered shear deformation theories (e.g., Reddy third-order plate theory) and developed finite element models used in commercial software like ABAQUS. Current work includes nonlocal mechanics, GraFEA for fracture analysis, and bio-medical applications. Award Highlights: Timoshenko Medal (2019), von Neumann Medal (2017), and membership in multiple national academies. His research has led to over 1,500 publications and international recognition. Advising: Mentor to over 100 Ph.D. and M.S. students. Collaborations span institutions globally, including Aalto University, National University of Singapore, and others. Lab: Advanced Computational Mechanics Laboratory (ACML) focuses on innovative numerical methods and materials research.

Zhilin Liمشاهده پروفایل

استاد

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۵ مورد دیگر

Zhilin Li is a Professor in the Department of Mathematics at North Carolina State University. He is affiliated with the College of Sciences and specializes in numerical analysis, scientific computing, and partial differential equations. His research focuses on developing numerical methods for interface problems, irregular domains, and complex fluid dynamics systems. Education: PhD in Applied Mathematics from the University of Washington (1994). Research interests include: numerical methods for PDEs with free boundaries, finite difference/element methods, computational fluid dynamics (CFD), and biological flow simulations. He has contributed to advancing high-order compact schemes, immersed interface methods, and adaptive finite element techniques. Recent work emphasizes solving anisotropic diffusion problems, moving contact line dynamics, and multiphase flow challenges in engineering and biomedical contexts. His methods address accuracy and stability in complex geometries and discontinuous coefficients. Key contributions include the Immersed Interface Method (IIM) for interface problems and novel finite difference schemes for irregular domains. His research spans applications from petroleum engineering (wellbore stability) to neuroscience (neuroregeneration). Grants and collaborations are implied through his publications, though specific funding details are not listed here. He is actively involved in interdisciplinary projects combining mathematics with engineering and life sciences.

• Continuous Casting Processes
• Mathematical Modeling of Industrial Systems
• Fluid Dynamics
• +۳ مورد دیگر

Michael Vynnycky is an Affiliated Professor at KTH Royal Institute of Technology , specializing in mathematical modeling and numerical analysis of industrial metallurgical processes. His research focuses on continuous casting , electromagnetic stirring , and fluid-structure interactions in manufacturing systems. Key Research Areas: Continuous casting of metals, fluid dynamics, heat transfer, computational methods (FEM, CFD), inverse Stefan problems, and oscillation mark formation. Collaborations: Frequent collaboration with researchers like H. Fredriksson, B. Glaser, and A. Safavi Nick. Applications: Steel production, die casting, redox flow batteries, and polymer electrolyte fuel cells. Recent publications highlight work on blast furnace dynamics , muon radiography for structural analysis, and asymptotic modeling of gas-solid flows. His methodologies emphasize mathematical rigor and industrial relevance , as seen in studies on macrosegregation and electromagnetic flow control. Techniques: Leverages asymptotic analysis multiphysics simulation finite element methods computational fluid dynamics boundary reconstruction algorithms experimental validation to solve complex industrial problems. Email Contact: michaelv@kth.se

Niklas Kolbeمشاهده پروفایل

استاد

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۴ مورد دیگر

Niklas Kolbe is an interim professor at the Department of Mathematics, RWTH Aachen University . His research focuses on numerical analysis, modeling of partial differential equations, and applications in cancer biology and traffic flow systems. Current affiliation: Department of Mathematics, RWTH Aachen University Academic rank: Interim Professor Research Interests Dr. Kolbe specializes in: Numerical methods for hyperbolic/parabolic PDEs Adaptive mesh refinement Lagrange-Galerkin techniques Cancer invasion modeling (stem cells, extracellular matrix) Network models for blood vessels/road systems Notable Contributions Recent publications address: Lax-Friedrichs methods in hemodynamics Relaxation approaches for fluid-solid coupling Flux-limited PDEs for glioma invasion Stochastic TGF-β signaling models

Francesc Verdugo Rojanoمشاهده پروفایل

استادیار

• Scientific Computing
• Parallel Algorithms
• Partial Differential Equations
• +۳ مورد دیگر

Francesc Verdugo Rojano is an Assistant Professor at the Faculty of Science (Computer Systems) at Vrije Universiteit Amsterdam, with additional affiliations at the Network Institute and Distributed Computer Systems. His research focuses on scientific computing, parallel algorithms, and numerical methods for partial differential equations, particularly leveraging finite element methods. He actively contributes to open-source software like Gridap, an extensible finite element toolbox in Julia. His work spans computational physics, structural engineering, and materials science, emphasizing scalable numerical techniques for complex systems. Notable research includes fusion technology simulations, hydroelastic analysis of floating structures, and optimization of surface-enhanced Raman spectroscopy substrates. Collaborations involve international teams and interdisciplinary applications. Teaching responsibilities include courses on parallel programming and large-scale parallel systems. His research outputs highlight contributions to unfitted finite element methods, geometric discretization, and computational mechanics, with a strong emphasis on practical software implementations.

• Fluid Mechanics
• Applied Mathematics
• Geothermal Energy Storage
• +۴ مورد دیگر

Meissam Bahlali is a Researcher at Imperial College London's Department of Earth Science & Engineering within the Faculty of Engineering, part of the Novel Reservoir and Simulation group (NORMS). He specializes in fluid mechanics and applied mathematics with applications to porous media flow, geothermal energy, and atmospheric dynamics. Educational Background: PhD in Fluid Mechanics (2015-2018) from CEREA, École des Ponts ParisTech/EDF R&D Postdoctoral Researcher at Aix-Marseille Université (2020) Research Associate at Imperial College London (2019) Research Focus: His work spans stochastic fluid mechanics models, unstructured adaptive mesh techniques for density-dependent flows in porous media, lattice Boltzmann methods for moving boundaries, and applications to saline intrusion, geothermal storage, and copper transport in sedimentary basins. He has contributed to over 15 peer-reviewed publications and presented at major conferences like AGU, EGU, and SEG. Teaching & Supervision: He has supervised 1 PhD and 2 MSc students (2024), taught MSc courses on geo-energy systems, and delivered training sessions on computational fluid dynamics. He also served as an examiner for a PhD defense on Lagrangian pollutant dispersion models. Affiliations: Active in NORMS group, with links to ResearchGate, LinkedIn, and a personal website. His work integrates numerical methods, geoscience, and environmental engineering to address challenges in resource modeling and climate systems.

Andreas Dednerمشاهده پروفایل

دانشیار

• Numerical Analysis
• Scientific Computing
• Higher Order Methods
• +۴ مورد دیگر

Andreas Dedner is an Associate Professor at the University of Warwick's Department of Mathematics, serving as Director of Studies for the MASDOC Doctoral Training Centre and a core developer of the DUNE Project. His work focuses on numerical analysis, scientific computing, and higher-order methods for nonlinear evolution equations, with applications in geophysical flows, magnetohydrodynamics, and software engineering. He leads research on discontinuous Galerkin methods, grid-based numerical schemes, and parallel computing. He has organized numerous workshops, including the Dune School at Warwick (2012) and conferences on geometric multigrid methods. His software contributions include the DUNE-FEM module and ALU-Grid Library, emphasizing efficient adaptive grid techniques and parallelization. Key research grants include EPSRC projects on finite element methods and NERC-funded weather modeling initiatives. His research spans computational fluid dynamics, surface PDEs, and interdisciplinary applications like radiation magnetohydrodynamics. Recent publications address stabilization techniques, virtual element methods, and coupled flow models. Dedner’s work bridges theoretical analysis with practical software development, impacting both academic and applied scientific computing landscapes.

• Computational Mechanics
• Fluid-Structure Interaction
• Solid Dynamics
• +۱۲ مورد دیگر

Professor Antonio Gil is a faculty member at Swansea University within the Faculty of Science and Engineering , specifically in the Department of Civil Engineering . He graduated magna cum laude from the University of Granada (Spain) in 1999 and earned his PhD in computational analysis of non-linear structural membranes at Swansea University in 2005, winning the UK Society for Computational Mechanics best PhD paper in 2004. Education: Ingeniero de Caminos, Canales y Puertos (University of Granada, 1999); MSc in Computational Mechanics; PhD in Computational Mechanics (Swansea University, 2005) Research Interests span Computational Mechanics , Fluid-Structure Interaction , Finite Strain Modeling , and Soft Robotics , with a focus on physics-informed machine learning and multi-physics simulations. His work addresses challenges in electromechanical systems , cardiac mechanics , and high-strain dynamics . Recent Publications highlight advancements in SPH algorithms , topology optimization , and hyperelastic metamodels , reflecting his leadership in numerical methods and material modeling . These contributions have been recognized by prestigious awards including the Philip Leverhulme Award (2011) and the Olgierd Cecil Zienkiewicz Award (2016) . Scientific Awards: UK Philip Leverhulme Award (2011) Olgierd Cecil Zienkiewicz Award (2016) 1st National Award (Spanish Ministry of Education, 2000) Grants include coordination of the Erasmus Mundus PhD Program and leadership in H2020 Marie Curie ETN projects with budgets exceeding €6M. His supervision covers PhD projects in soft robotics , computational fracture , and MRI scanner design .

• Computational Fluid Dynamics (CFD)
• Turbulence Simulation
• Wind Farm Optimization
• +۵ مورد دیگر

Professor Sylvain Laizet is a faculty member in the Department of Aeronautics at Imperial College London, part of the Faculty of Engineering. He holds a PhD and Habilitation à Diriger des Recherches from the University of Poitiers in France, specializing in Computational Fluid Dynamics (CFD). His research focuses on turbulent flows and their engineering applications, including wind farm optimization, quantum algorithms for fluid mechanics, and machine learning integration in CFD. Key research areas include: Wake-to-wake interaction in wind farms Bayesian optimization for drag reduction and energy efficiency Immersed boundary methods for moving objects Quantum computing for solving PDEs in fluid dynamics His work leverages high-order numerical methods and large-scale simulations, with contributions to frameworks like Xcompact3D and WInc3D. Recent publications emphasize quantum algorithms, turbulence entrainment, and data-driven optimization strategies for renewable energy systems. Scientific contributions span over 50 peer-reviewed articles in top-tier journals, focusing on advancing CFD methodologies and their applications in environmental and industrial fluid mechanics. His team collaborates globally, including partnerships in France and Brazil.