جست‌وجوی استاد و پژوهشگر

Vladimir Kazeevمشاهده پروفایل

استادیار

• Numerical Analysis
• Tensor Methods
• Partial Differential Equ to the data-driven solution of PDEs
• +۳ مورد دیگر

Vladimir Kazeev is an Assistant Professor at the Faculty of Mathematics, University of Vienna , where he has held a faculty position since 2019. He also held previous academic appointments as a Szegő Assistant Professor at Stanford University (2017–2019), a postdoctoral researcher at the University of Geneva (2015–2017), and research positions at ETH Zurich (2011–2015), Russian Academy of Sciences (2008–2011), and Moscow Institute of Physics and Technology (2009). His research focuses on adaptive, data-driven numerical methods for differential equations, nonlinear low-parametric approximation, and numerical linear algebra. His work intersects computational mathematics, tensor methods, and high-dimensional problem-solving, particularly in the context of partial differential equations (PDEs) and stochastic modeling. The 15 most recent publications reveal a strong emphasis on quantized tensor-structured methods for PDEs, low-rank approximations, and high-dimensional numerical analysis. His research spans theoretical advancements in tensor decomposition, practical applications in chemical reaction networks, and novel discretization techniques for multiscale and degenerate diffusion problems. Scientific awards include the prestigious ETH Medal for outstanding doctoral theses (2016) Russian Academy of Sciences Medal for outstanding student works in mathematics (2011) Advising and teaching activities include supervising Jason Zhu (Stanford, 2019) and Simon Etter (ETH Zurich, 2014), as well as teaching advanced courses in tensor methods, numerical analysis, and PDEs at the University of Vienna, Stanford University, and the University of Geneva. His service to the community includes peer review for 15+ journals and co-organizing minisymposia at SIAM meetings.

Ilaria Perugiaمشاهده پروفایل

استاد

• Numerical methods for PDEs
• Finite element methods
• Discontinuous Galerkin methods
• +۶ مورد دیگر

Ilaria Perugia is a University Professor (Univ.-Prof.) and Chair of Numerics of PDEs at the Department of Mathematics, Faculty of Mathematics, University of Vienna. She also serves as Deputy Head of the Research Platform Erwin Schrödinger International Institute for Mathematics and Physics. Her research focuses on numerical methods for partial differential equations with applications in computational physics and engineering. Professor Perugia's primary research interests include: Numerical methods for PDEs Finite element methods Discontinuous Galerkin methods Trefftz methods Virtual element methods Space-time methods Computational electromagnetics Wave propagation problems Nonlinear reaction-diffusion problems Her work spans theoretical analysis, algorithm development, and practical implementation of numerical methods for solving complex physical phenomena. Her recent publications demonstrate a strong focus on space-time methods, virtual element methods, and structure-preserving discretizations for wave equations, heat equations, and other PDEs. She has made significant contributions to the development of stable and efficient numerical schemes that preserve important physical properties of the underlying continuous problems, particularly in the context of wave propagation and computational electromagnetics. Professor Perugia leads a research group comprising several researchers and students including Mattia Corti, Matteo Ferrari, Monica Nonino, Andrea Scaglioni, Paul Stocker, Enrico Zampa, and Marco Zank. Her group actively collaborates on projects related to numerical analysis and scientific computing, with particular emphasis on developing novel discretization techniques for challenging PDE problems.

Süli Endreمشاهده پروفایل

استاد

• Free-discontinuity problems
• Computational modelling of fracture
• Quasi-continuum methods
• +۱۰ مورد دیگر

Endre Süli is a Professor of Numerical Analysis at the University of Oxford, affiliated with Worcester College and Linacre College. He has held various academic roles since 1985, including Fellowships and Tutorships in Mathematics. University Education: B.Sc. in Mathematics, University of Belgrade (1974-1978) M.Sc. in Mathematics, University of Belgrade (1978-1980) Ph.D. in Mathematics, University of Belgrade (1985) M.A., University of Oxford (1985) British Council Visiting Student, Reading University and University of Oxford (1983/84) Süli's research focuses on numerical methods for partial differential equations (PDEs), with expertise in finite element methods, adaptive algorithms, error control, and computational modeling of fractures and non-Newtonian fluids. His work bridges mathematical theory and practical applications in fluid dynamics and material science. His recent publications emphasize finite element approximations, nonlinear PDEs, and stochastic models for polymer dynamics. Themes include multiscale methods, tensor-sparsity for high-dimensional problems, and compressible flow simulations. Scientific Awards: Fellow of the Royal Society (2021) London Mathematical Society Naylor Prize and Lectureship (2021) Pro Urbe Prize, City of Subotica (2021) SIAM Fellow (2016) Member, Academia Europaea (2020) Foreign Member, Serbian National Academy of Sciences and Arts (2009) IMA Service Award (2011) Fellow, European Academy of Sciences (EurASc) (2010) Fellow, Institute of Mathematics and its Applications (2007) London Mathematical Society/New Zealand Mathematical Society Forder Lecturer (2015) Professor Hospitus, Charles University, Prague (2012) Distinguished Visiting Chair Professor, Shanghai Jiao Tong University (2013) Invited Speaker, International Congress of Mathematicians, Madrid (2006) Süli has supervised numerous research projects and held visiting appointments globally. His contributions to numerical analysis span foundational work on error estimation, nonlinear stability, and advanced computational frameworks for complex physical systems.

Eitan Tadmorمشاهده پروفایل

استاد

• Nonlinear Conservation Laws
• Spectral Methods
• Kinetic Theory
• +۵ مورد دیگر

Eitan Tadmor is a Distinguished University Professor at the Department of Mathematics and Institute for Physical Science & Technology at the University of Maryland. He holds the 2024 Chaire d'excellence at Sorbonne University's Fondation Sciences Mathématiques de Paris, and has served as Director of multiple research centers including the Center for Scientific Computation and Mathematical Modeling (2002-2016) and The Sackler Institute of Scientific Computation (1993-1996). Current: University of Maryland (2005-present) Previous: UCLA (1995-2002), Tel-Aviv University (1989-1995), CalTech (1980-1982) His research spans nonlinear conservation laws , entropy-stable schemes , collective dynamics , spectral methods , and multiscale modeling . He pioneered the spectral viscosity method and developed stability criteria for numerical schemes. Recent publications focus on swarm-based optimization , Euler-Poisson equations , and hydrodynamic alignment with over 15000 citations. His work on kinetic formulations and regularizing effects in PDEs has become foundational in computational mathematics. 2022 Norbert Wiener Prize (AMS-SIAM) 2022 Gibbs Lecturer (AMS) 2015 Peter Henrici Prize (SIAM-ETH) 2013-2021 Fellow of AMS/SIAM NSF grants (1999, 2008-2012, 2012-2020) He developed CentPack software for hyperbolic conservation laws and co-authored influential review papers on numerical methods and mathematical modeling. His collaborative work with institutions like IPAM, KI-Net, and ETH-ITS demonstrates international scientific leadership.

Christa Cuchieroمشاهده پروفایل

استاد

• Mathematical Finance
• Stochastic Processes
• Risk Management
• +۶ مورد دیگر

Christa Cuchiero is a Professor at the Department of Statistics and Operations Research , University of Vienna , and an elected member of the Austrian Young Academy (Junge Akademie) since 2020. Her research bridges rigorous mathematics and cutting-edge applications in finance, machine learning, and stochastic analysis. Education: Christa earned her M.Sc. in 2006 from TU Wien with a thesis on affine interest-rate models, her Ph.D. in 2011 from ETH Zürich on affine and polynomial processes, and completed her Habilitation at the University of Vienna in 2018 on high-dimensional finance beyond classical paradigms. Research Interests: Her work centers on affine and polynomial processes , stochastic portfolio theory , signature methods , and infinite-dimensional stochastic analysis . Recent projects explore signature-based neural SDEs for option calibration, measure-valued diffusions for energy markets, and universal approximation properties of signature transforms. Awards & Recognition: Among her accolades are the FWF START Award 2019 , the Bruti-Liberati Visiting Fellowship 2018 , the ETH Medal 2012 for an outstanding Ph.D. dissertation, and the Prix de l’Institut Europlace de Finance 2017 for the best paper in finance. Contact: christa.cuchiero@univie.ac.at , Kolingasse 14-16, 05.47, 1090 Wien, Austria.

• Computational Mathematics
• Numerical Analysis
• Finite Element Methods
• +۳ مورد دیگر

Prof. Joachim Schöberl is a faculty member at TU Wien's Faculty of Mathematics and Geoinformation, leading the Scientific Computing and Modelling research group. His academic career includes roles as a university professor (Univ.Prof.) with engineering and technical doctorates (Dipl.-Ing., Dr.techn.). Research focuses on advanced numerical methods, including finite element methods, computational fluid dynamics, and partial differential equations. He has pioneered high-order schemes for fluid-structure interaction, shell mechanics, and electromagnetic simulations. Notable contributions include the NGSolve finite element library and innovative approaches to curvature approximation in discrete geometry. Recent work emphasizes nonlinear elasticity modeling, fractional diffusion problems, and shape optimization for biomembranes. His team collaborates on projects like metascreen upscaling, micromorphic continuum models, and eddy current simulations in laminated materials. Prof. Schöberl advises PhD students researching mixed finite element methods, fractional operators, and computational mechanics. His lab develops open-source tools for high-performance scientific computing.

Martin Hairerمشاهده پروفایل

استاد

• Stochastic analysis
• PDE theory
• Probability theory
• +۵ مورد دیگر

Martin Hairer is a Professor of Pure Mathematics at Imperial College London and EPFL (École Polytechnique Fédérale de Lausanne). He has held significant academic positions, including Regius Professor at the University of Warwick and Professor at the Courant Institute, NYU. His research focuses on stochastic analysis, probability theory, and partial differential equations. Education: B.Sc., M.Sc., and Ph.D. in Physics from the University of Geneva (1998-2001) Martin Hairer’s research interests span Stochastic Partial Differential Equations (SPDEs), Rough Path Theory, and Regularity Structures, with applications in mathematical physics and statistical mechanics. His recent publications emphasize stochastic analysis and SPDEs, particularly the development of Regularity Structures and Rough Path Theory, enabling the rigorous understanding of singular SPDEs and nonlinear dynamics. Scientific Awards: Breakthrough Prize in Mathematics (2021) Fields Medal (2014) Fermat Prize (2013) Royal Society Wolfson Research Merit Award (2009) LMS Whitehead Prize (2008) Martin Hairer actively contributes to education through lecture notes and seminars, including courses on SPDEs and stochastic analysis. He also develops mathematical software.

• Nonlinear Partial Differential Equations
• Mathematical Physics
• Semiconductor Theory
• +۷ مورد دیگر

Ansgar Jüngel is a Full Professor for Analysis of Nonlinear Partial Differential Equations (PDEs) at the Technische Universität Wien (TU Vienna), affiliated with the E101-Institute for Analysis and Scientific Computing. His academic journey includes roles at universities in Berlin, Konstanz, Mainz, and Vienna since 1991. He specializes in mathematical analysis of cross-diffusion systems, entropy methods, semiconductor models, and quantum fluid dynamics. Notable achievements include an ERC Advanced Grant (2021) and the Tsungming-Tu Award (2011). Research focuses on nonlinear PDEs with applications in physics, engineering, and biology, emphasizing rigorous existence theory, numerical methods, and entropy-based approaches. Recent projects include 'Emerging network structures and neuromorphic applications' and 'Taming complexity in partial differential systems.' His teaching includes courses on partial differential equations, calculus of variations, and computational finance. Publications span over 200 works, with key contributions on cross-diffusion models, quantum hydrodynamics, and energy-transport systems. He has supervised numerous PhD students and collaborates internationally on topics like semiconductor simulations and stochastic interacting particle systems. Grants include an FWF Special Research Programme and ERC funding.

Otto Felixمشاهده پروفایل

استاد

• Micromagnetics
• Coarsening
• Stochastic Homogenization
• +۳ مورد دیگر

Felix Otto is a Professor and Director at the Max Planck Institute for Mathematics in the Sciences (Leipzig, Germany) since 2010. Previously, he held Full Professorships at the University of Bonn (1999–2010) and the University of California, Santa Barbara (1998–1999). His research focuses on applied mathematics, including micromagnetics, coarsening dynamics, stochastic homogenization, and hydrodynamic limits. He has received prestigious awards such as the Gottfried Wilhelm Leibniz Prize (2006) and the Max Planck Research Prize (2001). Education: 1993 PhD in Mathematics (advisor S. Luckhaus), University of Bonn 1990 Diploma in Mathematics (advisor G. Dziuk), University of Bonn Research interests emphasize the interplay between analysis, probability, and physics, particularly in understanding complex systems through rigorous mathematical methods. His work on gradient flows and optimal transport has led to foundational contributions in applied mathematics. Awards: Collatz Prize (2007) Membership in Berlin-Brandenburg Academy (2014) Leopoldina Academy (2008) Professional activities include roles as Editor of Archive for Rational Mechanics and Analysis and advisory roles at institutions like the Weierstrass Institute and Fondation Mathématique Jacques Hadamard.

Thomas Franoschمشاهده پروفایل

استاد

• Transport in crowded and disordered media
• Time-dependent nonlinear response
• Active and non-equilibrium systems
• +۳ مورد دیگر

Prof. Dr. Thomas Franosch is a Full Professor of Theoretical Physics at the Universität Innsbruck, Department of Theoretical Physics. His research focuses on transport phenomena in complex systems, including crowded and disordered media, active matter, non-equilibrium systems, and the glass transition. He leads the Bio and Nano Physics research group and has held academic positions at institutions such as Friedrich-Alexander-Universität Erlangen-Nürnberg and Ludwig-Maximilians Universität München. His career includes a PhD from TU München (1996) and postdoctoral research at Harvard University (1998-2000). He has contributed extensively to understanding dynamics in confined colloidal systems, mode-coupling theories for glass transitions, and active particle dynamics. His work bridges theoretical frameworks with applications in soft matter and biophysics. Research interests emphasize time-dependent nonlinear response, anomalous transport, and the interplay between geometry and dynamics in confined environments. Recent publications explore light-induced caging effects in colloids, Anderson localization in fluctuating media, and stochastic dynamics of active particles. Publications span over two decades, with a focus on theoretical models explaining complex fluid behavior. Notable contributions include studies on confined hard-sphere fluids, Lorentz gas models, and active matter systems. His work frequently employs advanced simulation techniques and mode-coupling theory to analyze non-equilibrium phenomena.

Klemens Fellnerمشاهده پروفایل

استاد

• Partial Differential Equations
• Reaction-Diffusion Systems
• Kinetic Equations
• +۶ مورد دیگر

Klemens Fellner is a Professor of Mathematics/Computational Sciences and Group Leader of the Applied Analysis Group at the Institute of Mathematics and Scientific Computing, University of Graz. His research focuses on the analysis of partial differential equations and mathematical modeling across physics, chemistry, and biology. Research Interests: Prof. Fellner's work spans theoretical analysis of nonlinear PDEs (reaction-diffusion, kinetic, and non-local equations) using entropy/duality methods, with applications to: Biological systems (lipolysis, protein localization, stem-cell division) Physical processes (organic photovoltaics, semiconductor modeling) Collective behavior (swarming micro-organisms, aggregation dynamics) Interdisciplinary Mathematics-Arts collaborations Publication Trends: His recent articles (2018-2021) demonstrate strong focus on: Global existence and regularity for reaction-diffusion systems Convergence to equilibrium via entropy methods Drift-diffusion models in semiconductor physics Mathematical biology applications (prion dynamics, lipolysis) Novel approaches for non-local aggregation and hysteresis phenomena Research Leadership: Currently leads the Applied Analysis Group with members including postdocs and PhD students. Key projects: Doctoral School IGDK (International Graduate School) SFB Lipid Hydrolysis (Special Research Program) Mathematics and Arts collaborations Colibri research platform Supervises PhD candidate Reymart Lagunero studying generalized reaction-diffusion systems.

• Mathematical Finance
• Stochastic Processes
• Affine Processes
• +۵ مورد دیگر

Christa Cuchiero is a Professor at the Department of Statistics and Operations Research, Faculty of Business, Economics and Statistics, University of Vienna. Her research spans Mathematical Finance, Stochastic Processes, and Machine Learning applications in finance. She has over 48 publications, including recent work on signature-based models for SPX/VIX options, polynomial McKean-Vlasov SDEs, and infinite-dimensional Wishart processes. Her projects include 'Dynamic Uncertainty Modeling in Finance' and a long-term study on 'Universelle Strukturen in Finanzmathematik' (2020–2028). Research Interests: Signature methods for financial modeling Affine and polynomial processes Machine learning in finance Measure-valued stochastic differential equations Volterra equations and rough path theory Portfolio optimization and risk management Scientific Awards: Bruti-Liberati Visiting Fellowship (2018) Fellow at the Center for Advanced Study (CAS), Norwegian Academy of Science and Letters (2024) ETH Medal for Ph.D. thesis (2012) Recent Publications (2023–2025) focus on signature methods, stochastic portfolio theory, energy markets, and robust calibration techniques. Her work integrates advanced mathematical theory with practical financial applications, emphasizing nonlinear SPDEs, polynomial models, and machine learning frameworks.

Lukas Einkemmerمشاهده پروفایل

استاد

• Numerical Analysis
• Plasma Physics
• Computational Mathematics
• +۳ مورد دیگر

Prof. Lukas Einkemmer is a faculty member at the University of Innsbruck, holding a position in the Institute of Mathematics. He specializes in numerical analysis, plasma physics, and high-performance computing. His work focuses on developing advanced numerical methods for solving complex kinetic equations and PDEs, with applications in plasma simulation and computational fluid dynamics. Education: He earned a PhD in applied mathematics (2014) and MSc in physics (2013) from the University of Innsbruck, alongside BSc in applied mathematics (2010). He completed research stays at UC Merced and holds notable academic awards, including the SciCADE New Talent Award (2015) and participation in the Heidelberg Laureate Forum (2013). Research & Teaching: His research includes exponential integrators, dynamical low-rank methods, and semi-Lagrangian discontinuous Galerkin schemes. He teaches numerical methods, PDEs, and computational courses at both undergraduate and graduate levels. He also leads training programs in parallel computing (OpenMP/MPI) at the University’s Research Center for High-Performance Computing. Publications & Grants: Over 70 peer-reviewed articles in journals like J. Comput. Phys. and SIAM J. Sci. Comput. , focusing on numerical algorithms and their applications. He has secured grants from FWF and other agencies, advancing methods for plasma physics and kinetic theory. Awards & Recognition: Multiple honors, including the Oberwolfach Leibniz Graduate Student award (2014) and sustained scholarship support for academic excellence.

Laszlo Erdosمشاهده پروفایل

استاد

• Mathematical Physics
• Random Matrix Theory
• Spectral Analysis
• +۵ مورد دیگر

László Erdős is a Professor of Mathematics at the Institute of Science and Technology Austria (IST Austria) since 2013. He previously held positions as C4/W3 Professor at LMU Munich (2003-2013), Associate Professor and Assistant Professor at Georgia Institute of Technology, and was a Member at the Institute for Advanced Study in Princeton (2013-2014). He is an elected Corresponding Member of the Austrian Academy of Sciences (2015). Erdős earned his Diploma in Mathematics from Lorand Eotvos University, Budapest (1990), followed by a PhD in Mathematics from Princeton University (1994) under advisor Elliott H. Lieb. He completed his Habilitation at the University of Vienna (2001). His research focuses on Mathematical Physics, particularly in the areas of Random Matrix Theory, Spectral Analysis of Quantum Systems, and Many-Body Quantum Dynamics. Erdős has made significant contributions to understanding universality in random matrices, quantum dynamics of Bose-Einstein condensates, and spectral properties of disordered quantum systems. His work bridges rigorous mathematical analysis with fundamental questions in theoretical physics. Analysis of Erdős's recent publications reveals a strong focus on spectral statistics of random matrices and their applications to quantum physics. His research demonstrates how universal patterns emerge in complex quantum systems, connecting stochastic processes with spectral theory. The work spans from foundational mathematical results to applications in condensed matter physics and quantum information. His scientific achievements have been recognized with numerous honors including: ERC Advanced Grant (2013) ICM Invited Speaker (2014) SPA Plenary Speaker (2014) QMATH 12 Plenary talk (2013) Aisenstadt Chair, Montreal (2012) ICMP Plenary speaker (2009) ECM Invited Speaker (2008) ICMP Invited Speaker (2000) Elected Corresponding Member of Austrian Academy of Sciences (2015) Geza Grunwald Prize (1995) Annales Henri Poincare Distinguished Paper Award (twice) Erdős has secured significant research funding throughout his career, including an ERC Advanced Grant (2014-2019) worth 1.755M Euro, multiple NSF grants, and participation in major collaborative projects like the Elite Graduate Program TMP and SFB TR12 "Symmetries and Universality." His research group at IST Austria continues to advance the mathematical understanding of quantum systems and random matrices.

• Probability theory
• Financial mathematics
• Financial management
• +۴ مورد دیگر

Univ.Prof. Dr. Rüdiger Frey is a Full Professor for Mathematics and Finance at WU Vienna University of Economics and Business, leading the Institute for Statistics and Mathematics. His academic career includes roles at the University of Leipzig and the University of Zurich. He specializes in quantitative risk management, financial mathematics, and stochastic processes. Roles: Head of Institute for Statistics and Mathematics, Vienna Graduate School of Finance (VGSF) member Education: PhD in Financial Economics (University of Bonn, 1996), Diploma in Mathematics (University of Bonn, 1992) Research focuses on financial risk modeling, credit risk, systemic risk, and quantitative methods. Recent work includes applications of deep learning to financial PDEs and systemic risk analysis. He has authored over 60 peer-reviewed publications and edited volumes, including the influential textbook Quantitative Risk Management . His grants include the WWTF Project and collaborations in stochastic filtering and climate risk modeling. Key awards include the WU Best Paper Award (2021) and recognition for his PhD work. He advises doctoral students and actively participates in international conferences, such as the Vienna Congress on Mathematical Finance.