جست‌وجوی استاد و پژوهشگر

Lehel Banjaiمشاهده پروفایل

استاد

• Numerical Analysis
• Computational Mathematics
• Boundary Element Methods
• +۱۶ مورد دیگر

Professor Lehel Banjai is a faculty member at the School of Mathematical and Computer Sciences, Heriot-Watt University, where he has held the position of Professor in Mathematics since 2022. Previously, he served as Associate Professor (2015–2022) and Assistant Professor (2012–2015) at the same institution. Education: Habilitation (University of Dusseldorf, 2013), D.Phil. (Oxford, 2003), BA(Hons) in Mathematics and Computation (Oxford, 2000) His research spans numerical analysis and computational mathematics, focusing on boundary and finite element methods, space-time formulations, and convolution quadrature for time-domain problems. Key areas of interest include wave scattering (acoustic and electromagnetic), Schrödinger equations, fractional differential operators, and high-order numerical schemes. Recent publications highlight his work on Runge-Kutta convolution quadrature, fractional diffusion, nonlinear impedance boundary conditions, and efficient solvers for wave equations. He has collaborated with researchers at institutions such as Max Planck Institute, University of Zurich, and University of Dusseldorf. Students supervised include Brian Hennessy (joint with Emmanuil Georgoulis), Ebraheem Aldahham, Katherine Baker, Jeta Molla (joint with Gabriel Lord), and Oluwaseun Lijoka, among others.

Leslie Greengardمشاهده پروفایل

استاد

• Integral Equation Methods
• Electromagnetics
• Acoustics
• +۵ مورد دیگر

Leslie Greengard is a Silver Professor of Mathematics and Computer Science at New York University's Courant Institute, part of the Faculty of Arts and Science. His research focuses on integral equation methods for electromagnetics, acoustics, plasma physics, and fluid dynamics, with recent work extending to kernel-based methods in statistical inference. He leads the Courant Mathematics and Computing Laboratory and contributes to novel electromagnetic simulation techniques. Education: Ph.D. and M.D. in Computer Science and Medicine from Yale University (1987) B.A. in Mathematics from Wesleyan University (1979) Research Interests: Greengard's group develops fast solvers for complex geometries in electromagnetics and fluid dynamics. Notable contributions include the Fast Multipole Method (FMM) for particle simulations and Quadrature by Expansion (QBX) for layer potential evaluations. His work bridges computational mathematics and applications in physics, engineering, and biomedicine. Recent Article Trends: Recent publications emphasize fast algorithms (e.g., FMM, adaptive Gauss transforms), biomedical applications (e.g., deep brain stimulation modeling), and cosmological simulations. His methods address challenges in high-dimensional data, multiscale problems, and real-time computation. Awards & Recognition: While no specific prizes are listed, his foundational work on FMM has had a transformative impact on computational science. Advising & Collaborations: Collaborations span academia and industry, with co-authors including V. Rokhlin, M. O’Neil, and others. No formal advisees are listed here, though his research involves postdoctoral fellows and graduate students. Labs & Teams: Active in the Courant Mathematics and Computing Laboratory, focusing on electromagnetic simulation and design methodologies.

Kartic Subrمشاهده پروفایل

مدرس ارشد

• Computer Graphics
• Monte Carlo Rendering
• Physics-based Simulation
• +۱۳ مورد دیگر

Kartic Subr is a Senior Lecturer (equivalent to Associate Professor) in the School of Informatics at the University of Edinburgh, where he conducts research at the intersection of computer graphics, machine learning, and robotics. He is affiliated with the Institute of Perception, Action and Behaviour and leads an active research group in physics-aware simulation and AI for scientific discovery. His research interests span Computer Graphics , Monte Carlo Rendering , Physics-based Simulation , Machine Learning , Robotics , and Computational Biology . He has made significant contributions to rendering theory, light transport analysis, BRDF modeling, and simulation of fluids and fractures. Recently, his group has applied deep learning to protein design, achieving notable success in international competitions. The recent publications reflect a strong trend toward interdisciplinary research, combining computer graphics with AI and biology. Key themes include explainable AI for physics-aware interfaces (e.g., CueTip), neural rendering (NeRF), protein design with CNNs, and reward learning in robotics. His group regularly publishes in top venues such as SIGGRAPH, NeurIPS, and IEEE RA-L. Royal Society University Research Fellowship (2014–2024) Lead, GCRF Impact Accelerator (2019) Lead, EPSRC First Grant (2017) Royal Society Challenge Grant (2016) Royal Society Newton International Fellow (2010) Marie-Curie Visitor (2006) Best Paper Honorable Mention, I3D 2012 Best Paper, I3D 2011 Kartic Subr actively supervises PhD students and postdocs, including Leonardo Castorina, Zhiyuan Zhang, and Kevin Denamganaï. Former students have gone on to positions at DeepMind, University of Edinburgh, and industry. He has secured multiple grants, including from the Royal Society and EPSRC. His research group collaborates across disciplines, particularly with biological sciences on protein design. He leads projects on approximate physics for robotics, protein design via deep learning, and interactive rendering systems. The group has developed frameworks like TIMED for de novo protein design and tools for explainable physics-aware assistants.

Jörg Nickمشاهده پروفایل

پژوهشگر

• Partial Differential Equations
• Wave Phenomena
• Numerical Analysis
• +۳ مورد دیگر

Jörg Nick is a Postdoctoral researcher at the Seminar for Applied Mathematics at ETH Zurich, Switzerland. His academic journey includes a Doctorate degree in Mathematics from the University of Tübingen (2023) under Prof. Christian Lubich and an MSc in Mathematics from the same institution (2018). He previously held a postdoctoral position at the University of Tübingen (2023) and was a doctoral researcher there from 2018 to 2023, associated with the Deutsche Forschungsgemeinschaft (DFG) project Wave phenomena: analysis and numerics , specifically Project A2 on numerical methods for wave problems with nontrivial boundary conditions. His research focuses on the numerical analysis of partial differential equations (PDEs), particularly wave scattering and metamaterials. Key areas include integral equations for PDEs, dynamical parametric approximation, numerical methods for time-dependent metamaterials, and inverse problems in wave phenomena. His work often integrates the Boundary Element Method (BEM) and Convolution Quadrature (CQ) to analyze wave scattering and subwavelength resonators. Notable contributions include studies on electromagnetic scattering from dispersive materials, time-periodic coefficients in wave equations, and regularized parametric approximation techniques. His research bridges theoretical developments with practical applications in metamaterials and medical imaging (e.g., anomaly detection in capsule endoscopy using ensemble learning). His academic affiliations include the Collaborative Research Center (CRC) 1173 at Tübingen and current participation in ETH Zurich’s mathematical and computational initiatives. While no formal awards are listed, his prolific publication record reflects sustained contributions to numerical mathematics and applied physics.

Gabriela Jaramilloمشاهده پروفایل

دانشیار

• Nonlinear Partial Differential Equations
• Integro-Differential Equations
• Pattern Formation in Biological Systems
• +۴ مورد دیگر

Gabriela Jaramillo is an Associate Professor in the Department of Mathematics at the University of Houston. Her research focuses on nonlinear partial differential equations, integro-differential equations, and pattern formation in biological and physical systems. She investigates how nonlocal diffusion mechanisms influence pattern formation, particularly in oscillatory media, and explores defects and impurities in such systems. Her teaching roles include advanced mathematics courses such as Partial Differential Equations, Theory of Differential Equations, and Multivariable Calculus at the University of Houston, as well as prior teaching at the University of Arizona and University of Minnesota. She leads research programs such as the Summer REU on pattern formation, supervising students like Sameel Siddiqi, Kevin Sony, and Jared Solomon. Her work emphasizes nonlocal effects in biological systems, including studies on spiral waves, target patterns, and the impact of mutations on ecological models. Recent publications explore topics like spiral wave dynamics in nonlocal oscillatory media and numerical methods for diffusive nonlocal operators. Her research bridges theoretical analysis with computational simulations, addressing challenges in pattern formation across disciplines.

• Numerical Analysis
• Acoustic Waves
• Elasticity
• +۹ مورد دیگر

Letizia Scuderi is a Tenured Associate Professor at the Department of Mathematical Sciences 'GL Lagrange' (DISMA) , Politecnico di Torino. She is affiliated with the College of Mathematical Engineering and contributes to teaching in Chemical and Sustainable Process Engineering, Mathematics for Engineering, and Aerospace Engineering programs. Her research focuses on numerical methods for wave propagation problems, particularly acoustic and elastic waves in bounded and unbounded domains. Scientific Branch: Numerical Analysis (MATH-05/A) Research Interests: Acoustic waves, Elasticity, Integral Equations, Wave Propagation, Computational Methods, etc. She actively collaborates with the Numerical Analysis and Scientific Computing (DISMA) research group. Her work involves coupling Boundary Element Methods (BEM) , Finite Element Methods (FEM) , and Virtual Element Methods (VEM) to solve partial differential equations in complex domains. Recent publications highlight her contributions to: Wave scattering problems Time-domain simulations Non-reflecting boundary conditions Curved virtual elements Convolution quadrature Wavelet-based matrix sparsification She supervises PhD students Davide Collato and Matteo Ferrari , focusing on non-symmetric coupling techniques and wave propagation in unbounded domains.

• Nonlocal Differential Equations
• Fractional Calculus
• Difference Equations
• +۴ مورد دیگر

Dr. Chris Goodrich is a Senior Lecturer at the School of Mathematics and Statistics, UNSW Sydney. He holds a PhD in Mathematics from the University of Nebraska-Lincoln. His research focuses on analytical and theoretical aspects of nonlocal differential equations, fractional calculus, and variational problems, with particular emphasis on operator theory and regularity analysis. Education: PhD Mathematics, University of Nebraska-Lincoln Research Interests: Dr. Goodrich specializes in nonlocal operators and fractional calculus applied to differential/difference equations. His work investigates existence theory, monotonicity properties, and topological analysis of solutions. Key areas include convolution equations, (p,q)-growth conditions in PDEs, and applications of Sobolev inequalities to Kirchhoff-type problems. He maintains strong collaborations with international researchers in fractional analysis and discrete calculus. Publications: His recent articles (2023-2025) demonstrate consistent focus on nonlocal operators, fractional differences, and convolution equations. Predominant themes include topological methods for elliptic equations, monotonicity analysis of fractional operators, and existence/nonexistence theorems for Kirchhoff systems. Analytical techniques leverage convexity, variational principles, and asymptotic characterization across both continuous and discrete frameworks.

David Chappellمشاهده پروفایل

دانشیار

• Computational Mathematical Modelling
• Wave Energy Transport
• Acoustics
• +۷ مورد دیگر

David Chappell is an Associate Professor in Applied Mathematics at the School of Science and Technology, Nottingham Trent University . His research focuses on computational mathematical modeling with applications in acoustics, fluid mechanics, neuroscience, and structural vibrations. Key areas include wave energy transport, uncertainty quantification in vibroacoustic systems, convolution quadrature methods for transient waves, and neural field simulations using isogeometric analysis. Wave energy transport in composite structures Uncertainty quantification in high-frequency dynamics Hybrid numerical-asymptotic methods for wave modeling Neural field modeling on curved brain surfaces Current research is funded by EPSRC (APP46305), Leverhulme Trust, and Innovate UK. He supervises postgraduate research students in mathematics and engineering disciplines.

Anthony P. Austinمشاهده پروفایل

استادیار

• Numerical Linear Algebra
• High-Performance Computing
• Approximation Theory
• +۳ مورد دیگر

Anthony P. Austin is an Assistant Professor in the Department of Applied Mathematics at the Naval Postgraduate School . His research focuses on numerical linear algebra, high-performance computing, approximation theory, and GPU-accelerated algorithms. He has held prior positions at Virginia Tech and Argonne National Laboratory as a J. H. Wilkinson Fellow. His work includes contributions to Chebfun, a software system for numerical computation. Education: D.Phil. in Mathematics , University of Oxford Mathematical Institute (2016) Ph.D. studies with active development in the Chebfun project Research Interests : Numerical methods for large-scale problems, high-order methods for PDEs, and computational techniques leveraging GPUs. His work emphasizes algorithmic innovation and stability in numerical simulations. Recent Contributions : Publications include advancements in spectral factorization, adversarial signal perturbations, and parallel algorithms for partial spectral computations. His seminar co-organization highlights collaboration in early-career faculty research initiatives. Professional Activities : Co-organizer of the NPS Junior Faculty Research Seminar (AY2022/Q3), focusing on fostering interdisciplinary collaboration among early-career faculty.

• Acoustic waves
• Advanced numerical methods
• Convolution integrals
• +۷ مورد دیگر

Silvia Falletta is an Associate Professor at the Department of Mathematical Sciences 'GL Lagrange' (DISMA), Politecnico di Torino. She teaches courses including Numerical Methods for Differential Equations and Finite Element Modelling across disciplines like Chemical Engineering and Aerospace Engineering. Her research focuses on advanced numerical methods for wave propagation problems, particularly in acoustics, elasticity, and seismology. Research Interests: Acoustic waves, Elasticity, Integral equations, Numerical Analysis, Convolution Quadrature, Wavelet techniques. Teaching Roles: Course Lecturer for Finite Element Modelling (2019–2025), Numerical Calculus collaborator, and contributor to PhD programs in Mathematical Sciences. Publications: Specializes in time-domain boundary integral equations, BEM-FEM coupling, and non-reflecting boundary conditions. Recent work includes virtual element methods for wave propagation and wavelet-based matrix sparsification. Students: Supervises PhD candidates Davide Collato and Matteo Ferrari, focusing on non-symmetric coupling of virtual/boundary elements and unbounded domain problems. Contact: Email: silvia.falletta@polito.it ; Phone: +39 0110907506.

• Numerical Analysis
• Partial Differential Equations
• Computational Mathematics
• +۵ مورد دیگر

Matteo Ferrari is a University Assistant Post-Doc in the Faculty of Mathematics at the University of Vienna, Austria, conducting research under Professor Ilaria Perugia's supervision. His position involves advanced numerical analysis and computational mathematics development. Education: Ph.D. in Numerical Analysis, Polytechnic University of Turin, supervised by Professors Silvia Falletta and Letizia Scuderi. His research centers on numerical methods for partial differential equations with emphasis on wave propagation and quantum mechanics. Key specialties include space-time discretization, isogeometric analysis, and coupling techniques between finite element and boundary element methods. He develops unconditionally stable schemes for wave equations and Schrödinger equations while applying virtual element methods to elastic wave problems and complex geometries. Analysis of his 2021-2025 publications reveals consistent innovation in space-time formulations and stability properties, particularly for Hamiltonian wave systems and time-domain scattering problems. His work bridges computational mathematics, physics, and engineering through novel discretization approaches for time-dependent PDEs. He actively contributes to Professor Ilaria Perugia's research group at the University of Vienna, focusing on computational mathematics advancements through collaborative projects and methodological developments.

Zhimin Zhangمشاهده پروفایل

استاد

• Numerical analysis
• Computational mathematics
• Scientific computing
• +۸ مورد دیگر

Zhimin Zhang is a Professor in the Department of Mathematics at Wayne State University's College of Liberal Arts and Sciences, where he has worked since 2002. Previously, he served at Texas Tech University from 1991 to 2000, including as associate professor (1997-2000). He earned a B.S. (1982) and M.S. (1985) in Computational Mathematics from the University of Science and Technology of China, followed by a Ph.D. (1991) in Applied Mathematics from the University of Maryland at College Park. Research Focus : Numerical analysis, computational mathematics, and scientific computing with specialization in finite element methods, finite volume methods, and spectral methods for partial differential equations. Teaching : Regularly teaches Calculus III (MAT2030) and Numerical Methods I (MAT5100). His research trends include: Development of superconvergence techniques for discontinuous Galerkin and immersed finite element methods Advancements in fractional calculus numerical schemes for nonlocal and nonsmooth solutions Innovations in curl-conforming elements for electromagnetic problems Studies on Hamiltonian systems with structure-preserving spectral methods Error analysis for high-order finite element methods in anisotropic and Shishkin meshes Efficient solvers for bihamonic and eigenvalue problems Dr. Zhang serves on multiple editorial boards including: Mathematics of Computation (2009-2017) Journal of Computational Mathematics (since 2007) SIAM Journal on Numerical Analysis (since 2013) Communications on Applied Mathematics and Computation (since 2018) Scientific recognition includes: 2011 Outstanding Graduate Mentor Award 2014 Charles H. Gershenson Distinguished Faculty Fellows Award Continuous NSF funding since 2003 for projects such as "Recovery Type A Posteriori Error Estimates" (DMS-0311807) and "Spectral and Spectral Collocation Methods for Hamiltonian Systems" (DMS-1115530) He maintains active contributions to mathematical culture through editorial roles at journals like Mathematical Culture and Journal of Mathematical Study since 2008 and 2013 respectively.

Dianne P. O'Learyمشاهده پروفایل

استاد

• Scientific Computing
• Numerical Analysis
• Computational Science
• +۶ مورد دیگر

Dianne P. O'Leary is a Professor affiliated with the Department of Computer Science at the University of Maryland. Her work focuses on scientific computing, numerical analysis, and computational science, with a particular emphasis on matrix factorizations, differential equations, and Monte Carlo methods. She authored the textbook *Scientific Computing with Case Studies* (SIAM Press, 2009), which integrates theoretical concepts with practical case studies across physics, engineering, epidemiology, and biology. Her research explores topics such as image deblurring, blind deconvolution, elastoplastic torsion, and iterative methods for solving large linear systems. The book includes nineteen case studies that illustrate algorithm design, mathematical modeling, and software development principles. Notably, the text emphasizes stability, error analysis, and MATLAB implementation grounded in machine arithmetic and memory management. While no explicit scientific awards or student advisees are mentioned in the provided texts, her contributions to computational education and algorithm development are central to her work. Supplementary materials include solution manuals, MATLAB code repositories, and detailed notes on topics like sensitivity analysis, computer memory management, and finite element methods. Her case studies often bridge theory and application, such as modeling epidemics, robot control systems, and structural engineering problems. The book’s structure reflects a commitment to hands-on learning, with units dedicated to dense matrix computations, optimization, Monte Carlo simulations, and sparse matrix techniques for partial differential equations.

• Numerical Analysis
• Applied Mathematics
• Wave Propagation and Scattering
• +۷ مورد دیگر

Penny Davies is a Senior Lecturer in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. Her work sits at the intersection of applied mathematics, numerical analysis, and biomechanical modeling, with a strong emphasis on solving inverse problems in medical imaging and wave scattering. Her research focuses on the numerical approximation of time-dependent boundary integral equations (TDBIE) for wave scattering, elastic stability, and the development of mathematical models for material and tissue mechanics. She applies these methods to Magnetic Resonance Elastography (MRE), aiming to reconstruct elastic properties of biological tissues non-invasively. Her work combines theoretical analysis with computational innovation to produce reliable and efficient algorithms. The recent publications highlight a consistent trajectory in inverse problems, particularly in MRE, and the development of stable and efficient numerical methods for time-domain integral equations. Her work spans both pure mathematical challenges—such as stability in convolution quadrature—and real-world clinical applications, including brain imaging. OBE for services to mathematics (2014 Birthday Honours) Penny Davies has received approximately £130k as Principal Investigator and £790k as Co-Investigator from EPSRC and other bodies. She has supervised research projects, organized workshops, and contributed to national initiatives like the Taught Course Centre. She is actively involved in academic service, including editorial roles and leadership in professional societies. She is a member of the editorial boards of the Journal of Integral Equations and Applications and Royal Society Open Science , and has held leadership positions such as President of the Edinburgh Mathematical Society (2009–2011) and chair of the LMS nominating committee. She also leads the Athena SWAN self-assessment team at her department, promoting gender equality in STEM.

Alexander Riederمشاهده پروفایل

پژوهشگر ارشد

• Numerical Analysis
• Partial Differential Equations
• Finite Element Methods (FEM)
• +۶ مورد دیگر

Alexander Rieder is a Research Fellow and University Assistant in Computational Mathematics at TU Wien's Institute of Analysis and Scientific Computing. His work focuses on numerical methods for partial differential equations, particularly boundary element methods (BEM), finite element methods (FEM), and their applications in wave propagation and fractional calculus. He holds a PhD from TU Wien (2017) and has held postdoctoral positions at TU Wien and the University of Vienna. Notable achievements include the TU Best Paper Award 2020 for his contributions to numerical analysis. Education: Bachelor of Science (BSc), Mathematics, TU Wien (1989) Diploma in Mathematics, TU Wien (2011) Doctorate (Dr.techn.), TU Wien (2017) Research Interests: Alexander specializes in fractional differential operators , hp-adaptive FEM/BEM , and time-domain boundary integral equations . His projects include developing open-source libraries for advanced BEM simulations and studying wave propagation in composite media. Recent work emphasizes convolution quadrature for semigroups and nonlinear wave equations. Teaching: Current courses include Numerics of Partial Differential Equations and Numerical Computation . He oversees seminars on differential equations and computational mathematics, emphasizing practical implementation and theoretical rigor. Projects: Leading the Advanced BEM for Wave Propagation initiative, he designs algorithms to reduce computational effort while improving accuracy in wave simulations. The project also develops an open-source software library for broader academic use.