جست‌وجوی استاد و پژوهشگر

Matheus Grasselliمشاهده پروفایل

استاد

• Financial Mathematics
• Stochastic Analysis
• Probability Theory
• +۵ مورد دیگر

Matheus Grasselli is a Professor of Financial Mathematics at the Department of Mathematics and Statistics, McMaster University, where he currently serves as Deputy Provost since July 2022. He is affiliated with the PhiMac research group and co-leads the Systemic Risk Analytics initiative at the Fields Institute. His previous roles include Deputy Director at the Fields Institute (2012–2016) and Director of the Centre for Financial Industries (2017–2020). Grasselli’s research spans Financial Mathematics, focusing on stochastic analysis, systemic risk, climate-economic modeling, and asset price bubbles. He has advised numerous graduate and undergraduate students, including PhD candidates and postdoctoral fellows, contributing to over 50 academic publications. His teaching includes advanced courses in financial mathematics, numerical methods, and real options, alongside contributions to the Integrated Sciences program. Grasselli holds a PhD in Information Geometry from King’s College London and has collaborated internationally on projects integrating economic theory with climate science. Education: PhD in Information Geometry, King’s College London. Leadership Roles: Deputy Provost (2022–present), Deputy Director (Fields Institute, 2012–2016), Director (Centre for Financial Industries, 2017–2020). Research Interests: Financial Mathematics, systemic risk, climate-economic models, asset price bubbles, and stochastic processes. His work bridges theoretical frameworks with practical applications in policy analysis and financial stability. Teaching: Courses include graduate programs like the McMaster Financial Mathematics (MFM) Master’s, numerical methods for finance, and undergraduate courses in calculus and linear algebra. He pioneered the design of the Integrated Sciences program. Collaborations: Active in interdisciplinary projects, including climate-economic modeling and systemic risk analysis. His research often employs agent-based computational economics and dynamical systems approaches.

John Keyserمشاهده پروفایل

استاد

• Computer Science
• Graphics and visualization
• Physically-based simulation
• +۵ مورد دیگر

John Keyser is a Professor in the Department of Computer Science & Engineering at Texas A&M University, serving as Graduate Advisor. He holds a Ph.D. from the University of North Carolina at Chapel Hill and multiple B.S. degrees from Abilene Christian University. His research focuses on geometric computing, physically-based simulation, graphics, and modeling, with notable contributions to 3D visualization and computational geometry. Keyser's educational background includes advanced degrees in Computer Science, Applied Mathematics, and Engineering Physics. He has received prestigious awards such as the William Keeler Faculty Fellowship and teaching accolades from the Association of Former Students and Tenneco. His research interests span robust geometric modeling, physically-based simulation, brain networks, and graphics. Keyser's work bridges theoretical foundations with applied systems, including innovations in particle-based fluids, mesh rendering, and filament tracking in microscopy. Awards: William Keeler Faculty Fellow (2009-2010), Teaching Excellence Awards (2007), Montague Scholar (2003-2004). Advising: Graduate Advisor role with expertise in guiding students through complex computational projects. Keyser collaborates on advanced imaging techniques like the Knife-Edge Scanning Microscope (KESM) for brain tissue analysis and contributes to GPU-accelerated algorithms for real-time simulations. His research trends emphasize interdisciplinary applications of geometric computing in both academic and industrial contexts.

Gregory Kneseمشاهده پروفایل

استاد

• Operator Theory
• Complex Analysis
• Harmonic Analysis
• +۳ مورد دیگر

Gregory Knese is a Professor of Mathematics and Director of Graduate Studies at Washington University in St. Louis (WashU), where he also earned his PhD in 2007. His research focuses on operator theory, complex analysis, harmonic analysis, and stable polynomials. He holds editorial roles at the Bulletin and Journal of the London Mathematical Society. Knese has led NSF-funded projects exploring operator theory, stable polynomials, and harmonic analysis. His work bridges pure mathematics with applications in astronomy and engineering. He teaches advanced courses like Measure Theory and Functional Analysis, and has advised PhD students such as Jeet Sampat and Jerry Li. Knese’s academic journey includes roles at UC Irvine and the University of Alabama before joining WashU in 2013. Education: PhD in Mathematics (2007), B.S. in Mathematics (2002), both from WashU and Truman State University respectively. Research Interests: Operator theory, complex function theory, stable polynomials, sums of squares, and harmonic analysis. His recent work explores Schur-Agler classes, von Neumann inequalities, and cyclic polynomials in multidimensional spaces. Grants & Service: Secured multiple NSF grants (e.g., 2023-2026 for stable polynomials and rational singularities). Organized major conferences like GPOTS 2022 and the 2016 International Workshop on Operator Theory. Active in editorial boards and academic service roles. Teaching & Mentoring: Taught over 20 courses, including Honors Mathematics and Analytic Combinatorics. Supervised PhD and undergraduate research projects, emphasizing mentorship in pure mathematics.

Juan Rivera-Letelierمشاهده پروفایل

استاد

• Dynamical Systems
• Number Theory
• Ergodic Theory
• +۳ مورد دیگر

Juan Rivera-Letelier is a Professor of Mathematics at the University of Rochester's School of Arts & Sciences. He holds a Doctorat en Mathématiques Pures (equivalent to a PhD) from Université de Paris Sud, obtained in 2000. His research focuses on dynamical systems, number theory, and ergodic theory, with particular emphasis on non-Archimedean dynamics, statistical properties of maps, and applications to arithmetic geometry. He has authored numerous influential papers on topics such as Fatou components, Gibbs states, and p-adic distributions of algebraic points. His recent work explores phase transitions in intermittent maps, sensitive dependence in geometric Gibbs states, and equidistribution of CM points in toric varieties. He has contributed to foundational results in ultrametric dynamics, including studies on wildly ramified power series and residue fixed point indices. Rivera-Letelier’s research bridges complex dynamics, real analysis, and number theory, often employing techniques from thermodynamic formalism and non-uniform hyperbolicity. His work has implications for understanding the interplay between arithmetic structures and dynamical systems, with applications to Diophantine geometry and statistical mechanics.

Erich Kaltofenمشاهده پروفایل

استاد

• Computational Algebra
• Symbolic Computation
• Number Theory
• +۴ مورد دیگر

Erich Kaltofen is a Professor of Mathematics and member of the Symbolic Computation group at North Carolina State University (NCSU). He holds an adjunct professorship in Computer Science at Duke University. His academic journey includes a PhD in Computer Science from Rensselaer Polytechnic Institute (1982) and an MS from the same institution (1979). Kaltofen’s research focuses on computational algebra, hybrid symbolic-numeric algorithms, sequential and parallel algorithms, and symbolic computation systems. Research Interests: Kaltofen’s work spans computational algebra and number theory, emphasizing the development of efficient algorithms for polynomial factorization, sparse interpolation, and error-correcting methods. He is renowned for contributions to symbolic computation systems like LinBox and FoxBox, and his research integrates theoretical insights with practical software development. Publications: His recent publications highlight advancements in sparse polynomial interpolation, error-correcting algorithms, and computational complexity. Key themes include symbolic-numeric computation, algorithm design, and applications in cryptography and algebraic geometry. Awards and Recognition: A Fellow of the ACM (2009) and recipient of the Jenks Memorial Prize (2017), Kaltofen’s contributions have shaped the field of symbolic computation. His work bridges theoretical foundations and real-world applications, impacting computer science and mathematics. Advising and Grants: Kaltofen has advised numerous PhD students and postdocs, fostering advancements in algorithmic research. His grants include NSF-funded projects on hybrid symbolic-numeric methods and error-correcting algorithms. He collaborates on initiatives such as the Genomic Sciences program at NCSU. Labs and Teams: Co-designer of the LinBox library, Kaltofen contributes to open-source software for linear algebra and symbolic computation. His work emphasizes collaborative, interdisciplinary projects addressing challenges in computational mathematics and computer science.

• Computational Geometry
• Computer Algebra
• Visualization
• +۴ مورد دیگر

Chee K. Yap is a Professor of Computer Science at the Courant Institute of Mathematical Sciences, New York University. He holds a PhD from Yale University (1979) and an S.B. from MIT (1975). His research focuses on computational geometry, computer algebra, visualization, algorithmic robotics, complexity theory, and numerical robustness. He leads the Exact Geometric Computation Group and contributes to the Active Visualization Project. Recent work includes validated algorithms for differential equations, path planning for robots in SE(3), and certified root isolation methods. Yap has authored over 200 publications, with contributions to ISSAC conference proceedings and software tools like SIAN for ODE identifiability analysis. His research emphasizes bridging theory and practice in geometric and algebraic computation.

David Mondمشاهده پروفایل

استاد

• Singularity Theory
• Algebraic Geometry
• Climate Change
• +۳ مورد دیگر

David Mond is a Professor of Mathematics at the University of Warwick, specializing in singularity theory, algebraic geometry, and climate change research. His work bridges pure mathematics with applications in topology and environmental modeling. He holds an office in C2.17 and can be reached at D.M.Q.Mond@warwick.ac.uk. His research spans over four decades, with notable contributions to the classification of singularities, logarithmic vector fields, and free divisors. A key publication is Singularities of Mappings (2020), part of Springer’s Grundlehren series. He has secured grants from the Royal Society, EPSRC, and the London Mathematical Society for projects like 'Frobenius Manifolds & F-manifolds in Singularity Theory' (2005–2008). Mond’s recent work explores intersections between singularity theory and climate change, applying game-theoretic models to environmental policy analysis. His teaching includes modules like MA3F1 Topology and MA5NO Cohomology, reflecting his commitment to both research and education in mathematics. He advises on pedagogical initiatives, such as the Warwick Teaching Certificate for Mathematics, and collaborates internationally on singularities and foliations. His research group focuses on topics like vanishing cycles, discriminants, and the topology of mapping images.

Dmitriy Rumyninمشاهده پروفایل

استاد

• Representation Theory
• Algebraic Geometry
• Algebraic Groups
• +۷ مورد دیگر

Professor Dmitriy Rumynin is a faculty member at the University of Warwick's Mathematics Institute, specializing in Representation Theory with interdisciplinary extensions into Algebraic Geometry, Lie Algebras, and Homotopy Theory. He serves as an editor for the Journal of Algebra and its Applications and teaches advanced courses like MA377 Rings and Modules and MA4E0 Lie Groups. His research explores topics such as Kac-Moody groups, D-modules, and algebraic structures in positive characteristic, with a focus on bridging abstract algebra with geometric and topological methods. Research Interests: Representation Theory (broadly interpreted), Algebraic Groups, Lie Algebras, Kac-Moody Groups, Homogeneous Spaces, and applications in Computer Arithmetic. Recent work includes studies of topological invariants of homogeneous spaces and classification of disconnected reductive groups. Publications highlight contributions to module theory, Hopf algebras, and geometric representation theory. His articles frequently intersect with algebraic geometry, differential geometry, and category theory, reflecting a synthetic approach to modern algebraic structures. No scientific awards explicitly mentioned in available texts. His editorial role at the Journal of Algebra and Applications underscores his influence in the field. Grants and advising details are not detailed in the provided materials, though his teaching responsibilities indicate active involvement in graduate education. Labs/Teams: Not explicitly stated, but collaborations are implied through co-authored works and editorial activities.

Samir Siksekمشاهده پروفایل

استاد

• Number Theory
• Arithmetic Geometry
• Diophantine Equations
• +۴ مورد دیگر

Samir Siksek is a Professor of Mathematics at the University of Warwick's Mathematics Institute. His primary role includes teaching advanced courses such as MA268 Algebra III and TCC Modular Curves, and he actively contributes to the Number Theory Group at Warwick. Education details are not explicitly stated in the text, but his PhD thesis on 'Descents on curves of genus 1' (1995) is referenced. Research interests focus on Number Theory, particularly Galois representations, Diophantine equations (including Fermat-type equations), arithmetic geometry, and modular forms. His work spans explicit methods for solving Diophantine equations, modular curves, and applications of modular forms. Key contributions include resolving cases of Fermat's Last Theorem over various number fields and advancing techniques in Chabauty methods and the Mordell-Weil sieve. He organizes events like the 'Modular curves and their arithmetic' conference (December 2023) and has contributed to workshops at BIRS, CMI-HIMR, and Banff. His research has been published in top journals like Inventiones Mathematicae and Compositio Mathematica. Professional activities include advising postdocs and PhD students, leading the Warwick Number Theory Seminar, and collaborating on projects like the L-Functions and Modular Forms Database (LMFDB).

• Nonlinear Partial Differential Equations
• Mathematical Physics
• Applied Mathematics
• +۴ مورد دیگر

Yisong Yang is a Professor of Mathematics at New York University, affiliated with both the Courant Institute of Mathematical Sciences and the Tandon School of Engineering. He holds a Ph.D. in Mathematics from the University of Massachusetts (1988), an M.S. from the Chinese Academy of Sciences (1985), and a B.S. from Henan University (1982). His research focuses on Nonlinear Partial Differential Equations, Mathematical Physics, and Applied Mathematics, with notable contributions to soliton theory, gauge field models, and cosmological equations. He has authored books on advanced linear algebra and nonlinear analysis, including works published by Springer, Cambridge University Press, and Oxford University Press. Teaching responsibilities include graduate courses such as Real Analysis II and Advanced Linear Algebra II at Tandon. His publications span over three decades, addressing topics like Born-Infeld theory, black hole physics, and vortex dynamics. Yang’s work bridges pure mathematics and theoretical physics, with applications in cosmology and quantum field theory. He maintains an active research profile, with recent studies on electromagnetic asymmetry, charged black holes, and nonlinear phenomena. Collaborative efforts include exploration of geometric curvatures in physical systems and the mathematical foundations of solitonic structures. Professional activities include curriculum development, academic advising, and participation in interdisciplinary projects. His hobbies include a strategic board game called “Four Armies,” emphasizing cooperative gameplay.

Benjamin Peherstorferمشاهده پروفایل

دانشیار

• Computational Mathematics
• Machine Learning
• Computational Statistics
• +۵ مورد دیگر

Benjamin Peherstorfer is an Associate Professor at the Courant Institute of Mathematical Sciences, New York University. His research focuses on computational mathematics, machine learning, and scientific computing, with an emphasis on nonlinear model reduction, uncertainty quantification, and multifidelity methods. He holds editorial roles at journals such as Journal of Scientific Computing and SIAM Journal on Scientific Computing . Peherstorfer co-organizes workshops on topics like digital twins and fusion energy, reflecting his commitment to advancing interdisciplinary computational science. He has advised students like Jules Berman, who received the Harold Grad Memorial Prize. His work integrates machine learning with traditional numerical methods to address challenges in high-dimensional systems and real-time simulations. Notable contributions include developing Neural Galerkin schemes for solving evolution equations and advancing multifidelity Monte Carlo methods to accelerate uncertainty propagation. His research bridges theoretical foundations with practical applications, such as wildfire-atmosphere coupling and plasma confinement in stellarators. Key Roles: Secretary of the SIAM Activity Group on Computational Science and Engineering Co-organizer of the Long Program on Multi-Fidelity Methods for Fusion Energy (IPAM, 2026) Main Research Themes: Reduced-order modeling Data-driven operator inference Adaptive sampling algorithms

Alistair Savageمشاهده پروفایل

استاد

• Algebra
• Representation Theory
• Lie Theory
• +۲ مورد دیگر

Prof. Alistair Savage is a Full Professor and Chair in the Department of Mathematics and Statistics at the University of Ottawa. He holds a PhD from Yale University and focuses on representation theory using geometric, categorical, and combinatorial methods. His research explores associative algebras, Lie algebras, and their applications in geometry and algebraic combinatorics. He is affiliated with the Algebra, Number Theory & Representation Theory and Lie Theory research groups. Education: MS, MPhil, PhD (Yale University). He teaches courses like MAT 1362 (Mathematical Reasoning & Proofs) and MAT 2742 (Introduction à l'Algèbre Linéaire Appliquée). His editorial roles include the Canadian Journal of Mathematics and Algebras and Representation Theory. Research Interests: Algebra, Representation Theory, Lie Theory, Categorification, and Quantum Algebra. He has organized conferences such as the Canada-Mexico-USA Conference in Representation Theory and the Algebraic and Geometric Categorification workshop. Advising: Current students include Niccolo Mattarei (PhD), Thomas Moran (PhD), Saima Samchuck-Schnarch (PhD), and Yaolong Shen (Postdoc). Teaching: Courses span undergraduate and graduate levels, emphasizing real analysis, linear algebra, and algebraic structures. Labs/Teams: Leads research in categorification and representation theory within the Department of Mathematics and Statistics.

Roza Galeevaمشاهده پروفایل

مدرس ارشد

• Commodity Markets
• Mathematical Finance
• Dynamical Systems
• +۳ مورد دیگر

Roza Galeeva is a Senior Lecturer in the Department of Applied Mathematics and Statistics at Johns Hopkins University, affiliated with the Whiting School of Engineering. With over 18 years of experience in commodity derivatives—modeling, pricing, and risk management—she bridges academic research and industry practice. Her education includes a PhD in Mathematical Physics from Moscow State University. She transitioned to academia in 2017 after a 13-year career as a senior quantitative analyst at major U.S. energy firms like Morgan Stanley, where she specialized in energy derivatives valuation and risk analysis. Galeeva’s research focuses on commodity markets, mathematical finance, dynamical systems, and geometry. Her work spans foundational studies in dynamical systems to applied financial engineering, including volatility modeling for commodities and energy derivatives. Recent projects emphasize parameterizing commodity futures volatility structures and developing precise pricing models for spread options. Her publications span major journals in mathematics and finance, reflecting contributions across energy risk management, eigenclaim valuation methods, and binomial tree dynamical systems. She has taught extensively in five languages globally, including roles at NYU’s financial engineering program, where she mentored students on commodity derivatives research.

Jan Stühmerمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Molecular Mechanics
• +۷ مورد دیگر

Jun.-Prof. Dr. Jan Stühmer is an Assistant Professor and Principal Investigator (PI) at the Helmholtz Institute for Information Technology (HITS). His research focuses on machine learning, artificial intelligence, and their interdisciplinary applications in molecular mechanics, protein structure prediction, and materials science. He explores advanced graph neural networks, neuro-symbolic systems, and geometric algorithms to address challenges in computational biology, weather forecasting, and computer vision. Key research interests include permutation-invariant learning models (e.g., Set-LLM), error correction in machine learning systems, and the development of physics-based force fields like Grappa. His work bridges theoretical computer science with practical applications in drug design, materials discovery, and climate modeling. Recent contributions highlight innovations in protein design through geometric algebra, dynamic graph representation learning, and the optimization of crystal structure networks. Dr. Stühmer’s methodologies often integrate spatial information learning and ensemble forecasting techniques, showcasing a commitment to impactful, cross-disciplinary research. Despite extensive publications since 2009, no awards or grants are explicitly mentioned in the provided data. His academic trajectory reflects a sustained focus on advancing machine learning fundamentals and their real-world implications.

Cyril Cohenمشاهده پروفایل

پژوهشگر

• Formal Methods
• Interactive Theorem Proving
• Type Theory
• +۱۲ مورد دیگر

Cyril Cohen is a permanent researcher (Chargé de Recherche) at Inria, affiliated with the CASH team in the Laboratoire de l'Informatique du Parallélisme (LIP) at École Normale Supérieure de Lyon (ENS de Lyon), France. He is also associated with CNRS and Université Claude Bernard Lyon 1. Previously, he was a member of the STAMP team at Inria Sophia Antipolis (2014–2024) and completed a postdoctoral position at the University of Gothenburg and Chalmers, Sweden (2012–2014). He earned his PhD in 2012 from École Polytechnique under the supervision of Assia Mahboubi. PhD: École Polytechnique, 2012 Postdoc: University of Gothenburg and Chalmers, 2012–2014 Researcher: Inria STAMP team, 2014–2024 Current: Inria CASH team, LIP, ENS de Lyon His research centers on the formalization of mathematics and programming languages using the Coq proof assistant. Key interests include type theory, formal verification, algebraic structures, real and complex analysis, measure theory, and proof transfer mechanisms. His work bridges theoretical mathematics and practical software verification. He has made foundational contributions to the Coq ecosystem, particularly in the areas of algebraic hierarchies, parametricity, and metaprogramming. The most recent publications reflect a strong trend toward advancing the theoretical and practical foundations of interactive theorem proving. His work spans formalizing classical mathematics (e.g., analysis, Galois theory), developing new logical frameworks (e.g., Cubical Type Theory), and engineering scalable proof automation tools (e.g., Hierarchy Builder, MetaCoq, Trocq). These efforts aim to make formal verification more expressive, efficient, and accessible. Cyril Cohen has not received any explicitly mentioned scientific awards in the provided texts. He has not mentored any PhD or master’s students listed in the provided materials. His research is highly collaborative, involving key figures in the formal methods community such as Assia Mahboubi, Thierry Coquand, and Enrico Tassi. He has contributed to major collaborative grants and projects including the Mathematical Components library, the MetaCoq project, and the development of Hierarchy Builder. These projects often involve multi-institutional and international collaboration. Cohen is a core member of the CASH team at LIP, ENS de Lyon, which focuses on formal methods, proof assistants, and the formalization of mathematics. The team develops and maintains key components of the Coq ecosystem, including libraries for algebra, analysis, and type theory. They also work on meta-tools for Coq such as Elpi and Template-Coq, enabling advanced metaprogramming and reflection.