جست‌وجوی استاد و پژوهشگر

Xin Guoمشاهده پروفایل

استاد

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

Xin Guo is Professor and Department Chair of Industrial Engineering and Operations Research (IEOR) at UC Berkeley's College of Engineering, holding the Coleman Fung Chair in Financial Modeling. Her research bridges mathematical finance, stochastic control, and machine learning with applications in risk analytics and quantitative trading. Education: Ph.D. in Mathematics, Rutgers University (1999) Research Interests: Professor Guo's work centers on mathematical finance , stochastic games , and reinforcement learning . She develops theoretical frameworks for α-potential games and mean-field systems while applying signature methods and GANs to financial data. Her research addresses critical problems in portfolio optimization, fraud detection (e.g., Medicare analytics), and market forecasting, emphasizing the intersection of stochastic control with machine learning for real-world decision-making under uncertainty. Publication Trends: Recent work (2023-2025) shows increasing focus on multi-agent reinforcement learning through mean-field game theory, with applications spanning finance (corporate bonds, trading), healthcare (fraud detection), and transportation (rate forecasting). Key innovations include BSDE approaches for stochastic games, signature-based time series analysis, and theoretical guarantees for GAN training dynamics. Scientific Awards: Holds the prestigious Coleman Fung Chair in Financial Modeling, reflecting significant contributions to quantitative finance research. Advising and Grants: As IEOR Department Chair, Professor Guo mentors graduate students in stochastic modeling and financial engineering. Her research is supported by the Coleman Fung Endowment Fund, with collaborations spanning finance, healthcare, and transportation sectors through industry partnerships. Labs and Teams: Leads the Risk Analytics & Data Analysis Research (RADAResearch) Lab ( https://risklab.ieor.berkeley.edu/ ), which develops cutting-edge methodologies for risk assessment, data-driven decision-making, and game-theoretic solutions to complex systems. The lab fosters interdisciplinary work connecting mathematical theory with practical applications in FinTech and beyond.

• Stochastic Analysis
• Mathematical Finance
• Systemic Risk
• +۲ مورد دیگر

Rama Cont is Statutory Professor of Mathematics at the University of Oxford and Head of the Oxford Mathematical and Computational Finance Group. He holds additional positions as Senior Research Fellow at the Institute for New Economic Thinking and Director of the Oxford Martin Programme on Systemic Resilience. Cont's research focuses on stochastic analysis and mathematical finance, particularly modeling extreme market risks, systemic risk, and developing pathwise approaches in stochastic analysis. His recent work explores causal functional calculus, fractional Ito calculus, and analysis of deep neural networks. His publications demonstrate consistent development of mathematical frameworks for financial risk analysis, including recent advances in causal transport theory and market microstructure modeling. Cont received the Louis Bachelier Prize in 2010 and was elected SIAM Fellow in 2017 for contributions to stochastic analysis and financial modeling.

• Stochastic Analysis
• Rough Analysis
• Functional Ito Calculus
• +۵ مورد دیگر

Prof. Rama Cont is a Statutory Professor of Mathematics at the University of Oxford and a Professorial Fellow at St Hugh's College . He serves as Director of the Centre for Doctoral Training in Mathematics of Random Systems , Faculty Member of the Stochastic Analysis Group , and Senior Research Fellow at the Institute for New Economic Thinking . Additional roles include Director of the Oxford Martin Programme on Systemic Resilience , Principal Investigator at the Oxford Suzhou Centre for Advanced Research , and Editor-in-Chief of Mathematical Finance . His research interests span pathwise methods in stochastic analysis, rough analysis, functional Ito calculus, mathematical modeling in finance, systemic risk, and data-driven decision systems. Recent publications focus on causal transport, rough volatility, and deep residual networks, reflecting his interdisciplinary approach to mathematics and finance. Functional Ito calculus and pathwise integration Rough volatility and financial market dynamics Systemic risk in financial networks Deep learning applications to finance and stochastic processes He has received prestigious awards including the Louis Bachelier Prize , SIAM Fellowship, Royal Society APEX Award, and IMA Fellowship. His editorial roles and seminar leadership underscore his influence in mathematical finance and stochastic analysis.

Miroslav Krsticمشاهده پروفایل

استاد

• Control Theory
• Nonlinear Systems
• Adaptive Control
• +۵ مورد دیگر

Miroslav Krstic is a Distinguished Professor of Mechanical and Aerospace Engineering at the University of California, San Diego (UCSD), and serves as Senior Associate Vice Chancellor for Research overseeing 17 research institutes, postdoctoral affairs, and shared facilities. He leads the Center for Control Systems and Dynamics and the Naval Innovation, Science, and Engineering Center (NISEC). Education: PhD (1994) and MS (1992) from University of California, Santa Barbara, under advisor Petar Kokotovic. BSc (1989) from University of Belgrade, Yugoslavia. Research Interests: Pioneered methods in control theory including PDE backstepping, extremum seeking, nonlinear adaptive control, and delay compensation. Focuses on applications in chip manufacturing, aircraft carriers, particle accelerators, Mars rovers, and traffic congestion. Integrates machine learning with control design for PDE systems. Awards: Over 30 major honors including the Bellman Award, Reid Prize, Oldenburger Medal, Bode Lecture Prize, and Fellowships from AAAS, SIAM, ASME, IEEE, and IFAC. Recognized as the world's top control theorist by ScholarGPS. Service & Grants: Editor-in-Chief of IEEE Transactions on Automatic Control and Systems & Control Letters . Directed over $100M in research funding annually. Advised 30+ PhD students and postdocs, many in industry leadership roles. Industry Impact: Technologies deployed in EUV lithography (Cymer/ASML), US Navy aircraft carrier arresting gear (General Atomics), and NASA's Mars Curiosity Rover laser system. Contributions to fusion control, battery estimation, and combustion optimization.

Fima Klebanerمشاهده پروفایل

استاد

• Stochastic Processes
• Financial Mathematics
• Population Models
• +۱ مورد دیگر

Fima Klebaner is Professor in the School of Mathematics at Monash University and Director of the Centre for Modelling of Stochastic Systems. His research spans stochastic processes, financial mathematics, and population biology, with emphasis on limit theorems, branching processes, and diffusion models. Current projects include ARC-funded work on stochastic population dynamics and financial derivatives pricing. Key research areas: 1) Population-dependent stochastic systems; 2) Large deviation principles; 3) Financial mathematics (Dupire formula, volatility); 4) Approximation methods for complex processes. Recent publications (2018-2025) show balanced focus on theoretical probability (45%) and applied modeling (55%), particularly in ecology and finance. Article analysis reveals advanced methodologies in: 1) Stochastic calculus applications (33% of recent works); 2) Limit theorems for interacting systems (27%); 3) Financial mathematics innovations (20%). Theoretical contributions frequently interface with biological and financial applications.

Christa Cuchieroمشاهده پروفایل

استاد

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

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

Martin Hairerمشاهده پروفایل

استاد

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

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

Francesco Russoمشاهده پروفایل

استاد

• Stochastic Analysis
• Financial Mathematics
• Probabilistic Models in Mathematical Physics

Francesco Russo is a Professor of Exceptional Class at ENSTA Paris under the Applied Mathematics Unit (UMA) . He has held academic positions at INRIA-Ecole des Ponts (2008-2010) and Paris 13 University (1994-2008) , where he led the Probability and Statistics Team and the Financial Engineering Option in the MACS course. His research spans Stochastic Analysis , Financial Mathematics , and Probabilistic Models in Mathematical Physics , with applications to energy systems, control theory, and nonlinear PDEs. He co-organizes international seminars and conferences, including the Seminar in Probability-Statistics-Control and the Day Around Stochastic PDEs . Research Themes : Stochastic calculus via regularization, path-dependent PDEs, BSDEs, non-semimartingale models, fractional Brownian motion, and McKean-Vlasov equations with irregular coefficients. Projects : Leads the SDAIM (2023-27) project funded by ANR (France) and FAPESP (Brazil). Coordinated the ANR MASTERIE (2011-2013) program. Teaching : Courses include Elementary Stochastic Calculus (ENSTA), Discrete Models in Finance (ENSTA), and Stochastic Calculus (Master Paris-Saclay). Collaborations : Organizes seminars with institutions such as Luiss University (Rome) and EPFL (Lausanne). Collaborates with Brazilian teams (UNICAMP) and French institutions (CMAP, CentraleSupélec).

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

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

Jason Swansonمشاهده پروفایل

دانشیار

• Stochastic Differential Equations
• Probability Theory
• Mathematical Logic
• +۲ 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.

Maxim Raginskyمشاهده پروفایل

استاد

• Probability and Stochastic Processes
• Control Theory
• Machine Learning
• +۵ مورد دیگر

Maxim Raginsky is a Professor at the University of Illinois at Urbana-Champaign, holding appointments in the Department of Electrical and Computer Engineering, Coordinated Science Laboratory, and a courtesy appointment in Computer Science. His work bridges probability, stochastic processes, control theory, machine learning, optimization, and information theory , focusing on modeling, learning, and simulation of nonlinear dynamical systems with applications to advanced electronics, autonomy, and artificial intelligence. Research Interests Nonlinear dynamical systems in machine learning and control Statistical machine learning theory Information-theoretic methods in learning Stochastic control and filtering Scientific Contributions Co-author of foundational monographs on concentration inequalities and generalization bounds Recipient of the NSF CAREER Award (2013) , IEEE Fellow (2025) , and Roberto Tempo Best CDC Paper Award (2024) Editorial roles in Foundations and Trends in Machine Learning , Journal of Machine Learning Research , and SIAM Journal on Mathematics of Data Science Academic Leadership Advising 15+ graduate students and postdocs including Joshua Hanson, Belinda Tzen, and Tanya Veeravalli Teaching core graduate courses: Control of Stochastic Systems , Statistical Learning Theory , Optimization by Vector Space Methods

Xue-Mei Liمشاهده پروفایل

استاد

• Stochastic Analysis
• Geometric Stochastic Analysis
• Malliavin Calculus
• +۵ 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

• Probability Theory
• Financial Mathematics
• Stochastic Processes

Paul Eisenberg is an Assistant Professor at the Institute for Statistics and Mathematics at Vienna University of Economics and Business. He holds a doctorate in Mathematics and has held positions at the University of Liverpool, Vienna University of Technology, and Technical University of Dortmund. His research focuses on probability theory and financial mathematics, particularly stochastic processes, term structure modeling, and applications to financial markets. He teaches courses in Probability, Quantitative Methods, and Business Mathematics. Research outputs concentrate on stochastic processes in finance, including term structure modeling, stochastic optimization, market microstructure, and applications to cryptocurrency markets. Recent work shows emphasis on regime-switching models and high-dimensional stochastic systems.

Purba Dasمشاهده پروفایل

مدرس

• Stochastic Analysis
• Mathematical Finance
• Financial Mathematics
• +۳ مورد دیگر

Dr. Purba Das is a Lecturer in Financial Mathematics at King's College London's Department of Mathematics, part of the Faculty of Natural, Mathematical & Engineering Sciences. She holds a DPhil from the University of Oxford (2022), specializing under Prof. Rama Cont, and prior degrees from Chennai Mathematical Institute (M.Sc. 2018, B.Sc. 2016). Her research focuses on stochastic analysis with applications to mathematical finance, particularly pathwise methods and rough volatility modeling. Education: DPhil (Oxford, 2022), M.Sc. (Chennai Mathematical Institute, 2018), B.Sc. (Chennai Mathematical Institute, 2016). Research interests include rough path theory, microstructure noise analysis, and functional Itô calculus. Recent work explores rough volatility's empirical validity, depositor behavior in digital banking systems, and Hölder continuity in function spaces. She co-organizes conferences on stochastic calculus and financial stability. Grants include £10k from KCL-IIT Madras Partnership and £5k from KCL's NMES Fund. Active in teaching financial mathematics and stochastic processes at both King’s and the University of Michigan.

Alexander Schiedمشاهده پروفایل

استاد

• Quantitative Finance
• Probability Theory
• Stochastic Analysis
• +۴ مورد دیگر

Alexander Schied is a Professor of Statistics and Actuarial Science at the University of Waterloo, holding the Munich Re Chair in Stochastic Finance and a University Research Chair. His research focuses on quantitative finance, probability theory, and stochastic analysis, with applications to risk measurement, financial modeling, and market microstructure. He co-authored the seminal textbook Stochastic Finance: An Introduction in Discrete Time (5th ed., 2025) and serves as Co-Editor of Finance and Stochastics . Before joining Waterloo, Schied held positions at the University of Mannheim, TU Munich, Cornell University, and TU Berlin. He earned his doctorate in mathematics from the University of Bonn. His work bridges theoretical advancements in stochastic processes with practical applications in finance, including robust optimization, model uncertainty, and high-frequency trading dynamics. His recent research explores rough volatility models , pathwise Itô calculus , and market impact games , with publications in top journals like Annals of Applied Probability and Mathematical Finance . His contributions to risk management and stochastic analysis have positioned him as a leading figure in mathematical finance. Awards & Roles: Munich Re Chair in Stochastic Finance (University of Waterloo) University Research Chair (University of Waterloo) Co-Editor, Finance and Stochastics Editorial Board Member: Applied Mathematics and Optimization , Mathematical Finance , and SIAM Financial Mathematics series Key Themes in Publications (2020–2025): Model-free portfolio theory and continuous-time optimization Rough stochastic volatility and Hurst parameter estimation Market impact dynamics and game-theoretic models Robust risk measures and optimization under uncertainty