جست‌وجوی استاد و پژوهشگر

Julien FAVIERمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Fluid-Structure Interaction
• Lattice Boltzmann Method
• +۳ مورد دیگر

Julien FAVIER is a Professor at Aix-Marseille Université, where he directs the M2P2 laboratory and coordinates the H2020 FALCON project on fluid-structure interaction in aeronautics. He also serves as an associate editor for Computers and Fluids . Research Focus: Fluid-structure interaction (FSI), Lattice Boltzmann Method (LBM), Immersed Boundary Method (IBM), turbulent and compressible flows Applications: Biomedical (aortic valves, mucus transport), aerospace (hypersonic flows), and mechanical systems (rupture/fragmentation) Scientific Contributions include: Developing stable explicit FSI solvers for LBM-IBM coupling Modeling metachronal wave dynamics in cilia arrays Advancing compressible LBM with rotating overset grids Studying drag reduction via flexible filament coatings Pioneering non-Newtonian fluid transport simulations Technical Expertise spans: Multi-grid and dual-time stepping techniques GPU acceleration for heterogeneous architectures Viscoelastic and Herschel-Bulkley flow modeling Validation of immersed boundary methods for turbulent flows

Vladimir Rokhlinمشاهده پروفایل

استاد

• Fast Algorithms
• Randomized Algorithms
• Numerical Harmonic Analysis
• +۳ مورد دیگر

Vladimir Rokhlin is the Arthur K. Watson Professor of Computer Science at Yale University, with additional appointments in Applied & Computational Mathematics and Mathematics. His research focuses on fast deterministic and randomized algorithms for computational mathematics, numerical harmonic analysis, and numerical linear algebra. He holds a Ph.D. from Rice University and an M.S. from the University of Vilnius. Key research interests include the development of efficient algorithms for solving integral equations, prolate spheroidal wave functions, and high-accuracy numerical methods. His work has led to breakthroughs in fast multipole methods and low-rank matrix approximations. Rokhlin has been recognized with prestigious awards such as the 2001 Leroy P. Steele Prize, membership in the National Academies of Sciences and Engineering, and the 2014 William Benter Prize. His recent publications emphasize advancements in quadrature formulas, scattering problems, and spectral methods for partial differential equations. His contributions bridge theoretical mathematics and computational science, with applications in electromagnetics, signal processing, and engineering. Current efforts include optimizing algorithms for complex geometries and improving the efficiency of numerical linear algebra techniques.

Malte Helmertمشاهده پروفایل

استاد

• Automated Planning
• Combinatorial Search
• Artificial Intelligence
• +۷ مورد دیگر

Malte Helmert is a Professor at the University of Basel in the Department of Mathematics and Computer Science. He previously worked at the University of Freiburg's Research Group on the Foundations of Artificial Intelligence from 2001 to 2011. His research focuses on intelligent problem-solving , particularly in automated planning , combinatorial search , constraint satisfaction , and NP-hard graph problems . Helmert has made significant contributions to classical planning, including the development of the Fast Downward planning system and its derivatives. Education : Diploma in Computer Science (M.Sc.) from the University of Freiburg (2001) Ph.D. in Computer Science from the University of Freiburg (2006) Research interests encompass the theoretical and practical aspects of automated planning, including heuristic search , optimal planning , abstraction techniques , and domain-independent planning . His work explores merge-and-shrink abstractions , landmark progression , and cost partitioning algorithms for classical planning systems. Recent publications analyze advancements in pseudo-Boolean proof logging , higher-dimensional potential heuristics , and correlation complexity in planning domains. These works often integrate mathematical modeling, algorithm design, and empirical benchmarking. Scientific awards include the AAAI Fellow (2021), EurAI Fellow (2020), multiple Best Paper Awards at ICAPS and SoCS conferences, and the Computers and Thought Award (2011). He also received the VDI-Förderpreis for his Master’s thesis. Software contributions include the Fast Downward planning system, MIPS (now maintained by Stefan Edelkamp), and COVER (a vertex cover solver). Helmert has organized tutorials at ICAPS and AAAI conferences on topics like landmark progression , abstraction heuristics , and LP-based heuristics .

• Magnetic Confinement Fusion
• Plasma Physics
• Tokamak
• +۱۲ مورد دیگر

Jonathan Graves is Professor of Physics at the University of York's School of Physics, Engineering and Technology and Senior Scientist at EPFL's Swiss Plasma Center (SPC-TH). He serves as Editor-in-Chief of Plasma Physics and Controlled Fusion and Director of the Varenna-Lausanne International Workshop in Theory of Fusion Plasmas. His research focuses on magnetohydrodynamic stability, kinetic theory, and transport phenomena in tokamak and stellarator plasmas, with applications to magnetic confinement fusion and ITER/JET experiments. PhD in Theoretical Mechanics (University of Nottingham, 1999), preceded by a first-class joint honors in Electronic Engineering and Mathematics (1996) Senior Scientist at EPFL since 2014 Member of EUROfusion STAC and DEMO Technical Advisory Group since 2015 His research interests include: magnetohydrodynamic confinement and stability of tokamak plasmas, linear and non-linear resistive instabilities, long-wavelength kinetic instabilities, fast particle physics, 3D Alfvenic and wave codes (LEMan), guiding centre theory (VENUS-LEVIS), ion cyclotron resonance heating in 3D (SCENIC code), and impurity transport in rotating plasmas. He has directed PhD theses on topics such as Equilibrium β-limits in stellarators , Heavy impurity transport in 3D perturbed plasmas , and Non-linear MHD modeling in tokamaks . His recent publications emphasize tokamak β-limits, fast ion generation in stellarators, impurity transport under MHD perturbations, and 3D equilibrium modeling. Key tools developed include the VENUS-LEVIS guiding centre code, SCENIC ion cyclotron resonance code, and LEMan Alfvenic wave solver. Collaborative work spans JET, TCV, and Wendelstein 7-X experiments. Graves has contributed to integrated modeling of fusion plasmas, including neutron activation dosimetry, Alfven eigenmode analysis, and disruption prediction algorithms. His team at EPFL and York explores kinetic-MHD interactions, plasma diagnostics via tomography, and optimization of auxiliary heating schemes for reactors.

Terry Jo Leitermanمشاهده پروفایل

دانشیار

• Applied Mathematics
• Fluid Dynamics
• Mathematical Modeling
• +۳ مورد دیگر

Terry Jo Leiterman is an Associate Professor of Mathematics at St. Norbert College. She holds a B.S. from the University of Wisconsin-Oshkosh and a Ph.D. from the University of North Carolina. Her research focuses on applied mathematics with emphasis on fluid dynamics, mathematical modeling in biomedical contexts (e.g., Virtual Lung Project), and population dynamics. She directs the SNC Fluid Mechanics Laboratory and established the Poss-Wroble Summer Undergraduate Fellowship in Mathematics, supporting student research leading to national presentations. Education: B.S., University of Wisconsin-Oshkosh Ph.D., University of North Carolina Research Interests: Dr. Leiterman investigates fluid dynamics phenomena at micro- and macro-scales, including cilia motion modeling and applications to Cystic Fibrosis therapies. She also develops mathematical frameworks for phytoplankton population dynamics and fluid-structure interactions. Her work bridges theoretical models with experimental validation in collaborative environments. Awards: Recognized as a Project NExT Fellow (2006) by the Mathematical Association of America. Advising & Grants: Spearheaded the SNC summer undergraduate research program since 2008, fostering over 40 student presentations at national conferences. Created the Poss-Wroble Fellowship supporting full-time summer research culminating in MathFest presentations. Labs & Teams: Leads the SNC Fluid Mechanics Laboratory in the Gehl-Mulva Science Center, focusing on experimental fluid dynamics and computational modeling.

Xavier Claeysمشاهده پروفایل

استاد

• Wave Propagation
• Mathematical Modeling
• Numerical Analysis
• +۵ مورد دیگر

Xavier Claeys is a Professor at ENSTA Paris, affiliated with the Applied Mathematics Unit (UMA) and the Wave Propagation, Mathematical Study and Simulation (POEMS) research team. His work focuses on the mathematical modeling and numerical analysis of wave propagation phenomena with applications in electromagnetics and acoustics. He maintains an active research program with numerous publications spanning from 2007 to the present, demonstrating sustained scholarly contributions to his field. Dr. Claeys earned his PhD from Université Versailles Saint-Quentin-en-Yvelines in 2008 with a thesis on 'Asymptotics and numerical analysis for wave diffraction by thin wires.' He completed his Habilitation from Université Pierre-et-Marie Curie in 2016 with research on 'Boundary integral equations of time harmonic wave scattering at complex structures.' His academic trajectory shows a consistent focus on developing mathematical frameworks for wave propagation problems. His primary research interests center on the modeling and numerical analysis of linear wave propagation phenomena, particularly in the context of frequency domain electromagnetics and acoustics. His specific technical interests include domain decomposition methods, boundary element methods, scientific computing, multi-scale problems, and singularities in elliptic problems. Dr. Claeys has developed specialized software tools including bemtool (a boundary element library) and ddmtool (a domain decomposition library) to support his research, demonstrating his commitment to translating theoretical advances into practical computational tools. Analysis of his publication record reveals a consistent evolution toward increasingly sophisticated domain decomposition approaches, particularly optimized Schwarz methods and multi-trace boundary integral formulations. His work demonstrates a strong theoretical foundation combined with practical implementation considerations, with applications spanning electromagnetic scattering, acoustic wave propagation, and metamaterial analysis. Recent publications show increasing focus on addressing computational challenges related to complex geometries and physical boundaries. Dr. Claeys has led significant research projects including 'NonlocalDD' funded by the French National Research Agency (ANR), which investigated boundary integral equations in conjunction with domain decomposition. He was previously involved in the ANR-funded 'METAMATH' project focused on the modeling and numerical analysis of metamaterials. His research contributes to ENSTA Paris's broader research focus on cutting-edge areas with applications in sustainable energy, transportation, and defense. His work aligns particularly with the 'Waves and Vibrations' research axis at ENSTA Paris, which encompasses activities related to wave propagation phenomena with applications including seismic effects on infrastructure, non-destructive testing, and acoustic management in transportation and energy sectors. Dr. Claeys' theoretical contributions provide foundational support for these applied research directions through advanced mathematical modeling and numerical methods development.

Heather Wilberمشاهده پروفایل

استادیار

• Approximation Theory
• Direct Solvers and Higher Order Methods for PDEs
• Nonlinear Approximation Methods
• +۳ مورد دیگر

Heather Wilber is an Assistant Professor in the Department of Applied Mathematics at the University of Washington. Her research focuses on the intersection of approximation theory, numerical linear algebra, and scientific computing, with active projects in fast transforms, Fourier integral operators, direct solvers for elliptic PDEs, and nonlinear approximation methods. She holds a PhD and has received prestigious awards including the Householder Prize and AWM Dissertation Prize. Her work includes software development such as Structmats and REfit, advancing numerical methods for structured matrices and rational approximations. She teaches courses in scientific computing and applied linear algebra, and her research contributions span topics like Sylvester matrix equations and Zolotarev rational functions.

Hengguang Liمشاهده پروفایل

استاد

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۷ مورد دیگر

Hengguang Li is Professor and Chair of Mathematics at Wayne State University's College of Liberal Arts and Sciences, also directing the Computation, AI, and Data Science (CAD) Initiative with contact at li@wayne.edu. Education: Ph.D. in Mathematics, The Pennsylvania State University Ph.D. Minor in High Performance Computing, The Pennsylvania State University B.S. in Computational Mathematics, Peking University His research centers on Numerical Analysis and Scientific Computing with specialization in Partial Differential Equations, particularly numerical methods for singularities. He develops Fast Numerical Solvers and Multigrid Methods while integrating Data Science and Artificial Intelligence through High-Performance Computing frameworks. Accolades include: Continuous NSF Research Grants Academy of Scholars Elected Member Career Development Chair Award IMA General Membership Air Force Faculty Fellowship Silicon Mechanics Research Cluster Award AMS Fan China Exchange Award Supported by continuous NSF funding and Air Force collaboration, his CAD Initiative leadership drives computational research integration across disciplines.

• Inverse Problems
• Scattering Theory
• Partial Differential Equations
• +۲ مورد دیگر

Thi Phong Nguyen is an Assistant Professor in Mathematical Sciences at the New Jersey Institute of Technology. His research focuses on inverse problems, scattering theory, and computational mathematics with applications to wave propagation and imaging. Research develops novel mathematical methods including Tikhonov regularization techniques for fractional derivative problems, fast imaging algorithms for periodic media, and sampling methods for anisotropic scatterers. Current investigations address inverse source problems for fractional PDEs. Publications demonstrate consistent focus on regularization theory for ill-posed inverse problems, particularly in scattering scenarios involving periodic structures and anisotropic materials. Recent work extends methods to time-space fractional parabolic equations.

Mahdi Esmaily Moghadamمشاهده پروفایل

استادیار

• Computational Fluid Dynamics
• Cardiovascular Mechanics
• Biological Flows
• +۱۲ مورد دیگر

Mahdi Esmaily Moghadam is an Assistant Professor in the Sibley School of Mechanical and Aerospace Engineering at Cornell University, where he joined in January 2018. His research bridges computational mechanics and cardiovascular medicine, focusing on developing high-fidelity tools for surgical design and disease modeling. Research Interests: His work centers on computational fluid dynamics (CFD), cardiovascular mechanics, and biological flows. He develops advanced numerical methods—such as finite-element and time-spectral solvers—for simulating complex fluid-solid interactions in the cardiovascular system. Key areas include multi-scale modeling of red blood cells, optimization of surgical procedures like the Norwood and Assisted Bidirectional Glenn, and investigating hemolysis and turbulence effects in pediatric heart patients. He also explores cerebrospinal fluid dynamics as a potential biomarker for Alzheimer’s disease. Publication Trends: His recent articles (2023–2025) emphasize accelerating cardiovascular simulations using frequency-domain solvers, cell-resolved modeling of red blood cells, and improved stabilization techniques for CFD. These works reflect a strong trend toward real-time, high-accuracy predictive tools with direct clinical applications. Scientific Awards: Postdoctoral fellowship, Center for Turbulence Research, Stanford University Outstanding Graduate Student award, UCSD MAE Department Kaplan Fellowship, UCSD Best B.Sc. Thesis Award, Iranian Society of Mechanical Engineering Advising and Grants: While specific students are not listed, his lab conducts extensive research in computational cardiovascular engineering, supported by academic fellowships and likely federal or institutional grants. His collaborations with clinical researchers indicate interdisciplinary funding sources. He has mentored work on surgical optimization, hemodynamics, and multi-scale modeling. Labs and Teams: He leads a research group focused on computational cardiovascular mechanics at Cornell. His prior work at the Center for Turbulence Research (Stanford/NASA) and collaborations with the Predictive Science Academic Alliance Program highlight involvement in large-scale, multi-institutional research teams.

Ramesh Harjaniمشاهده پروفایل

استاد

• Analog Circuit Design
• RF Circuit Design
• Wireless Communications
• +۷ مورد دیگر

Ramesh Harjani is the Edgar F. Johnson Professor in the Department of Electrical and Computer Engineering at the University of Minnesota. He maintains an active research program with numerous ongoing projects and publications, and is currently accepting PhD students. His office is located in Kenneth H. Keller Hall on the University of Minnesota campus in Minneapolis. Dr. Harjani received his educational training at prestigious institutions globally: B.Tech in Electrical and Electronics Engineering from Birla Institute of Technology, Pilani, India (1982) MTech in Electrical Engineering from Indian Institute of Technology, New Delhi (1984) PhD in Electrical and Computer Engineering from Carnegie Mellon University (1989) Professor Harjani's research focuses on analog and RF circuit design for communication systems with particular emphasis on CMOS technologies. His work spans both wireless and wired communication domains, with current efforts directed toward high-performance front-end components for broadband and multi-standard wireless systems, as well as next-generation high-speed wired communication systems. His research group also investigates specialized areas including data converters, sensor interface circuits, analog circuit synthesis, and micro-power analog design. Recent publication trends show continued innovation in analog circuit design methodologies, with emphasis on improving performance metrics while addressing modern semiconductor challenges like FinFET self-heating effects. His work bridges theoretical circuit design with practical implementation challenges in advanced technology nodes, particularly 65nm CMOS processes. The research demonstrates strong industry relevance with applications in wireless communications, signal processing, and high-speed data conversion. Professor Harjani leads multiple significant research projects: Scalable Ultra-Low Variation Analog-Time Neural Network (S-UATN) Accelerator (2025-2025) Passive Tile Architecture for MAX (2023-2024) ALIGN Analog Layout Design Suite (2023-2024) Automated Layout Of Analog Arrays In Advanced Technology Nodes (2022-2024) ALIGN: Analog Layout, Intelligently Generated from Netlists (2018-2023) He maintains the Harjani Research Group, which collaborates extensively with industry partners including BAE SYSTEMS, NORTHWESTERN UNIVERSITY, SPAWAR, and THE NATIONAL SCIENCE FOUNDATION, demonstrating strong connections between academic research and practical engineering applications.

• Environmental Fluid Mechanics
• Wildfire Propagation Modeling
• Computational Wind Dynamics
• +۵ مورد دیگر

Professor Rob Stoll at the University of Utah's Mechanical Engineering Department specializes in environmental fluid dynamics, wildfire modeling, and urban/agricultural canopy flows. His work bridges computational modeling with field measurements across diverse domains. Develops GPU-accelerated QES simulation tools Focuses on wildfire-atmosphere coupling Advances low-cost sensor networks for environmental monitoring Research Trends revealed through 15 recent publications include: Wildfire propagation under heterogeneous terrain/fuel 3D wind modeling in vineyards and urban environments Particle transport in sparse and row-organized canopies Turbulence characterization in stable boundary layers Open-source hardware for atmospheric sensing Scientific Contributions 2008: Best PhD Dissertation (University of Minnesota) 2017-2022: NSF Grant for wildfire modeling 2020-2025: Systems approach for carrot blight management 2023-2026: Vineyard smoke exposure modeling grants Teaching Activities include graduate courses in Numerical Methods for Engineering Systems and advising PhD/Master's theses since 2015.

Andreas Paul Eberhard Kloecknerمشاهده پروفایل

دانشیار

• Scientific Computing
• Parallel Computing
• Numerical Techniques
• +۷ مورد دیگر

Andreas Paul Eberhard Kloeckner is an Associate Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), where he has been serving since 2013 (promoted to Associate Professor in 2019). He also holds an affiliate faculty appointment in the Department of Electrical and Computer Engineering since 2016. His academic journey includes a PhD in Applied Mathematics from Brown University (2010), an MSc from Brown University (2006), and a Diplom in Applied Mathematics from Universität Karlsruhe (2005). Prior to joining UIUC, he was a Courant Instructor at the Courant Institute of Mathematical Sciences at New York University. Dr. Kloeckner's research focuses on high-order accurate integral equation methods, fast algorithms for elliptic boundary value problems, and code transformation for high-performance scientific computing. His work bridges mathematical theory with practical implementation, with particular emphasis on GPU computing and parallel architectures. He has made significant contributions to the development of open-source scientific software, most notably PyCUDA and PyOpenCL, which have become widely used tools in the scientific computing community. His publication record shows a consistent focus on advancing numerical methods for scientific computing, with recent work emphasizing code generation techniques, fast integral equation solvers, and optimization of algorithms for modern hardware architectures. The trajectory of his publications reveals a progression from foundational work on GPU-based discontinuous Galerkin methods toward increasingly sophisticated approaches for integral equation methods and automatic code generation. Among his notable recognitions is the 2017 National Science Foundation CAREER Award, which supports his work on general-purpose, high-order integral equation methods for computer simulation in engineering. His research has been published in prestigious venues including SIAM Journal on Scientific Computing and has influenced both academic research and practical applications in scientific computing. Dr. Kloeckner has advised numerous graduate students through completion of their PhD and MS degrees, with alumni moving to positions at Apple, NVIDIA, Rice University, and other leading institutions. His research group maintains an active portfolio of open-source software projects that advance the state of scientific computing infrastructure.

• 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 .

Adrien MERLINIمشاهده پروفایل

پژوهشگر

• Computational Electromagnetics
• Integral Equations
• Neuroimaging
• +۳ مورد دیگر

Adrien MERLINI is a Researcher at IMT Atlantique's Microwave Department in Brest, France. His work focuses on computational electromagnetics, integral equation methods, and neuroimaging applications. He specializes in developing numerical techniques for low-to-high-frequency electromagnetic modeling, preconditioning strategies for integral equations, and machine learning-enhanced solutions for inverse problems. His research bridges fundamental theory and applied engineering, addressing challenges in medical imaging, material characterization, and high-performance computing. Key areas of expertise include: High-frequency spectral analysis of boundary integral operators Stabilized formulations for low-frequency electromagnetic simulations Supervised learning approaches for electrical source imaging Quasi-Helmholtz projector-based preconditioning techniques Fast direct solvers for integral equations His innovations in numerical methods have advanced applications in brain-computer interfaces, microwave-based medical imaging, and terahertz dosimetry. Collaborative projects include developing the simBCI framework for EEG simulation and the Pythran compiler for accelerating scientific Python codes. Research contributions span over 30 peer-reviewed articles since 2015, with recent emphases on conditioning analysis of electromagnetic integral equations and regularization strategies for neuroimaging inverse problems.