جست‌وجوی استاد و پژوهشگر

Magdalena E. Musatمشاهده پروفایل

استاد

• Functional Analysis
• Operator Algebras
• Noncommutative Probability Theory
• +۳ مورد دیگر

Magdalena E. Musat is a Professor at the Department of Mathematical Sciences, University of Copenhagen, within the Faculty of Science. She holds a Ph.D. from the University of Illinois at Urbana-Champaign (2002) and has extensive teaching experience across institutions including the University of Copenhagen, University of Southern Denmark, and UC San Diego. Her research focuses on Functional Analysis, Operator Algebras, and their intersections with noncommutative probability, quantum information theory, and group theory. She has organized major conferences like the Harald Bohr Lectures and the ICM Satellite conference on Operator Algebras. Her academic contributions include over 15 publications in top journals such as Inventiones Mathematicae and Communications in Mathematical Physics. She has supervised numerous Ph.D. and Master’s students, including current advisee Rasmus Kløvgaard Stavenuiter. Her work explores topics like quantum channel factorization, Connes embedding problem, and non-commutative L_p-spaces. Musat serves as Head of Studies for the Master’s Program in Mathematics and co-organizes the Department Colloquium. Her teaching spans advanced courses on Functional Analysis, Operator Algebras, and Measure Theory. Professional activities include organizing masterclasses on Sofic Groups and Approximation Properties for Operator Algebras.

• Geometric Group Theory
• Group Rings
• Algebra
• +۶ مورد دیگر

Dawid Kielak is a Professor of Pure Mathematics at the University of Oxford and a Tutorial Fellow at Hertford College, Oxford. He holds a DPhil from the University of Oxford and has held academic positions in Warsaw, Bonn, and Bielefeld before returning to Oxford. His research focuses on geometric group theory, particularly the interplay between group rings, algebraic structures, and topological spaces. He is a member of the Algebra and Topology research groups at Oxford. His research interests include geometric group theory, cohomology of arithmetic groups, ℓ²-invariants, and the study of automorphism groups of free groups. His work is funded by prestigious grants such as the ERC Starting Grant 'Fibring' (2019) and the ERC Consolidator Grant 'HigherHyper' (2024). He has also received awards like the Whitehead Prize (2022) and the Frontiers of Science Award (2023). Key research contributions include studies on Kazhdan constants for Chevalley groups, profinite rigidity of fibring, and coherence properties of groups. His work often bridges algebraic and topological methods, with applications to 3-manifold groups and random groups. He supervises multiple DPhil students and has mentored postdoctoral researchers in areas like ℓ²-Betti numbers and group rings. Teaching responsibilities include pure mathematics tutorials at Hertford College and advanced courses on geometric group theory, 3-manifolds, and ℓ²-invariants at the University of Oxford and Bielefeld University. His lab focuses on collaborative projects in algebraic topology and geometric group theory, with a particular emphasis on virtual fibring and higher Kazhdan properties.

Shuang Gaoمشاهده پروفایل

استادیار

• Control systems
• Evolutionary, learning and adaptive systems
• Optimization and optimal control theories
• +۵ مورد دیگر

Shuang Gao is an Assistant Professor in the Department of Electrical Engineering at Polytechnique Montréal . Prior to joining Polytechnique Montréal, he held postdoctoral and research fellow positions at McGill University and the Simons Institute for the Theory of Computing at UC Berkeley, respectively. His research focuses on control systems , mean field games , network science , and machine learning , with applications in large-scale networks such as social networks, renewable energy systems, transportation, and neural networks. He is affiliated with the Union of Neurosciences and Artificial Intelligence - Quebec (UNIQUE) and the Decision Analysis Study and Research Group (GERAD) . Dr. Gao’s recent publications highlight his work on Graphon mean field games for analyzing and controlling large-scale networked systems Linear quadratic regulation with quantile-dependent cost coefficients Spectral decomposition for optimal control of coupled subsystems Transmission neural networks for approximation and control His work bridges theoretical advancements in optimal control theories and mathematical modeling with practical applications in complex networks. He teaches graduate courses such as ELE6953KE: Network Models, Systems and Games and ELE6210 Control System Design , and serves as course coordinator for ENE8412: Management of Fluctuating Load and Production . His research is available in 23 publications, including 7 journal articles and 16 conference papers.

Daniel Kressnerمشاهده پروفایل

استاد

• Numerical Linear Algebra
• High-Performance Computing
• Matrix Equations
• +۴ مورد دیگر

Prof. Daniel Kressner is a Professor at the École Polytechnique Fédérale de Lausanne (EPFL), holding positions in the School of Basic Sciences (SB), Mathematics Institute (MATH), and the Numerical Algorithms and High-Performance Computing (ANCHP) group. He also leads the SMA-ENS unit within the SB-SMA division. His research focuses on numerical linear algebra, high-performance computing, and tensor approximation methods, with applications in scientific computing and data science. Education details are not explicitly listed, but his career at EPFL includes leadership in key research groups and doctoral programs. He supervises multiple doctoral students, including Alice Cortinovis, Peter Effenberger, and others. Research interests emphasize low-rank methods, matrix equations, and efficient algorithms for large-scale problems. Recent work includes advancements in randomized algorithms, tensor networks, and preconditioning techniques for eigenvalue problems. His publications span high-impact journals like Siam Journal on Matrix Analysis and Applications and Numerical Linear Algebra with Applications, addressing topics such as compressed sensing, multigrid methods, and distributed signal processing. Prof. Kressner advises doctoral candidates and contributes to the Program doctoral Mathématiques (EDMA-GE) committee. His lab, ANCHP, develops software tools for hierarchical matrices and tensor computations, such as the hm-toolbox for HODLR and HSS matrices.

Michael A. Demetriouمشاهده پروفایل

استاد

• Control Systems
• Systems and Controls Engineering
• Distributed Parameter Systems
• +۷ مورد دیگر

Michael A. Demetriou is a Professor of Aerospace Engineering at Worcester Polytechnic Institute (WPI). He holds a PhD in Electrical & Computer Engineering from the University of Southern California (1993), and has been a faculty member since joining WPI. His research focuses on systems and controls, particularly in estimation and control of systems governed by partial differential equations (PDEs), distributed parameter systems, and fault detection in dynamical systems. He has pioneered work in adaptive control, fluid-structure interaction, and optimization in thermal manufacturing. Demetriou has held significant editorial roles, including Associate Editor for the IEEE Transactions on Automatic Control and SIAM Journal on Control and Optimization. He established the IEEE-CSS Technical Committee on Distributed Parameter Systems and currently serves in leadership roles within SIAM and the American Automatic Control Council (AACC). His work is funded by agencies like AFOSR, DARPA, and NASA. His research emphasizes practical applications, such as CubeSat attitude control, plume concentration estimation with UAVs, and contaminant sensing technologies. Demetriou is an IEEE Fellow (2015) and has collaborated extensively with industry partners like NASA's Jet Propulsion Laboratory. His labs, including the Intelligent Control Systems Laboratory, focus on advancing control methodologies for aerospace and mechanical systems.

• Numerical Analysis
• Uncertainty Quantification
• Inverse Problems
• +۳ مورد دیگر

Oliver G. Ernst is a Professor of Numerical Analysis at Technische Universität Chemnitz . His research focuses on Numerical Analysis , Uncertainty Quantification , and Inverse Problems , with applications in Thermo-Hydro-Mechanical (THM) processes , Electromagnetics , and Stochastic Partial Differential Equations . He is associated with the Numerical Analysis group at TU Chemnitz. Key Research Areas : Efficient numerical methods for PDEs Krylov subspace techniques Stochastic finite element methods Multi-physics modeling Geoscientific applications Recent Publications (2025-2010): THM simulations under uncertainty Neural network PDE solvers Bayesian inversion frameworks Rational Krylov algorithms Deflated restarting strategies Collaborations : TU Bergakademie Freiberg University of Manchester Technical University of Munich University of Maryland University of Geneva Software Development : Contributor to OpenGeoSys platform Developer of FEMALY MATLAB library Academic Recognition : h-index 32, i10-index 66, with over 4423 citations since 2020.

• Functional Analysis
• Operator Theory
• Semigroup Theory
• +۷ مورد دیگر

Felix Leopold Schwenninger is an Associate Professor at the University of Twente, affiliated with the Digital Society Institute and working in Mathematical Systems Theory. His research lies at the intersection of functional analysis, operator theory, and control systems, with a strong focus on semigroups, admissibility, and functional calculus. His research interests include: Functional Analysis and Operator Theory Admissibility and Controllability in Infinite-Dimensional Systems Semigroup Theory and Evolution Equations Functional Calculus for Operators Numerical Range and Spectral Theory Mathematical Foundations of Control Systems His recent publications (2024–2025) show a strong trend in duality concepts in stability, sharp bounds in functional calculus, and structural properties of operators in Banach spaces. These works are primarily theoretical, contributing to the rigorous mathematical underpinnings of control and operator theory. Scientific contributions and service include: Associate Editor, Optimal Control Applications and Methods (since 2021) Active publication in top mathematical journals and preprint servers (e.g., arXiv) Contributor to conference presentations, including on Barron spaces and embeddings He has supervised at least one PhD student (T. Heeringa) and continues to be actively involved in research, editorial work, and academic collaboration. He is part of a vibrant network in applied mathematics and systems theory, with international collaborations evident in recent outputs.

Louis-Pierre Chaintronمشاهده پروفایل

پژوهشگر ارشد

• Probability Theory
• Stochastic Processes
• Optimal Transport
• +۱۲ مورد دیگر

Louis-Pierre Chaintron is a Research Fellow at the École Normale Supérieure de Paris (ENS-PSL), affiliated with the Department of Mathematics and Applications (ENS DMA). His work bridges probability theory, stochastic processes, and applied mathematics, with a focus on constrained measure-valued dynamics, stability analysis, and approximation methods. PhD supervised by Julien Reygner (CERMICS) and Philippe Moireau (Inria M3DISIM) from 2022–2024 Member of the Probability and Statistics research team at ENS DMA Teaching roles include assistant for PDE courses and organizer of applied mathematics workshops Research Interests : His research explores connections between mean-field theory , large deviations , and viscosity solutions for Hamilton-Jacobi equations. He investigates filtering theory in dynamic systems, optimal transport frameworks, and Schrödinger bridge problems for high-dimensional systems. Applications span diffusion models in machine learning, muscle contraction modeling , and non-linear estimation under constraints. Recent Publications analyze convergence rates in stochastic control, stability of Gibbs principles, and jump-diffusion formalisms for biological systems. His work often combines calculus of variations , stochastic control , and viscosity solutions to address stability and approximation challenges. Contact : Email: lchaintron@dma.ens.fr Office: Bureau C11, Espace Cartan, 45 Rue d'Ulm, Paris

Jean Auriolمشاهده پروفایل

پژوهشگر

• PDEs
• Control Theory
• Robustness
• +۲ مورد دیگر

Jean Auriol is a researcher affiliated with the Signals and Systems Laboratory , focusing on advanced control theory and partial differential equations (PDEs). His work spans robustness, hyperbolic systems, and infinite-dimensional systems, often addressing real-world applications in engineering and physics. Research Interests: PDEs and Control Theory Robustness in Dynamical Systems Hyperbolic Systems and Networked Control Stochastic and Delayed Systems Recent Publications: Stability analysis of triangular hyperbolic systems Smart traffic management for autonomous vehicles Stochastic hyperbolic PDE stabilization Minimum time control of coupled PDEs Neural network-based parameter estimation for drilling systems

• Geometry
• Topology
• Quantum Field Theory
• +۲ مورد دیگر

Ryan Grady is an Associate Professor in the Department of Mathematical Sciences at Montana State University. His research and teaching focus span advanced mathematical disciplines. Education: Ph.D. and M.S. (2012, 2009) from University of Notre Dame B.S. (2007) from Colorado School of Mines Ryan's research lies at the intersection of geometry, topology , and quantum field theory (QFT) , with a focus on rigorous mathematical frameworks. He explores connections between QFT, derived geometry , and higher Lie theory , aiming to bridge physical intuition with formal mathematical structures. His recent publications highlight trends in topological data analysis , homotopy theory , and quantization . Key areas include factorization algebras , K-theory , and non-linear sigma models , reflecting a synthesis of abstract mathematics and physical applications. Ryan has advised multiple graduate students, including Eric Berry, Adam Howard, Garrett Oren, and Bryce Morrow, whose work spans cohomology of Grassmanians , surface immersions , algebraic structures , and infinite-dimensional linear algebra .

Oliver Fabertمشاهده پروفایل

دانشیار

• Symplectic Geometry
• Hamiltonian Systems
• Floer Theory
• +۳ مورد دیگر

Dr. Oliver Fabert is an Associate Professor in the Department of Mathematics at the Faculty of Science, Vrije Universiteit Amsterdam. His research focuses on advanced topics in symplectic geometry, Hamiltonian systems, and Floer theory. He teaches courses such as Differential Geometry, Non-linear Dynamical Systems, and Partial Differential Equations. Key research interests include Hamiltonian systems, periodic solutions, symplectic manifolds, and the application of Floer theory to nonlinear PDEs. His work often intersects with algebraic topology and geometric analysis, addressing challenges like the small divisor problem in Hamiltonian PDEs and the development of regularization techniques in polysymplectic geometry. Dr. Fabert has published extensively on topics such as hyperkähler Floer theory, pseudoholomorphic curves, and topological recursion relations. His contributions span foundational work in symplectic field theory and polyfold theory, with applications to both finite and infinite-dimensional Hamiltonian systems. He has supervised at least one PhD thesis and actively engages in teaching advanced mathematical concepts, reflecting his commitment to both research and education in theoretical mathematics.

• Geometric Functional Analysis
• Banach Space Theory
• Mathematical Structures in Nonlinear Dynamics

Razvan Anisca is a Professor in the Department of Mathematical Sciences at Lakehead University, specializing in Geometric Functional Analysis . He has held this position since 2015 and previously served as Department Chair (2013-2017, 2021-2023) and Associate/Assistant Professor since 2003. His research focuses on Banach spaces, Hilbert spaces, and their geometric properties. PhD, University of Alberta (2002) BSc, University of Bucharest (1997) Recent publications highlight his work on: Ergodicity in Hilbert spaces (2020, 2023) Arithmetic sums of Cantor sets (2009, 2023) Complex structures in Banach spaces (2003, 2017) Approximation properties in functional spaces (2012) He co-organized a Banff International Research Station (BIRS) workshop on Banach space theory in 2012.

Matthew Thorpeمشاهده پروفایل

دانشیار

• Machine Learning
• Data Science
• Applied Mathematics
• +۴ مورد دیگر

Matthew Thorpe is an Associate Professor in the Department of Statistics at the University of Warwick and a member of the European Laboratory for Learning and Intelligent Systems (ELLIS). His research focuses on applying methods from applied analysis—including partial differential equations (PDEs), calculus of variations, and optimal transport—to machine learning and data science challenges. He has organized workshops such as the 'Machine Learning in Infinite Dimensions' at ETH Zurich and the 'LMS-Bath Symposium on Inverse Problems and Artificial Intelligence in Medicine.' Thorpe currently seeks PhD students for his research projects. His work bridges theoretical mathematics with practical applications in data-driven fields. Thorpe's research interests include manifold learning in Wasserstein space, PDE-based approaches to data science, and convergence analysis of graph-based learning algorithms. He has contributed to understanding the impact of imputation quality on machine learning models and developed novel transportation distances for pattern recognition. His interdisciplinary approach integrates mathematical rigor with advancements in artificial intelligence. He has co-organized the One World Seminar Series on the Mathematics of Machine Learning and remains active in promoting collaborative research initiatives. Despite no explicitly listed awards, his prolific publication record reflects sustained academic impact. Thorpe’s advising focuses on training students in the intersection of applied mathematics and modern data science techniques.

Lassi Paunonenمشاهده پروفایل

دانشیار

• Functional Analysis
• Operator Theory
• Infinite-Dimensional Linear Systems
• +۳ مورد دیگر

Lassi Paunonen is an Associate Professor in Mathematics at the Faculty of Information Technology and Communication Sciences (ITC), Tampere University. He leads the Systems Theory Research Group, focusing on functional analysis, operator theory, and robust control of infinite-dimensional systems. His work addresses challenges in stability analysis of semigroups, output regulation, and control design for distributed parameter systems. Research Interests: Functional analysis, operator theory, infinite-dimensional linear systems, robust control, stability of strongly continuous semigroups, and mathematical systems theory. Key Contributions: Recent publications explore admissibility in infinite-dimensional systems, boundary control of heat equations, and model reduction techniques for neural ODEs. His research emphasizes theoretical foundations with applications in engineering and physics. Lassi Paunonen collaborates actively through his research group, maintaining professional presence on Systems Theory Research Group and personal website .

André Uschmajewمشاهده پروفایل

استاد

• Numerical Analysis
• Tensor Methods
• Low-Rank Approximation
• +۷ مورد دیگر

Prof. Dr. André Uschmajew is a full professor and holds the Chair of Mathematical Data Science at the Institute of Mathematics, Faculty of Mathematics, Natural Sciences, and Materials Engineering, University of Augsburg, Germany. He has held prominent research and academic positions at institutions including the Max Planck Institute for Mathematics in the Sciences (Leipzig), University of Bonn, and EPF Lausanne. 2022–present: Chair of Mathematical Data Science, University of Augsburg 2017–2022: Research Group Leader, Max Planck Institute MiS Leipzig 2014–2017: Bonn Junior Fellow Professorship, University of Bonn 2013: Ph.D. in Mathematics, TU Berlin His research centers on the theoretical and computational aspects of low-rank tensor and matrix approximations, with deep connections to Riemannian optimization, functional analysis, and high-dimensional scientific computing. He investigates the geometry of low-rank varieties, convergence of alternating algorithms, and applications in data science and dynamical systems. His work combines rigorous mathematical analysis with algorithmic innovation. The recent publications (2023–2025) reflect a strong focus on optimization methods for low-rank structures, dynamical low-rank approximation for PDEs like the Vlasov-Poisson equation, randomized SVD, Sinkhorn-type algorithms with overrelaxation, and Kronecker product operator approximation. Key themes include convergence analysis, algorithmic acceleration, and applications in scientific computing and signal processing. Although no specific awards are listed, his publication record in top-tier journals such as Numerische Mathematik , SIAM Journal on Optimization , and Foundations of Computational Mathematics indicates significant recognition in applied mathematics and numerical analysis. He advises students and researchers in mathematical data science and numerical analysis, though specific advisees are not named. He teaches courses such as Kernel Methods and Linear Algebra II. He has collaborated with leading researchers including Bart Vandereycken, Daniel Kressner, and Wolfgang Hackbusch. His work is supported through institutional affiliations and likely research grants, though specific grants are not listed. He is actively involved in the development of numerical methods for high-dimensional problems, particularly using tensor networks and manifold optimization. He is affiliated with research teams at the University of Augsburg and previously led a group at the Max Planck Institute MiS Leipzig, focusing on mathematical aspects of data science and tensor methods.