جست‌وجوی استاد و پژوهشگر

Yuri Bazilevsمشاهده پروفایل

استاد

• Computational Mechanics
• Isogeometric Analysis
• Fluid-Structure Interaction
• +۵ مورد دیگر

Yuri Bazilevs is the E. Paul Sorensen Professor of Engineering at Brown University's School of Engineering and Co-Director of the Mechanics of Undersea Science and Engineering Center. His research focuses on computational mechanics, isogeometric analysis, fluid-structure interaction, and high-performance computing. Prior to Brown, he held positions at UC San Diego, where he advanced to Full Professor in 2014 after a rapid tenure. He earned his PhD in 2006 and postdoc training in computational engineering at UT Austin's ICES. Research interests span computational fluid dynamics, solid mechanics, and advanced discretization methods like isogeometric analysis (IGA) and meshfree approaches. He has developed novel formulations for complex phenomena such as underwater explosions, composite material failure, and hypersonic flow dynamics. His work integrates cutting-edge numerical methods with practical engineering applications in aerospace, energy, and biomedical systems. Recent publications highlight advancements in IGA for architected materials, RKPM-based crack modeling, and stabilized formulations for compressible flows. His contributions bridge theoretical mechanics with computational innovation, addressing challenges in multiphysics coupling and large-scale simulations. Collaborations span academia and industry, emphasizing practical validation and real-world impact. Bazilevs' expertise includes variational multiscale methods, peridynamics for fracture mechanics, and immersive particle methods for fluid-structure interaction. His work has been applied to wind turbine aerodynamics, gas turbine optimization, and cardiovascular flow analysis. He actively contributes to computational infrastructure development, such as the tIGAr software framework for IGA automation.

Hailong Chenمشاهده پروفایل

دانشیار

• Computational Mechanics
• Computational Materials
• Meshfree Methods
• +۶ مورد دیگر

Hailong Chen is an Associate Professor in the Department of Mechanical and Aerospace Engineering within the Stanley and Karen Pigman College of Engineering at the University of Kentucky. His academic journey includes a Ph.D. in Mechanical Engineering from Arizona State University (2015) and an M.S. in Mechanical Engineering from the University of Florida (2012). Dr. Chen's research focuses on Computational Mechanics & Materials, with expertise spanning meshfree methods, multi-scale multi-physics modeling, mechanics of stochastic heterogeneous microstructures, and pervasive fracture and impact modeling. His work bridges theoretical developments with practical engineering applications through the CM 3 (Computational Mechanics and Methods) research group, which develops advanced computational techniques for real-world mechanics problems. The CM 3 group specializes in multi-scale multi-physics modeling of solid materials, damage and failure analysis under extreme conditions, mechanics of stochastic heterogeneous microstructures (composites, polycrystals), and computational materials engineering. Recent publications demonstrate strong activity in peridynamics, lattice particle methods, and computational homogenization techniques for fibrous and porous materials. Dr. Chen's research has resulted in numerous publications in top journals including Computer Methods in Applied Mechanics and Engineering and Mechanics Research Communications, with recent work focusing on generalized peridynamic formulations, micro-CT-based property computation, and fluid-structure interaction frameworks for hypersonic applications. His academic progression shows steady advancement from Postdoctoral Computational Scientist at Idaho National Laboratory (2015-2018) to Assistant Professor (2018-2024) and currently Associate Professor (2024-present) at the University of Kentucky.

• Geomechanics
• Granular Materials
• Foundation Engineering
• +۶ مورد دیگر

Prof. Wu, Wei is a Professor and Director at Institute of Geotechnical Engineering , Department of Structural Engineering and Natural Hazards, BOKU University, Vienna, Austria. With over two decades of academic and industry experience, his work bridges geotechnical research and engineering practice. Education: Dr.-Ing. in Geotechnical Engineering (Karlsruhe University, Germany, 1986–1993), MSc in Geotechnical Engineering (Xian University of Technology, China, 1982–1985), Bachelor in Civil Engineering (Wuhan University, China, 1978–1982). Research Interests span geomechanics, granular materials, and computational geotechnical engineering. His expertise includes: Constitutive modeling of soils and granular media Numerical simulation of landslides and debris flows Soil bioengineering and root reinforcement Geo-energy systems and energy storage Advanced computational methods (SPH, DEM, FE) Selected Google Scholar Articles (2025–2024) highlight innovations in hypoplastic models for climate-affected soils, machine learning applications for slope stability, and multiscale simulations of geohazards. His work emphasizes both theoretical advancements (e.g., phase-field fracture models) and practical solutions (e.g., centrifuge testing for tunnel design). Scientific Awards include: Advanced Grant, European Research Council (2024) Gold Medal, Technical University of Brno (2024) Teaching & Supervision covers soil mechanics, tunneling, and advanced geotechnical courses. He has supervised over 30 PhD and 100 MSc theses, mentoring future engineers in numerical methods and geohazard mitigation. Leadership Roles : Editor-in-Chief of Acta Geotechnica , founder of Springer Series in Geomechanics, and Chairman of the Otto Pregl Foundation (€3M endowment). He organized key conferences like the China-Europe Conference on Geotechnical Engineering (2018) and International Symposium on Particle-Based Continuum Methods (2019).

Armin Iskeمشاهده پروفایل

استاد

• Numerical Approximation
• Applied Mathematics
• Kernel Methods
• +۴ مورد دیگر

Prof. Dr. Armin Iske is a Full Professor of Numerical Approximation at the University of Hamburg's Department of Mathematics, within the Faculty of Mathematics, Computer Science and Natural Sciences. He holds a PhD from the University of Göttingen (1994) and habilitation from TU Munich (2002). His research focuses on numerical approximation, kernel-based methods, computational fluid dynamics, and medical imaging. He has held academic positions globally, including visiting roles at ANU (Australia) and the University of Leicester (UK). Research interests include scattered data approximation, adaptive particle methods for flow simulation, and high-dimensional data analysis. He has authored 118+ publications, including works on kernel interpolation, medical imaging reconstruction, and machine learning applications. He serves on editorial boards for journals like Advances in Computational Mathematics and Sampling Theory . His contributions span interdisciplinary projects, such as SFB/TRR 181 on energy transfer in atmosphere and ocean, and collaborations in nanotechnology for brain interfaces. His work bridges theoretical mathematics with practical applications in engineering and biosciences.

• 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 .

Yanzhi Zhangمشاهده پروفایل

استاد

• Fractional Partial Differential Equations (PDEs)
• Scientific Computing
• Numerical Analysis
• +۶ مورد دیگر

Dr. Yanzhi Zhang is a Professor of Mathematics at the Department of Mathematics and Statistics, Missouri University of Science and Technology (Missouri S&T), where she has held academic positions since 2010. She earned a Ph.D. in Mathematics from the National University of Singapore and a B.Sc. in Applied Mathematics (with a Computer Science minor) from Chongqing University. Her research spans computational and applied mathematics, focusing on fractional PDEs, nonlocal models, machine learning applications in materials science and business, Bose-Einstein superfluids, and seismic wave inversion. Dr. Zhang has been awarded the Faculty Excellence Award from Missouri S&T and other accolades. Her work is supported by grants from the National Science Foundation, including projects on fractional viscoacoustic wave equations, Bose-Einstein superfluids, and dispersive wave equations. She advises Ph.D. students in interdisciplinary research, such as Yumeng Wang (machine learning for eye-tracking data) and Yixuan Wu (seismic inversion). Her research integrates mathematical rigor with computational innovation, addressing real-world challenges in geophysics, materials science, and business analytics. Collaborations with industry and academia enhance her contributions to data-driven modeling and open-source strategies for digital transformation.

Pedro Navasمشاهده پروفایل

دانشیار

• Computational Mechanics
• Geotechnical Engineering
• Solid Dynamics
• +۶ مورد دیگر

Pedro Navas serves as Associate Professor at the Department of Continuum Mechanics and Structural Theory within the Civil Engineering School of Universidad Politécnica de Madrid (Technical University of Madrid). His academic progression includes Assistant Professor (2019-2022), Contract Doctor Professor (2022-present), with upcoming appointment as Department Director (September 2024). He also contributes as a member to the R&D+i Center for Smart and Sustainable Civil Infrastructure (CIVILis) since November 2024. His educational background includes PhD studies in Computational Mechanics at the University of Castilla-La Mancha (2013-2017) followed by a PostDoc position at the Polytechnic University of Catalonia (2017-2018). Navas specializes in computational mechanics with particular expertise in Material Point Method applications for large deformation problems in geotechnical engineering. His research spans soil-water coupled problems, landslide modeling, biomechanics, and numerical methods for saturated soils. Current projects focus on 'Meshfree modeling of dynamic problems in civil engineering,' employing techniques like MPM, OTM, and PFEM. His technical skills encompass Differential Equations, Numerical Modeling, Nonlinear Dynamics, and Mathematical Modeling across civil engineering applications. His publication record demonstrates consistent output in computational geomechanics, with recent work emphasizing two-phase modeling, stabilization techniques for numerical methods, and interdisciplinary applications in medical engineering. The research shows strong methodological development in meshfree approaches with practical applications to geotechnical challenges. Juan de la Cierva - Formación Scholarship (June 2018) Navas maintains active collaborations with researchers across Spain and internationally, evidenced by co-authorship with institutions including Polytechnic University of Catalonia, King's College London, and various Spanish research centers. His work bridges theoretical numerical methods with practical engineering applications across civil infrastructure and biomedical contexts.

Yanghong Huangمشاهده پروفایل

مدرس

• Applied Mathematics
• Numerical Analysis
• Mathematical Biology
• +۱۱ مورد دیگر

Dr. Yanghong Huang is a Lecturer in Applied Mathematics at the University of Manchester's School of Mathematics since July 2015. Previously, he held a Chapman Fellowship at Imperial College London (2012–2015) and was a Postdoctoral Fellow at Simon Fraser University (2010–2012). His education includes a PhD in Applied and Computational Mathematics from UCLA (2010), an MA in Mathematics from UCLA (2006), and a BSc in Mathematics from Hong Kong Baptist University (2004). His research focuses on applied analysis for differential and integral equations, particularly in mathematical biology and collective behavior of particle systems. He investigates asymptotic analysis of steady states, solutions near blowup, numerical methods for gradient flow systems, and fractional Laplacians. Key areas include nonlocal interactions, stability analysis, and numerical schemes for complex systems. Dr. Huang contributes to the UN Sustainable Development Goals through his work on Digital Futures. His expertise spans pattern formation, finite volume methods, self-similar solutions, and kinetic theory. He leads research groups in Industrial and Applied Mathematics and Numerical Analysis and Scientific Computing. His publications explore topics like ground states of nonlocal variational problems, fragmentation equations, and aggregation-diffusion models. Collaborations span global institutions, addressing challenges in mathematical physics, computational methods, and nonlinear dynamics.

Phu Nguyenمشاهده پروفایل

مدرس

• Computational Mechanics
• Phase-field Fracture
• Multiscale Modeling
• +۵ مورد دیگر

Dr. Phu Nguyen is a Lecturer in Structural Engineering at Monash University's Department of Civil and Environmental Engineering. He holds a PhD in Computational Mechanics from Delft University of Technology (2011) and has held academic positions at Johns Hopkins University, Cardiff University, and the University of Adelaide before joining Monash in 2016. His expertise spans computational mechanics, phase-field fracture modeling, and multiscale material analysis. Education: Bachelor of Science in Civil Engineering, Hochiminh University of Technology (1998) Master of Science in Computational Mechanics, University of Liège (2005) PhD in Computational Mechanics, Delft University of Technology (2011) Research Interests: Focuses on computational modeling of failure in quasi-brittle materials (concrete, composites) using advanced numerical methods such as phase-field fracture, material point method (MPM), isogeometric analysis, and multiscale homogenization. Active in developing open-source computational tools like MPMat and Karamelo . Publications: Over 78 peer-reviewed articles, including highly cited works on meshless methods, phase-field fracture, and computational homogenization. Notable contributions to journals like Computer Methods in Applied Mechanics and Engineering and Engineering Fracture Mechanics . Awards: ARC DECRA Fellowship (2016–2019) Best PhD Presentation Award (2010) CIFRE Scholarship Most Cited Article in Advances in Applied Mechanics (2025) Grants & Supervision: Leads research projects on hydraulic fracturing and composite failure. Supervised PhD student Tushar K Mandal. Active in teaching courses like CIV4235 (Advanced Structural Design) and CIV3284 (Concrete and Masonry Structures). Professional Roles: Editorial board member of Engineering Fracture Mechanics , Computers, Materials and Continua , and Computer Modeling in Engineering & Sciences . Reviews for top journals including Computer Methods in Applied Mechanics and Engineering and International Journal of Numerical Methods in Engineering .

Pengtao Sunمشاهده پروفایل

استاد

• Computational Mathematics
• Numerical Solutions of Partial Differential Equations
• Finite Element Method
• +۵ مورد دیگر

Pengtao Sun is a Professor in the Department of Mathematical Sciences at the University of Nevada, Las Vegas (UNLV). His research focuses on computational mathematics, numerical solutions of partial differential equations, and scientific computing, with applications in fluid-structure interaction, fuel cell dynamics, and clean energy technologies. Supported by NSF since 2009, his work emphasizes advanced numerical methods like the finite element method, finite volume method, and domain decomposition techniques. He has contributed to modeling fluid-structure interactions using ALE and fictitious domain methods, as well as studies on lithium batteries and PEM fuel cells. His research also explores energy-preserving algorithms and machine learning approaches for complex systems. Dr. Sun’s expertise includes anisotropic/isotropic adaptive finite element methods, phase field methods, and the development of efficient solvers for multiphysics problems. His recent work addresses challenges in deterministic lateral displacement problems and thermal management of energy systems. He collaborates with the Center for Applied Math & Statistics (CAMS) at UNLV and has published extensively on topics like blood pressure prediction via fluid-structure interaction modeling and mesh-free neural network methods. His research portfolio reflects a blend of theoretical advancements and practical applications, bridging computational mathematics with engineering and environmental science. While no awards are explicitly listed, his sustained NSF funding underscores the significance of his work in advancing numerical methodologies for complex physical systems.

Axel Klarمشاهده پروفایل

استاد

• Kinetic Theory
• Traffic Flow Modeling
• Pedestrian Dynamics
• +۶ مورد دیگر

Prof. Axel Klar is a Professor in the Department of Technomathematics at the Rheinland-Palatinate University of Applied Sciences (RPTU) Kaiserslautern-Landau. His research focuses on mathematical modeling of complex systems, with a strong emphasis on kinetic theory, fluid dynamics, and applied analysis. Key areas of expertise include traffic flow dynamics, fiber dynamics in industrial processes, pedestrian movement patterns, and biological systems such as cell motion and tumor growth. He develops and analyzes numerical methods for partial differential equations and stochastic systems, often addressing challenges in technical textile production, non-equilibrium thermodynamics, and multi-physics simulations. His work bridges microscopic particle-based models with macroscopic continuum descriptions, emphasizing asymptotic methods and domain decomposition techniques. Notable contributions include stochastic fiber lay-down models for nonwoven manufacturing, mesh-free particle methods for granular and rarefied gas flows, and kinetic-based traffic models with applications to autonomous vehicles and crowd control. Current research explores data-driven approaches for coupled systems in socio-economic and biomedical contexts. Prof. Klar’s interdisciplinary projects involve collaborations with industry partners (e.g., in textile engineering) and academic institutions globally. His team develops open-source numerical toolkits for applications ranging from radiation therapy optimization to climate-resilient infrastructure design. Recent efforts focus on AI-driven parameter estimation for high-dimensional PDE systems and uncertainty quantification in multi-scale modeling.

• Computational Electromagnetics
• Numerical Methods for Partial Differential Equations
• Wave Propagation
• +۳ مورد دیگر

Dimitrios Gouliermis is affiliated with the Universität Heidelberg's Zentrum für Astronomie (Center for Astronomy) and the Max Planck Institute for Astronomy, where he conducts research in computational electromagnetics and numerical methods for partial differential equations. His work focuses on fast algorithms for solving scattering problems in layered media, integral equation methods, and metamaterials. He has held roles including invited speaker at the International Congress on Industrial and Applied Mathematics (ICIAM 2023) and has presented at numerous conferences globally. His research interests span computational physics and optics, with a strong emphasis on developing efficient numerical techniques for wave propagation and electromagnetic phenomena. Recent work includes advancements in fast multipole methods, dyadic Green's functions, and stochastic methodologies for meta-material design. Dr. Gouliermis has collaborated with institutions such as the University of Massachusetts Dartmouth, Dartmouth College, and Peking University, contributing to the computational science community through algorithm development and high-performance computing initiatives. His research has been published in leading journals like Journal of Computational Physics and SIAM Journal on Scientific Computing .

Jeong-Hoon Songمشاهده پروفایل

دانشیار

• Computational Multiscale Analysis
• Computational Multiphysics Analysis
• Computational Material Design
• +۳ مورد دیگر

Jeong-Hoon Song is an Associate Professor in the Department of Civil, Environmental and Architectural Engineering at the University of Colorado Boulder. His research focuses on computational multiscale and multiphysics analysis, particularly in failure mechanisms, material design, and real-time model reduction. He holds a PhD from Northwestern University (2008) and MS/BS degrees from Yonsei University (2003/2001). Prof. Song’s work bridges atomistic simulations with continuum mechanics to predict material behavior under coupled thermal and mechanical loads. His lab (CM2 Lab) develops advanced numerical methods like the extended finite element method (XFEM) and strong-form meshfree collocation approaches for fracture mechanics, multiphase solidification, and additive manufacturing processes. Professional Memberships: ASCE EMI, USACM, IACM Key Research Themes: Multiscale modeling, computational material synthesis, and real-time simulation techniques Recent publications highlight advancements in frictional contact modeling, nano-crystal solidification, and continuum point cloud methods. His research emphasizes interdisciplinary applications, including aerospace and civil infrastructure durability under extreme conditions.

• Partial Differential Equations
• Computational Fluid Dynamics
• Numerical Analysis
• +۳ مورد دیگر

Associate Professor Fabrice Colin is affiliated with the Bharti School of Engineering & Computing at Laurentian University, specifically within the Department of Mathematics and Computer Science. He joined Laurentian University in summer 2005 after a one-year professorship at Université de Moncton, bringing expertise in mathematical modeling and computational methods. His educational background includes a B.Sc., M.Sc., and Ph.D. in Mathematics, with doctoral studies completed in 2002 at Université de Sherbrooke under Professors Tomasz Kaczynski and Michel Willem. Professor Colin's research centers on partial differential equations (PDEs) as foundational tools for modeling phenomena ranging from fluid dynamics to quantum mechanics and biological processes. He maintains an active collaboration with Professor Richard Égli on real-time numerical simulation of fluids (water, smoke, fire), with direct applications in computer graphics, video games, and film production. This work bridges theoretical mathematics and practical computational challenges in visual effects. His publication portfolio demonstrates consistent focus on meshfree methods and fluid dynamics, with recurring themes in stabilization techniques, kernel-based approaches, and nonlinear systems. The research trajectory shows increasing emphasis on real-time computational efficiency for graphics applications while maintaining mathematical rigor in PDE analysis. His scholarly recognition includes: Dean of the Faculty of Science Honor List 2003 (University of Sherbrooke) for doctoral research excellence Dean of the Faculty of Science Honor List 1997 (University of Sherbrooke) for master's research excellence Professor Colin has supervised three master's students through his collaboration with Richard Égli and currently co-supervises two doctoral candidates—one with Professor Kaczynski in mathematical analysis, and another with Professors Benaissa and Megrez in applied computational methods. His research program receives partial funding from the Natural Sciences and Engineering Research Council of Canada (NSERC), supporting both theoretical investigations and practical simulation development. He operates within Laurentian's computational mathematics research environment, contributing to interdisciplinary projects that connect pure mathematics with computer graphics applications through ongoing industry-relevant fluid simulation work.

Anamika Pandeyمشاهده پروفایل

پژوهشگر ارشد

• Uncertainty quantification
• Bayesian inference
• Deterministic fluid dynamics
• +۵ مورد دیگر

Anamika Pandey is a Postdoctoral Researcher at the Chair for Mathematics for Uncertainty Quantification at RWTH Aachen University, where she has been working since November 2018. Prior to this position, she began collaborating with Prof. R. Tempone at King Abdullah University of Science and Technology in Saudi Arabia in 2017. She earned her PhD from Universität Kaiserslautern under the supervision of Prof. A. Klar. Her research focuses on uncertainty quantification, Bayesian inference, deterministic and stochastic fluid dynamics, and numerical methods for differential equations. She specializes in meshfree numerical methods, which provide flexible computational approaches for complex physical systems where traditional grid-based methods face limitations. Her work bridges theoretical mathematics with practical applications in fluid dynamics and mathematical biology. Dr. Pandey's publications demonstrate expertise in developing and analyzing numerical methods for systems involving randomness and uncertainty. Her research shows particular strength in applying meshfree techniques to fluctuating hydrodynamics, Brownian dynamics, and biological aggregation models. The trend in her work moves from foundational meshfree methods toward increasingly complex applications involving uncertainty quantification and multiscale phenomena. Her collaborative work spans multiple institutions and disciplines, reflecting the interdisciplinary nature of modern computational mathematics. She has contributed to research in mathematical biology through her analysis of the Keller-Segel system, which models chemotaxis (cell movement in response to chemical signals), and in geophysics through her work on seismic wave propagation under uncertainty. Dr. Pandey maintains active research collaborations with mathematicians and scientists across Germany and internationally, contributing to the vibrant research community in computational mathematics and uncertainty quantification.