جست‌وجوی استاد و پژوهشگر

• Mathematical Finance
• Stochastic Processes
• Energy Markets
• +۵ مورد دیگر

Sven Karbach is an Assistant Professor for Data-Driven Mathematical Modelling and Computing in Finance at the University of Amsterdam. He coordinates the Stochastics and Financial Mathematics Master Program and is affiliated with the Stochastics group at the Korteweg-de Vries Institute, Computational Science Lab (CSL) at the Informatics Institute, and the AI4Fintech initiative. Education: BSc Mathematics, University of Wuppertal (2013-2016) MSc Mathematics, University of Wuppertal (2016-2018) Doctor of Mathematics, University of Amsterdam (2018-2022) Research Focus: Robust finance methods in infinite-dimensional models Hedging and trading in energy markets Deep Spatio-Temporal Hedging for climate risk mitigation Stochastic volatility and covariance modeling Renewable energy market risk networks Recent Article Trends include applications of affine processes in Hilbert spaces, measure-valued CARMA models for energy markets, and spatio-temporal hedging techniques. His work bridges mathematical rigor with practical AI integration in fintech. Scientific Awards & Grants: Barmenia mathematics award (2017, 2019) Deutschlandstipendium (2015–2016, 2016–2018) €25,000 grant for 'Deep Spatio-Temporal Hedging' €35,000 joint grant with Simon Trimborn for 'Risk Networks of Renewable Energy Markets' Students include PhD candidates Diogo Sousa Franquinho and Konstantinos Chatziandreou. His research team explores advanced mathematical frameworks for sustainable energy finance.

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

• Probability Theory
• Mathematical Physics
• Stochastic Analysis
• +۳ مورد دیگر

Pierre PERRUCHAUD is a Postdoctoral researcher at the Department of Mathematics within the Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg. His research focuses on advanced topics in stochastic analysis, mathematical physics, and functional analysis. He is affiliated with the Maison du Nombre research unit located in Esch-sur-Alzette. His work explores complex systems such as hypoelliptic operators, stochastic processes in geometric settings, and homogenization theory. Key contributions include studies on non-de Finetti theorems, loop soup representations, and kinetic Dyson Brownian motion. His research bridges probability theory with applications in quantum field theory and statistical mechanics. Pierre's publications reflect a deep engagement with both theoretical and applied aspects of stochastic analysis, often involving interdisciplinary approaches combining geometry and probability. His current projects likely continue to advance understanding in anisotropic kinetic systems and asymptotic expansions for hypoelliptic equations. No scientific awards or grants are explicitly mentioned in the provided information. His advising record remains unspecified, though his postdoctoral role suggests active participation in academic mentorship.

• Functional Analysis
• Operator Theory
• Holomorphic Functions
• +۶ مورد دیگر

Maria Pilar Rueda Segado is a Professor in the Department of Mathematical Analysis at the Faculty of Mathematics, University of Valencia. She is a leading researcher in functional analysis and operator theory, with a focus on holomorphic functions, polynomials, and multilinear operators in infinite-dimensional spaces. Her work is closely associated with the ESALDI research group. Her research interests lie primarily in Functional Analysis, particularly in the areas of: Weighted spaces of holomorphic functions Summing and dominated multilinear operators and polynomials Isometries in function spaces Factorization of operators and polynomials Spaceability and norm-attaining mappings Tensor norms and operator ideals Her extensive publication record, with over 90 works since 1996, reflects a deep and sustained engagement with core problems in nonlinear functional analysis. Her publications demonstrate a consistent focus on abstract operator theory, functional ideals, and the geometry of Banach spaces, often in collaboration with prominent mathematicians such as Daniel Pellegrino, Enrique Sánchez-Pérez, and Christopher Boyd. She earned her PhD from the University of Valencia in 1997 with a thesis on infinite-dimensional holomorphy under the supervision of Dr. Pablo Galindo Pastor. She has not received any explicitly mentioned scientific awards in the provided text. She has supervised PhD students, though their names are not listed in the provided content. Her research has been supported through institutional and collaborative academic grants, typical of senior faculty in mathematical sciences. She actively collaborates with an international network of researchers in functional analysis. She is a key member of the ESALDI (Spaces and Algebras of differentiable Functions) research group at the University of Valencia, which focuses on advanced topics in functional analysis and differentiable structures in infinite dimensions.

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.

Qiudong Wangمشاهده پروفایل

استاد

• Dynamical Systems
• Differential Equations
• Chaos Theory
• +۷ مورد دیگر

Qiudong Wang is a Professor in the Department of Mathematics at the University of Arizona, where he conducts research and teaches in the field of dynamical systems and differential equations. His work spans theoretical and applied aspects of nonlinear dynamics, celestial mechanics, and chaotic systems. Education: Ph.D., University of Cincinnati, 1994 B.S., Nanjing University, China, 1982 His research focuses on homoclinic tangles, Melnikov methods, rank one attractors, twist maps, and the N-body problem . He has made significant contributions to the understanding of chaotic behavior in both deterministic and stochastically perturbed systems. His work often involves deep analytical techniques and has been published in premier journals such as Annals of Mathematics , CPAM , and JDE . He has also contributed expository works on rank one chaos and homoclinic tangles, including a Scholarpedia article. The trends in his recent publications emphasize nonautonomous and stochastic perturbations, geometric methods in dynamical systems, and the statistical properties of chaotic attractors . His research bridges pure mathematics with applications in physics and engineering, particularly in celestial mechanics and circuit systems. Scientific Contributions: Development of high-order Melnikov methods Theory of rank one attractors with Lai-Sang Young Analysis of homoclinic tangles and their chaotic dynamics Study of the N-body problem and integral manifolds Investigations into twist maps and variational methods Wang advises students in mathematics and has mentored work in dynamical systems, though specific names are not listed. He has received recognition through publications in top journals, though formal awards are not mentioned. He teaches undergraduate courses such as Math 254 and maintains comprehensive lecture notes on dynamical systems, homoclinic tangles, and rank one chaos. He is actively involved in research and continues to publish preprints and expository works, indicating ongoing scholarly activity. He leads a research group focused on nonlinear dynamics and chaos theory, with a strong emphasis on rigorous mathematical analysis. His team explores theoretical frameworks for understanding complex dynamical behavior in both finite and infinite-dimensional systems.

• Computational Mechanics
• Micromechanics
• Homogenization
• +۳ مورد دیگر

Prof. Dr. Matti Schneider serves as Professor of Engineering Mathematics and Head of the Institute of Engineering Mathematics within the Faculty of Civil Engineering at the University of Duisburg-Essen. His academic leadership spans computational mechanics research and teaching core mathematics courses for civil engineering students. His educational background includes: Diploma in Applied Mathematics with distinction from TU Bergakademie Freiberg (2009) PhD (Dr. rer. nat.) from Leipzig University (2013) on "The Leray-Serre spectral sequence in Morse homology on Hilbert manifolds and in Floer homology on cotangent bundles" Professor Schneider's research focuses on advancing computational methods for solid mechanics through FFT-based homogenization techniques, microstructure modeling, and multi-scale material analysis. His work bridges applied mathematics and engineering to solve complex problems in heterogeneous material systems, with particular emphasis on numerical stability, boundary condition implementation, and efficient solver development for industrial applications. His methodologies enable accurate prediction of material behavior across scales from microscopic structures to macroscopic components. Analysis of his 15 most recent publications reveals dominant trends in FFT-based computational homogenization, with significant contributions to thermal problems, porous media, and fiber-reinforced composites. He pioneers the integration of machine learning (particularly deep material networks) with traditional numerical methods to model complex material behaviors like shear-thinning suspensions and 3D-printed materials. His work consistently addresses computational challenges in boundary condition implementation and convergence for stochastic microstructures. Professor Schneider leads the Institute of Engineering Mathematics and directs research within the ERC-funded BeyondRVE project, which focuses on extending representative volume element concepts for advanced material modeling. His collaborative network includes major German research institutions like Fraunhofer ITWM and international partners in materials science.

Monica Jinwoo Kangمشاهده پروفایل

پژوهشگر ارشد

• Mathematical Physics
• High Energy Theory
• Quantum Information
• +۷ مورد دیگر

Monica Jinwoo Kang is a postdoctoral researcher at the University of Pennsylvania in the Department of Physics and Astronomy and the Center of Particle Cosmology. Previously, she was a Sherman Fairchild Postdoctoral Fellow at the California Institute of Technology (Caltech), following her PhD in Physics from Harvard University (2019). She also holds a bachelor's degree from UC Berkeley in Mathematics and Physics. Roles: Postdoctoral Fellow (UPenn), Sherman Fairchild Fellow (Caltech), Thesis Advisor: Mboyo Esole, Shing-Tung Yau Education: PhD in Physics (Harvard, 2019), BS in Mathematics and Physics (UC Berkeley, 2012) Her research explores the intersection of quantum gravity , string theory , and mathematical physics , with a focus on holography, operator algebras, and supersymmetric field theories. She combines techniques from conformal field theory, algebraic geometry, and quantum information to study spacetime geometry and entanglement. Her work includes constructing holographic tensor networks and analyzing nonperturbative gravitational corrections to bulk reconstruction. Recent publications examine: Holographic tensor networks in 3D spacetime Nonperturbative bulk reconstruction with infinite-dimensional Hilbert spaces Supersymmetric dualities in 4D and 6D SCFTs Geometric origins of anomalies and spectra in lower-dimensional theories Scientific awards include: Sherman Fairchild Postdoctoral Fellowship (Caltech) Center of Particle Cosmology Postdoctoral Fellowship (UPenn) At UPenn and Caltech, Kang has organized seminars and workshops connecting mathematicians and physicists on topics like integrability, geometry, and quantum field theory. She also lectures extensively on quantum field theory, holography, and algebraic geometry, with recent talks at Princeton , CERN , and the Isaac Newton Institute .

Giulia Di Nunnoمشاهده پروفایل

استاد

• Stochastic Analysis
• Financial Mathematics
• Risk Management
• +۴ مورد دیگر

Giulia Di Nunno is a Professor in the Department of Mathematics at the University of Oslo, specializing in stochastic analysis and its applications to finance and risk management. She also holds an adjunct professorship at the Norwegian School of Economics (NHH). Her research focuses on stochastic calculus, control theory, financial modeling, and energy finance, with a particular interest in dynamic risk measures. She has led major projects like the STORM initiative on time-space risk models and is involved in interdisciplinary research on sustainability and energy markets. Di Nunno has served as President of the Scientific Council of CIMPA and is an associate editor for several prestigious journals, including Finance and Stochastics and Stochastics . Her work bridges theoretical advancements with practical applications in finance and energy sectors. Education: PhD in Mathematical Statistics (University of Pavia, 2003), Degree in Mathematics (University of Milan, 1998). Research Groups: Risk and Stochastics, STORE (completed). Key Projects: SURE-AI (AI-driven risk modeling), Unruly Sustainability (interdisciplinary research), STORM (ToppForsk project). Editorial Roles: Associate Editor for Finance and Stochastics , DEAF , FMF , and others. Her publications emphasize stochastic processes, volatility modeling, and risk measurement, with recent contributions on time-changed dynamics and applications to energy finance. She actively contributes to the international academic community through research networks like AMaMeF and ModSimFIE.

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.

• Applied Stochastic Analysis
• Mathematical Ecology
• Interacting Particle Systems
• +۳ مورد دیگر

Michela Ottobre is a Professor of Mathematics at Heriot-Watt University, affiliated with the School of Mathematical & Computer Sciences. She holds editorial roles at Foundations of Data Science and SIAM Review , and is a member of the European Mathematical Society and Edinburgh Mathematical Society. Her research focuses on applied stochastic analysis, mathematical ecology, and multiscale modeling, with applications to rewilding and ecological systems. Education & Career PhD in Mathematics, Imperial College London (2012) Postdoctoral roles at Warwick University and Imperial College London Joined Heriot-Watt as Assistant Professor (2014), promoted to Full Professor (2024) Research Interests Her work integrates stochastic processes, interacting particle systems, and PDEs to model ecological and biological phenomena. Key areas include: Stochastic multiscale models Mathematical ecology and rewilding Numerical methods for SDEs Grants & Awards Leverhulme Research Grant (2020–2023) EPSRC Standard Grant (2025, £550k) for multiscale methods Sir Edmund Whittaker Memorial Prize (2019) Collaborations & Outreach Organized workshops including the 11th International Conference on Stochastic Analysis (2023) and contributed to ecological modeling initiatives. Supervises PhD students in applied stochastic analysis and mathematical ecology.

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 .

• Mathematical Optimization
• Nonsmooth Optimization
• Multiobjective Optimization
• +۴ مورد دیگر

Bennet Gebken is a researcher at the Department of Mathematics , Technical University of Munich , affiliated with the Chair of Mathematical Optimization led by Prof. Ulbrich. His work focuses on nonsmooth and multiobjective optimization, particularly in PDE-constrained problems and numerical continuation methods. Research Interests: Bennet specializes in nonsmooth optimization, multiobjective optimization, and regularization techniques. His recent work explores convergence analysis in nonsmooth settings, second-order gradient sampling, and inverse optimization methods for data-driven decision criteria. Publications: His research spans topics like PDE-constrained multiobjective optimization, L1 penalty terms, and the hierarchical structure of Pareto critical sets. Key trends include reduced-order modeling, computational efficiency, and the interplay between optimization and machine learning. Contact: bennet.gebken@tum.de . Based at Boltzmannstr. 3, Garching b. München, Germany.

Hugo LHACHEMIمشاهده پروفایل

دانشیار

• Control Theory
• Partial Differential Equations
• Cyber-Physical Systems
• +۴ مورد دیگر

Hugo LHACHEMI is an Associate Professor of System Control at CentraleSupélec since September 2020 and a member of the CNRS Laboratory of Signals and Systems (L2S), part of Paris-Saclay University. Previously, he was a Postdoctoral Fellow at University College Dublin (2018-2020) under the supervision of Professor Robert Shorten. His research focuses on control theory for finite and infinite-dimensional systems, with applications in aerospace and cyber-physical systems. Key areas include stabilization of partial differential equations (PDEs), time-delay systems, and robust control. He has contributed to boundary feedback stabilization, output feedback control for PDEs, and cyber-physical systems for additive manufacturing. Notable academic contributions include work on static output feedback for heat equations, low-dimensional controller design, and cyber-physical systems integrating mixed reality and deep learning. His research has been published in top journals like IEEE Transactions on Automatic Control and Automatica. Education: No explicit details provided, but holds a PhD in control systems (implied by academic rank). Grants/Projects: Active in collaborative projects on additive manufacturing and control systems design. Key Skills: Expertise in PDE stabilization, nonlinear control, and cyber-physical systems.

Markus Keelمشاهده پروفایل

استاد

• Partial Differential Equations
• Real Analysis
• Harmonic Analysis
• +۵ مورد دیگر

Markus Keel is a Professor at the School of Mathematics, Department of Mathematics, University of Minnesota. He holds a B.S. in Mathematics from the University of Chicago and a Ph.D. in Mathematics from Princeton University. Education: University of Chicago - B.S. in Mathematics Princeton University - Ph.D. in Mathematics Research Interests Markus Keel's research focuses on Partial Differential Equations (PDEs) , with significant contributions to Real Analysis , Harmonic Analysis , and Functional Analysis . His work addresses fundamental questions in Global Well-Posedness , Scattering Theory , and Instability Phenomena for nonlinear PDEs such as the Nonlinear Schrödinger Equation , Korteweg-de Vries (KdV) Equation , and Wave Equations . Research Trends Keel's publications highlight his expertise in analyzing the behavior of solutions to nonlinear dispersive equations. Key areas include Energy-Critical PDEs , High-Frequency Dynamics , and Resonant Interactions , often employing techniques like the I-Method , Multilinear Estimates , and Strichartz Inequalities . His collaborations with prominent mathematicians like Terence Tao, James Colliander, and Gigliola Staffilani reflect a strong emphasis on advancing theoretical frameworks for nonlinear partial differential equations. Contact Information Email: keel@umn.edu Phone: (612) 624-6341 Address: 222 Vincent Hall, 206 Church Street SE, Minneapolis, MN 55455