جستجوی استاد راهنمای دانشگاهی

Maxim Kontsevich has been a permanent professor at the Institut des Hautes Études Scientifiques (IHÉS) since 1995, holding the AXA-IHES Chair for Mathematics . He is also Professor at Rutgers University (one month per year since 1997) and was Professor at University of California, Berkeley (1993–1995). Born 25 August 1964 in Khimki, former USSR, he became a French citizen in 1999. Education: Ph.D. in Mathematics, University of Bonn, March 1992. Research Interests: Prof. Kontsevich’s work lies at the intersection of algebraic geometry , mathematical physics , and quantum theory . He introduced revolutionary ideas in mirror symmetry , non-commutative geometry , and deformation quantization , creating new algebraic structures that have found applications far beyond their original contexts. His current ERC Synergy Grant “ReNew Quantum” (2019-2025) explores recursive and exact new quantum theory . Publications & Trends: Across more than 50 influential papers, Kontsevich has consistently pushed the boundaries of enumerative geometry , motivic integration , and topological field theory . His recent work delves into symplectic aspects of homological algebra , motivic Donaldson-Thomas invariants , non-archimedean geometry , and integrable systems , revealing deep connections between geometry, algebra, and physics. Scientific Awards & Honors: Fields Medal (1998) Crafoord Prize (2008) Shaw Prize in Mathematical Sciences (2012) Breakthrough Prize in Fundamental Physics (2012) Breakthrough Prize in Mathematics (2014) ERC Synergy Grant “ReNew Quantum” (2019) AMS Moore Prize (2025) Doctor Honoris Causa: Aarhus University (2014), Universität Wien (2015), Syddansk Universitet (2023) Member of Académie des Sciences, Institut de France, Academia Europaea, National Academy of Sciences (foreign), London Mathematical Society (honorary) Grants & Leadership: As Principal Investigator of the ERC Synergy Grant “ReNew Quantum” (€10 million, 2019-2025), Kontsevich coordinates an international team advancing exact methods and resurgence in quantum field and string theories. Editorial Service & Community Roles: He serves on the editorial boards of Compositio Mathematica , Publications Mathématiques IHÉS , Journal of Noncommutative Geometry , and several other leading journals, shaping the direction of contemporary mathematical research.

• Algebraic Geometry
• Mathematical Physics
• Mirror Symmetry
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Konstantinos Spiliopoulos is a Professor and Director of Statistics at Boston University's Department of Mathematics and Statistics, part of the College of Arts & Sciences. He leads research in Applied Mathematics and Probability and Statistics groups, focusing on stochastic processes, machine learning, and mathematical finance. His research interests include stochastic analysis of complex systems, multiscale phenomena, and their applications to neural networks, PDEs, and financial modeling. Notable areas of study involve mean-field limits, rare event simulation, and asymptotic methods in stochastic differential equations. He has received grants such as DMS-EPSRC funding for analyzing online training algorithms in recurrent and deep neural networks. His work bridges theoretical advancements with practical applications in data science and computational methods. Spiliopoulos maintains an active presence in interdisciplinary research, addressing challenges in systemic risk, network dynamics, and optimization. His contributions span from fundamental probability theory to applied problems in engineering and finance.

• Stochastic Processes
• Applied Mathematics
• Probability Theory
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Guangqu Zheng is an Assistant Professor in the Department of Mathematics and Statistics at Boston University. He holds a BA from Wuhan University, a Master's from Université Paris-Saclay, and a Ph.D. from the University of Luxembourg. Prior to Boston University, he was a Lecturer at the University of Liverpool and conducted postdoctoral research at the University of Melbourne and the University of Kansas. Education: Ph.D. in Mathematics, University of Luxembourg (2018) Master in Probability, Université Paris-Orsay (2014) BA in Economics and Management, Wuhan University (2011) Research Interests: His work focuses on probability theory, stochastic analysis, and SPDEs. Key areas include Malliavin calculus, Stein’s method, limit theorems, and applications to stochastic partial differential equations. Recent projects involve hyperbolic Anderson models, Lévy noise-driven systems, and spatial ergodicity. Publications: His recent articles explore central limit theorems for SPDEs, hyperbolic models, and applications of Stein’s method. These contributions highlight advancements in stochastic processes and their interdisciplinary applications. Teaching & Advising: At BU, he teaches advanced courses in stochastic analysis and advises students in probability and statistics. Expectations for students include proficiency in real analysis and probability theory.

• Probability Theory
• Stochastic Analysis
• Stochastic Partial Differential Equations (SPDEs)
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Eulàlia Nualart is Associate Professor at Universitat Pompeu Fabra (UPF) under the Serra Hunter Program and an Affiliated Professor at the Barcelona Graduate School of Economics (Barcelona GSE). She serves as Deputy Director of the Barcelona GSE Master Program in Economics. Her academic affiliation is with the Department of Economics and Business at UPF, located at the Jaume I Building on the Ciutadella Campus in Barcelona. Research Interests: Her work centers on stochastic analysis and its applications, particularly in finance. Key areas include Malliavin calculus, stochastic and stochastic partial differential equations (SDEs and SPDEs), fractional Brownian motion, Lévy processes, and statistical inference for parametric models driven by stochastic dynamics. These fields are central to modern probability theory and quantitative finance. Publications and Research Trends: Her research has been published in leading journals such as Stochastic Processes and their Applications , The Annals of Probability , SPDEs: Analysis and Computations , and Journal of Functional Analysis . The body of her work reflects a deep engagement with theoretical probability and its practical modeling implications, especially in financial contexts. Marie Curie Career Integration Grant (2013) Advising and Grants: While specific students are not listed, her role as Deputy Director of a master's program and her publication record suggest active mentorship and research supervision. She secured competitive European funding through the Marie Curie program, indicating strong grant-writing ability and research leadership. No other grants are mentioned in the text. Labs and Research Teams: Though no formal lab is named, she is embedded in the research ecosystem of the Department of Economics and Business at UPF and collaborates with the Barcelona GSE, a major hub for economics and finance research in Europe. Her work likely contributes to broader research groups focused on mathematical economics and financial modeling.

• Stochastic Analysis
• Malliavin Calculus
• Stochastic Differential Equations (SDEs)
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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.

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

Jason Swanson is an Associate Professor in the Department of Mathematics at the University of Central Florida, specializing in stochastic processes and probability theory. His research encompasses stochastic differential equations, fractional Brownian motion, and the foundations of probability. Recent work includes developing the iterated Dirichlet process for Bayesian inference and extending representations for row-exchangeable arrays. He maintains an active research program connecting mathematical logic with probability theory. Teaching responsibilities include graduate courses in Measure and Probability (MAA 6238) and undergraduate probability (MAP 4113). His lecture notes on measure-theoretic probability are publicly available.

• Stochastic Differential Equations
• Probability Theory
• Mathematical Logic
• +۲ مورد دیگر

Professor Massimiliano Gubinelli is the Wallis Professor of Mathematics at the University of Oxford and a Professorial Fellow at St. Anne's College. He leads the Stochastic Analysis Group within the Mathematical Institute, where his research focuses on stochastic analysis, constructive quantum field theory, and the intersection of probability theory with partial differential equations (PDEs) and renormalization group methods. His work spans statistical mechanics of multiscale systems, analysis of PDEs with random terms, homogenisation theory, mathematical quantum mechanics, path-integral formalisms, and non-commutative probability/geometry. He has pioneered paracontrolled distribution techniques to study singular stochastic PDEs and explored rough paths in ramification and transport equations. Recent publications highlight advancements in the sine-Gordon model via stochastic quantization, nonlinear PDEs with modulated dispersion, and ρ-irregularity in stochastic systems. His research bridges stochastic analysis, quantum field theory, and PDEs, emphasizing pathwise behavior and renormalization. Scientific Awards Junior member of the Institut Universitaire de France (2013–2018) Invited session speaker at the 2018 International Congress of Mathematicians (ICM) in Rio He contributes to scientific software development as a lead developer of TeXmacs , an open-source platform for technical documents, and teaches courses such as C8.1 Stochastic Differential Equations (MT22). No formal student advisement or grant details are provided.

• Stochastic Analysis
• Constructive Quantum Field Theory
• Statistical Mechanics of Multiscale Systems
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Felix Otto is a Director at the Max Planck Institute for Mathematics in the Sciences and an Honorary Professor for Analysis and Mathematical Modeling at the University of Leipzig. His research focuses on pattern formation, energy landscapes, and scaling laws, with contributions to stochastic homogenization, PDEs, and optimal transport. He has held academic positions at the University of California and the Hausdorff Center for Mathematics. Notable grants include projects on microstructure formation in thin coatings and stochastic homogenization. He has organized conferences such as the ICM satellite conference on Probability and Mathematical Physics. His work bridges pure and applied mathematics, with implications for materials science and fluid dynamics. Education: Diplom (1990), PhD (1993) from Bonn University. Postdoctoral roles at Bonn, Courant Institute, and CMU. Tenured faculty roles at UCSB (1998–2010) and Bonn (1999–2010). Research interests span stochastic PDEs, calculus of variations, and the mathematical theory of materials. Grants include BMBF and DFG projects on microstructure modeling and homogenization.

• Mathematical Analysis
• Partial Differential Equations
• Stochastic Homogenization
• +۴ مورد دیگر

Xue-Mei Li is a Professor of Mathematics at Imperial College London and École Polytechnique Fédérale de Lausanne (EPFL). She holds chairs in Probability and Stochastic Analysis at both institutions. Her research focuses on stochastic analysis, geometric stochastic processes, and multi-scale systems, with contributions to areas like Malliavin calculus, fractional dynamics, and coarse curvature. Li has held positions at the University of Warwick, University of Connecticut, and others, supported by fellowships from the Alexander von Humboldt Foundation, Royal Society, and MSRI. Her work addresses fundamental questions in stochastic differential equations, geometric analysis, and their applications to complex systems. Education and Career: PhD in Mathematics, University of Warwick EPSRC Research Associate Faculty positions at the University of Connecticut (tenured Associate Professor) Research Interests: Her research spans stochastic differential equations (SDEs), stochastic partial differential equations (SPDEs), geometric stochastic analysis, and fractional dynamics. Notable contributions include the BEL formula, strict local martingales, and solutions to longstanding problems in strong completeness on non-compact manifolds. She explores interactions between stochastic processes and geometric structures, including coarse Ricci curvature and homogenization theory. Awards and Grants: Supported by NSF, EPSRC/UKRI, and Swiss NSF grants Awarded fellowships from Alexander von Humboldt Foundation, Royal Society, and MSRI Advising and Teams: PhD students: Johann Gehringer, Rhys Steel, Julian Sieber, and others Leading working groups on stochastic analysis and geometric dynamics

• Stochastic Analysis
• Geometric Stochastic Analysis
• Malliavin Calculus
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Dr. Panqiu Xia is a Lecturer in the School of Mathematics at Cardiff University since Autumn 2024. His research focuses on theoretical and applied probability, with expertise in stochastic partial differential equations (SPDEs) and chemical reaction networks (CRNs). Previously, he held postdoctoral positions at Auburn University (USA) and the University of Copenhagen (Denmark). He earned his Ph.D. in Mathematics from the University of Kansas (USA) in 2020 under the supervision of Professors Yaozhong Hu and David Nualart. His research interests include Malliavin calculus, Stein's method, and the analysis of SPDEs such as the parabolic Anderson model and super-Brownian motions. In CRN studies, he investigates stationary distributions and stochastic modeling of biochemical systems. His work bridges pure probability theory with applications in mathematical biology and statistical physics. Dr. Xia has taught courses in statistics, stochastic analysis, and numerical methods at institutions including Auburn University and the University of Copenhagen. His educational background includes a BSc from Wuhan University (China) and an MSc from the University of Macau. Key research themes include the long-term behavior of SPDE solutions, intermittency phenomena, and ergodic properties. His contributions span both theoretical advancements in stochastic analysis and applied problems in chemical reaction systems.

• Stochastic Partial Differential Equations
• Chemical Reaction Networks
• Malliavin Calculus
• +۳ مورد دیگر

Patrick Pun is an Associate Professor in the Division of Mathematical Sciences at Nanyang Technological University (NTU), Singapore, serving as Assistant Chair (MSc Programs) and Director of the MSc in FinTech program within the School of Physical and Mathematical Sciences. His academic journey includes a Ph.D. and M.Phil. from the Chinese University of Hong Kong (CUHK) and a B.Sc. from Nankai University. Professor Pun’s research focuses on the intersection of applied mathematics and finance, with methodologies spanning stochastic controls, nonlinear partial differential equations (PDEs), robust optimization, and machine learning. His work addresses challenges in portfolio optimization, derivatives pricing, risk management, and financial data analysis. He has also contributed to interdisciplinary areas such as nanoparticle characterization and epidemiological modeling (e.g., during the COVID-19 pandemic). Award-winning scholar, Pun holds the 2016 Nicola Bruti Liberati Prize from the Bachelier Finance Society and the CUHK Young Scholars Thesis Award. He is an ad-hoc reviewer for leading journals including Automatica , SIAM Journal on Financial Mathematics , and Quantitative Finance . His professional roles include membership in the Academic Council of the Global Digital Economy Forum. Pun’s teaching and academic leadership include oversight of master’s programs and curriculum development. His research outputs emphasize innovative solutions to time-inconsistent problems, high-dimensional financial data challenges, and the integration of machine learning with traditional financial models. His recent work explores transformer-based generative models, quantum algorithms for financial PDEs, and reinforcement learning applications in portfolio management.

• Applied Mathematics
• Financial Mathematics
• Quantitative Finance
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Professor Dan Crisan is a Professor of Mathematics at Imperial College London and Director of the EPSRC Centre for Doctoral Training in the Mathematics of Planet Earth. He holds a PhD in Mathematics from the University of Edinburgh and an MSci in Mathematics from the University of Bucharest. His research focuses on Stochastic Analysis, Stochastic PDEs, Fluid Dynamics, Nonlinear Filtering, and Data Assimilation. He leads the Stochastic Transport in Upper Ocean Dynamics (STUOD) project, supported by an ERC Synergy Grant, exploring stochastic models in geophysical fluid dynamics. His academic roles include directing the MPE CDT and teaching advanced courses like Stochastic Calculus with Applications to Non-Linear Filtering. He collaborates extensively with researchers globally on topics including stochastic fluid dynamics, particle methods, and Bayesian inference. His work bridges theoretical advancements with applications in climate modeling and environmental systems. Education: PhD (University of Edinburgh, 1996), MSci (University of Bucharest, 1992). Professional roles include Director of MPE CDT (2013–present), Professor at Imperial College (2011–present), and prior academic appointments at the University of Cambridge and Imperial College. His research emphasizes stochastic processes in fluid dynamics, with projects funded by EPSRC and EU grants. Current PhD supervision opportunities are available in areas like stochastic fluid dynamics and data assimilation. Key achievements include foundational contributions to particle filtering, numerical methods for stochastic PDEs, and stochastic transport models. His work on the Camassa-Holm equation and rotating shallow water models demonstrates expertise in nonlinear wave dynamics and stochastic parametrization. He actively engages in international collaborations and serves on editorial boards for leading journals in stochastic analysis.

• Stochastic Analysis
• Fluid Dynamics
• Stochastic Partial Differential Equations (SPDEs)
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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.

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

Michele Coghi is an Associate Professor in the Department of Mathematics at the University of Trento. He specializes in probability theory, stochastic differential equations, and their applications to mathematical physics and nonlinear partial differential equations. His research explores rough path analysis, mean-field models, and turbulence phenomena in fluid dynamics, with a focus on stochastic frameworks. He teaches courses such as Biostatistics and Statistical Methods across multiple departments, including the Department of Cellular, Computational and Integrative Biology (CIBIO) and the Department of Information Engineering and Computer Science. His work bridges theoretical mathematics with practical applications in data science and computational biology. Michele Coghi's recent publications emphasize rough stochastic calculus, nonlocal diffusion processes, and robust data assimilation techniques like ensemble Kalman filtering. His research on McKean-Vlasov dynamics and interacting particle systems highlights his contributions to stochastic modeling and mathematical fluid dynamics.

• Probability and Mathematical Statistics
• Stochastic Differential Equations
• Malliavin Calculus
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Prof. Nan Chen is a Professor in the Department of Systems Engineering and Engineering Management at The Chinese University of Hong Kong (CUHK). He holds a PhD from Columbia University (2006) and directs the Bachelor of Engineering in Financial Technology (FinTech) and the Master of Science in Financial Engineering at CUHK-Shenzhen. His research focuses on quantitative finance, systemic risk, Monte Carlo simulation, and reinforcement learning. He has authored over 40 papers in top journals like Operations Research and Review of Financial Studies . Education : BSc and MSc in Probability & Statistics, Peking University (1998–2001) MPhil/PhD in Operations Research, Columbia University (2005–2006) Research Interests : FinTech and quantitative finance Systemic risk modeling and network analysis Reinforcement learning and stochastic control Monte Carlo methods and computational finance Awards & Grants : Best Student Paper Award, INFORMS (2006) Exemplary Teaching Awards (2009, 2017) Over HK$7M in GRF grants (2008–2023) Second Prize, Jiangsu Province Social Science Award (2023) Public Service : Member of Hong Kong's Payment Systems Tribunal and Insurance Appeals Tribunal, and reviewer for major journals like Mathematical Finance and Operations Research . Key Contributions : Pioneered Ito-Taylor expansions for diffusion models, dual methods for stochastic control, and liquidity risk frameworks. Led development of Hong Kong's first FinTech undergraduate program.

• Financial Engineering
• FinTech
• Quantitative Finance
• +۷ مورد دیگر