جست‌وجوی استاد و پژوهشگر

Boualem Djehicheمشاهده پروفایل

استاد

• Stochastic Analysis
• Stochastic Control
• Insurance Mathematics
• +۸ مورد دیگر

Boualem Djehiche is a Professor of Mathematical Statistics at the Department of Mathematics, KTH Royal Institute of Technology. He is affiliated with the Digital Futures Faculty and the SCI School at KTH. His research focuses on Stochastic Analysis, including Stochastic Control, Insurance Mathematics, Mathematical Finance, and Game Theory. Djehiche holds editorial roles in journals such as Scandinavian Actuarial Journal and Finance and Stochastics . Education details are not explicitly stated in the provided texts. His teaching responsibilities include courses like Game Theory, Probability Theory, and Financial Mathematics. He advises students in these areas, though explicit student names are not listed. His research explores advanced topics such as mean-field games, time-inconsistent optimal control, and applications in finance and economics. Recent publications address topics like zero-sum Dynkin games, generative AI outcomes as Nash equilibria, and commodity futures pricing with regime switching. Research Interests: Stochastic Control, Insurance Mathematics, Mathematical Finance, Mean-Field Games, System Identification. Editorial Duties: Editor-in-Chief of Scandinavian Actuarial Journal , Associate Editor of Finance and Stochastics , and roles in multiple other journals. Grants & Collaborations: Collaborations include work on disability insurance modeling, credit scoring, and energy market dynamics via mean-field-type games. Labs/Teams: Involved in cross-disciplinary initiatives like the Digital Futures research center, focusing on digital technologies and societal challenges.

• Finance
• Asset Pricing
• Portfolio Management
• +۵ مورد دیگر

René Garcia is an Associate Professor in the Department of Economics at the Faculty of Arts and Sciences, University of Montreal. He maintains an office in Pavillon Lionel-Groulx, room C6031, and is also designated as an Honorary Professor, reflecting his distinguished career. Garcia is actively affiliated with CIREQ (Centre interuniversitaire de recherche en économie quantitative), a major research center in quantitative economics. His research expertise spans several key areas: Asset pricing and financial market analysis Portfolio management and risk assessment Non-linear econometric modeling Regime-switching processes in financial markets Stochastic discount factors and performance evaluation Garcia's scholarly work focuses on developing theoretical frameworks that integrate time and state dependencies in pricing models, with significant contributions to understanding information processing in economic decision-making and price stickiness phenomena. His research bridges theoretical economics with practical financial applications, particularly in emerging markets contexts as evidenced by his work on the Brazilian stock market. His current research trajectory shows continued productivity with multiple active projects extending through 2026, including work on Markov switching processes, reinforcement learning applications in portfolio choice, and advanced financial econometrics. Garcia has secured substantial research funding from major Canadian institutions: CRSH/Conseil de recherches en sciences humaines du Canada CRSNG/Conseil de recherches en sciences naturelles et génie du Canada MITACS Inc. FRQSC/Fonds de recherche du Québec - Société et culture As an educator, Garcia has supervised numerous PhD students since 1999, with his most recent advisee completing in 2023. His supervision record demonstrates his commitment to training the next generation of economists and financial researchers, with students exploring diverse topics in empirical asset pricing, climate finance, and quantitative financial methods.

Wei Weiمشاهده پروفایل

استادیار

• Behavioural Economics
• Financial Mathematics
• Time-Inconsistent Decision Making
• +۴ مورد دیگر

Dr. Wei Wei is an Assistant Professor in the Department of Actuarial Mathematics and Statistics at Heriot-Watt University, part of the School of Mathematical & Computer Sciences. He holds a PhD from the University of Oxford and previously worked as a postdoctoral researcher at the University of Waterloo. His research focuses on behavioral economics, time-inconsistent decision making, stochastic control, and applications of deep learning in dynamic models. He teaches courses such as F70TS: Time Series and Machine Learning. Education: PhD in Mathematical and Computational Finance (University of Oxford, 2017); MSc in Mathematics (Tongji University, 2012); BSc in Mathematics (Tongji University, 2009). Research interests include collective decision making, risk management, and financial engineering. His work bridges theoretical frameworks (e.g., HJB equations, optimal stopping) with practical applications in reinsurance, investment, and algorithm design. He collaborates internationally and contributes to journals like SIAM Journal on Control and Optimization and the Journal of Economic Theory. Grants and funding details are not explicitly listed, but his publications suggest engagement with topics requiring computational and theoretical resources. He is affiliated with the Maxwell Institute for Mathematical Sciences and serves as a reviewer for multiple top-tier journals.

Aleksey S. Polunchenkoمشاهده پروفایل

دانشیار

• Statistics
• Sequential Analysis
• Quickest Change-Point Detection
• +۲ مورد دیگر

Aleksey S. Polunchenko serves as an Associate Professor in the Department of Mathematics and Statistics within Harpur College of Arts and Sciences at Binghamton University (SUNY), where he has been affiliated since 2012. His academic foundation includes a Ph.D. from the University of Southern California (2009). Contact details confirm active status: Office WH-129, phone (607) 777-6901, and email aleksey@binghamton.edu. Research Interests: Specializing in mathematical statistics with intense focus on sequential analysis and quickest change-point detection. His work addresses composite hypotheses in change-point theory, developing rigorous frameworks for Shiryaev-Roberts procedures and quasi-stationary distributions. Primary applications span cybersecurity, financial surveillance, and anomaly detection in autocorrelated systems. Recent scholarly output demonstrates consistent expertise in stochastic diffusion models and asymptotic optimality. His publications analyze exit times, fractional moments, and performance metrics of change-point detectors, with notable emphasis on mathematical precision in continuous-time and Brownian motion setups. Teaching & Service: Currently instructs MATH 147 (Elementary Statistics) and MATH 458 (Time Series), while contributing to the Statistics Seminar series. His work is accessible via arXiv, Google Scholar, and ResearchGate, with an ORCID identifier (0000-0001-8025-4059) for scholarly tracking.

• Probability Theory
• Stochastic Processes
• Brownian Motion
• +۵ مورد دیگر

Paavo Salminen is a faculty member in the Mathematics department at the Faculty of Natural Sciences and Engineering. With a prolific publication record spanning from 1990 to 2025, he has established himself as a prominent researcher in probability theory and stochastic processes. His research interests primarily focus on: Brownian Motion and its variants Optimal Stopping problems Diffusion processes and spider processes Excessive functions and Green kernels Theta functions and their probabilistic aspects Markov processes and their applications Salminen's recent work demonstrates a continued focus on theoretical aspects of stochastic processes with applications in mathematical finance and other fields. His publications show consistent contributions to understanding diffusion processes, optimal stopping problems, and the mathematical properties of Brownian motion variants. The research spans both theoretical developments and potential applications in financial mathematics and other domains requiring sophisticated stochastic modeling techniques. His scientific contributions include: 34 publications documented between 2009-2024 Multiple collaborations with international researchers including Christophe Vignat, Ernesto Mordecki, and Pierre Vallois Hosting academic visitors at his institution in 2022 and 2024 Salminen maintains an active research program, with several publications appearing in 2024 and even some listed for 2025, indicating ongoing productive research activities. His work bridges pure probability theory with potential applications in mathematical finance and other fields requiring advanced stochastic modeling techniques.

Juan J. Manfrediمشاهده پروفایل

استاد

• Partial Differential Equations
• Nonlinear Analysis
• Subelliptic Equations
• +۴ مورد دیگر

Juan J. Manfredi is a Professor of Mathematics at the University of Pittsburgh's Department of Mathematics, part of the Dietrich School of Arts and Sciences. He holds a PhD from Washington University in St. Louis, focusing on quasiregular mappings and partial differential equations. His research emphasizes elliptic and parabolic PDEs of p-Laplacian type, sub-Riemannian manifolds, and game-theoretic interpretations of equations like the infinity Laplacian. He explores regularity properties of p-harmonic functions and their applications in stochastic processes and signal processing. His work spans nonlinear potential theory, subelliptic equations, and geometric analysis. Notable contributions include studies on Monge-Ampère equations, viscosity solutions, and the interplay between stochastic games (e.g., tug-of-war) and PDEs. He has collaborated on topics like Carnot groups, Heisenberg group geometry, and Riemannian approximations in sub-Riemannian settings. Recent publications highlight advancements in asymptotic mean-value formulas, BMO estimates for solutions, and convergence principles for dynamic programming. His research bridges pure analysis and applied problems, including mass transport and optimal control. While no formal awards are listed, his extensive bibliography and academic roles reflect significant scholarly impact. Manfredi maintains an active online presence with resources like the QuasiWorld page, offering lecture notes and computational tools. His work often intersects with probability, geometric analysis, and numerical methods, positioning him at the forefront of modern nonlinear PDE research.

• Financial Mathematics
• Stochastic Analysis
• Derivatives Pricing
• +۴ مورد دیگر

Professor Marek Rutkowski is a distinguished academic at The University of Sydney, Faculty of Science, Department of Applied Mathematics. He serves as a Professor specializing in Financial Mathematics, with a research focus on Stochastic Analysis and its applications to financial markets. His work directly impacts investment banks, hedge funds, and other financial institutions worldwide through modeling financial markets, pricing derivatives contracts, and understanding risk. Professor Rutkowski is a member of the Applied Mathematics Research Group with specific research areas including exotic options, interest rate derivatives, credit derivatives, stochastic volatility modeling, foreign exchange derivatives, multi-person game options, hedging of financial derivatives under funding costs, counterparty credit risk, credit and funding valuation adjustment, and problems related to enlargements of filtrations. His current research is devoted to nonlinear arbitrage pricing theory and nonlinear optimal stopping problems with applications to valuation of American and game options in financial markets with frictions. His research aligns with the Faculty of Science Research Strengths in Understanding the Universe, Fundamental Laws of Nature, Complex Systems, Data and Decisions, and National Security. Professor Rutkowski has co-authored several influential monographs including 'Credit Risk Modeling' (Osaka University Press, 2009), 'Martingale Methods in Financial Modelling' (2nd edition, Springer, 2005), 'Credit Risk: Modelling, Valuation and Hedging' (Springer, 2002), and the first edition of 'Martingale Methods in Financial Modelling' (Springer, 1997). He also co-edited 'Inspired by Finance. The Musiela Festschrift' (Springer, 2014). His editorial contributions include: Finance and Stochastics (1997-2017) Mathematical Finance (since 2000) International Journal of Theoretical and Applied Finance (2007-2022) International Journal of Portfolio Analysis and Management (since 2011) Probability, Uncertainty and Quantitative Risk (since 2016) Professor Rutkowski has supervised numerous PhD students including Libo Li, Ivan Guo, Silvio Tarca, Desmond Ng, Edward Kim, Tal Morgenstern, Huansang Xu, and Yining Ding. His research has been supported by multiple Australian Research Council Discovery Projects including 'Can green investors drive the transition to a low emissions economy?' (2022), 'Fair pricing of superannuation guaranteed benefits with downturn risk' (2020), and 'Non-Linear Arbitrage Pricing of Multi-Agent Financial Games' (2015). Professor Rutkowski maintains strong international collaborations with researchers in China (Shandong University), France (Universite Paris-Saclay), United Kingdom (Imperial College and King's College London), and the United States (Illinois Institute of Technology).

• Machine Learning Theory
• Game Theory
• Information Theory
• +۹ مورد دیگر

Wouter M. Koolen is a Professor of Mathematical Machine Learning at the University of Twente and a Senior Researcher in the Machine Learning group at Centrum Wiskunde & Informatica (CWI) in Amsterdam. Appointed to his professorship on June 1, 2022, he delivers his expertise across both institutions with offices in Enschede and Amsterdam. He is actively engaged in academic leadership through his organization of the Machine Learning Theory Research Semester Programme at CWI in Spring 2023 and serves as an ELLIS Scholar since December 2020. Dr. Koolen's research spans machine learning theory with particular focus on pure exploration in multi-armed bandit models , game tree search algorithms , and provably accelerated learning in both statistical and individual-sequence settings, which he characterizes as 'learning faster from easy data.' His work bridges theoretical foundations with practical applications, especially in safe statistical testing using e-values. He maintains active collaborations through INRIA-CWI associate teams 6PAC with Inria Lille and 4TUNE with Inria Paris and Grenoble. His recent publications reveal a strong emphasis on developing theoretically sound methods for statistical inference that maintain validity under optional stopping and continuation, representing a significant shift from traditional p-value based approaches. This work has important implications for fields requiring rigorous statistical guarantees in adaptive experimental settings. NWO VENI grant recipient QUT Vice-Chancellor's postdoctoral research fellowship awardee ELLIS Scholar (elected December 2, 2020) Member of ACM Future of Computing Academy Professor Koolen has supervised numerous PhD students to completion, including Hongwei Wen, Clément Lezane, and Tyron Lardy in 2025, and formerly Rianne de Heide who won the VVSOR Willem R. van Zwet award. He has served on program committees for major conferences including COLT, ICML, and ALT, and actively organizes workshops on cutting-edge topics in machine learning theory. His research group at CWI hosts regular reading groups and seminar series, fostering a vibrant theoretical machine learning community in the Netherlands.

H. Dharma Kwonمشاهده پروفایل

دانشیار

• Game Theory
• Strategic Decision Making under Uncertainty
• Stochastic Dynamic Games
• +۵ مورد دیگر

H. Dharma Kwon is an Associate Professor of Business Administration and Robert and Karen May Faculty Fellow at the Gies College of Business, University of Illinois at Urbana-Champaign. He holds a Ph.D. in Management and Operations Research from UCLA Anderson School of Management (2008) and a B.S. in Physics from KAIST (1991). His research focuses on strategic decision making under uncertainty, stochastic dynamic games, and technology management. He explores topics such as free-rider problems, Bayesian sequential decisions, and real options, with applications in supply chain management, project contracts, and employee retention strategies. His work bridges theoretical rigor and practical business challenges, addressing issues like optimal pricing strategies, investment decisions under spillovers, and cooperative game theory. He has published extensively in journals like Operations Research , Mathematics of Operations Research , and Management Science . His research also extends to early-career physics, with studies on superconductors and quantum phase transitions. Awarded the Robert and Karen May Faculty Fellowship (2018–present), Kwon is recognized for his teaching excellence, receiving the Excellent Teacher award multiple times (2014–2018, 2019–2020, 2023–2023). He serves as an Associate Editor for Management Science and Decision Analysis . His courses include Operations Management (BADM 275) and Decision Analytics (BADM 573), emphasizing data-driven decision frameworks and probabilistic methods.

Erik Baurdouxمشاهده پروفایل

دانشیار

• Lévy Processes
• Optimal Stopping Problems
• Financial Mathematics
• +۳ مورد دیگر

Erik Baurdoux is an Associate Professor in the Department of Statistics at the London School of Economics (LSE). He holds a PhD from Utrecht University (2007), with research visits to Heriot-Watt University and the University of Bath. His work focuses on Lévy processes and their applications in financial and insurance mathematics, particularly optimal stopping problems and stochastic games. He coordinates the BSc Financial Mathematics and Statistics program. Research Interests: Lévy processes, optimal stopping, stochastic games, financial/insurance mathematics. His publications span theoretical advancements in stochastic processes and practical applications in risk management and actuarial science. Teaching includes ST330 (Stochastic and Actuarial Methods in Finance), ST426 (Applied Stochastic Processes), and specialized courses like Lévy Finance and Advanced Probability Theory. He is affiliated with the Probability in Finance and Insurance Group at LSE. Publications emphasize Lévy process analysis, with recent work exploring optimal prediction, drawdowns, and ruin theory. His research often bridges theoretical probability with real-world financial and insurance challenges.

• Stochastic Analysis
• Rough Path Theory
• Mathematical Finance
• +۵ مورد دیگر

Paul GASSIAT is a Lecturer at CEREMADE (Paris Dauphine University-PSL) and DMA (École Normale Supérieure, Paris). His research focuses on stochastic analysis, particularly rough path theory, stochastic PDEs, and applications to financial mathematics. 2011 PhD in Mathematics, supervised by Huyên Pham 2019 Habilitation (Authorization to supervise research) Research interests include: Pathwise stochastic analysis and regularization by noise Stochastic Hamilton-Jacobi equations Rough volatility modeling Applications to financial mathematics and machine learning optimization Scientific roles: JUNIOR MEMBER OF THE UNIVERSITY INSTITUTE OF FRANCE (2024-2029) Co-head of the MASEF Master program (2023/2024) Member of the editorial board of EJP/ECP (2020-) Member of the RT Matrisk office (2024-)

Yaakov Malinovskyمشاهده پروفایل

استاد

• Decision theory
• Stochastic ordering
• Sequential selection
• +۶ مورد دیگر

Yaakov Malinovsky is a Professor in the Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC). His research focuses on decision theory, stochastic ordering, sequential selection methods, group testing, and nonparametric methods. He has held editorial roles at journals including Enumerative Combinatorics and Applications , Methodology and Computing in Applied Probability , and The American Statistician . His work bridges theoretical probability and applied statistics, with contributions to group testing optimization, sequential analysis, and combinatorial probability. Malinovsky earned his Ph.D. in Statistics from The Hebrew University of Jerusalem in 2009. He has secured research funding from the United States-Israel Binational Science Foundation for projects on minimax online learning policies in stochastic sequential selection. His teaching portfolio includes courses such as Probability Theory, Mathematical Statistics, and specialized topics in stochastic processes and nonparametric methods. His recent research explores round-robin tournament models, prime number distribution via dice rolls, and optimal stopping rules. He has published extensively in top-tier journals like Statistica Sinica , Biometrics , and Sequential Analysis , demonstrating expertise in statistical inference and combinatorial problems. His work often addresses practical applications in epidemiology and algorithm design while advancing foundational probability theory.

Shadi Mohamedمشاهده پروفایل

دانشیار

• Computational Mechanics
• Finite Element Analysis
• Acoustic Wave Modeling
• +۴ مورد دیگر

Shadi Mohamed is an Associate Professor at Heriot-Watt University's School of Energy, Geoscience, Infrastructure and Society, specifically within the Institute for Infrastructure & Environment. His research focuses on computational mechanics with applications spanning acoustic wave modeling, traffic flow simulation, and structural dynamics. He maintains an active research profile with over 100 publications and currently accepts PhD students for projects in computational mechanics, traffic modeling, and acoustic waves. His research interests center on advanced numerical methods for engineering problems, particularly finite element analysis for transient diffusion, wave propagation, and structural dynamics. Key focus areas include enriched finite element methods, partition of unity techniques, and machine learning integration for structural health monitoring and inverse problems. His work demonstrates strong alignment with UN Sustainable Development Goals through sustainable infrastructure development and environmental protection. Analysis of his recent publications reveals a clear trajectory toward hybrid computational approaches combining traditional numerical methods with machine learning, particularly for structural dynamics, fatigue analysis, and wave propagation problems. His work increasingly integrates convolutional neural networks for vibration analysis and employs isogeometric analysis for thermal and diffusion problems in composite materials. Best Post-graduate Research (2008) Japan Society for the Promotion of Science Invitational Fellowship (2019) Dr. Mohamed actively supervises PhD research and collaborates internationally, with recent work spanning vibration-induced fatigue assessment, dynamic load identification, and thermal analysis of composite materials. His research is supported by prestigious fellowships and demonstrates strong industry relevance, particularly in structural integrity assessment and sustainable infrastructure development. He is affiliated with the Institute for Infrastructure & Environment, which focuses on sustainable engineering solutions for global challenges.

Churlzu Limمشاهده پروفایل

دانشیار

• Operations Research
• Mathematical Optimization
• Nonlinear Programming
• +۱۱ مورد دیگر

Dr. Churlzu Lim serves as Associate Professor, Associate Chair and Curriculum Director in the Industrial and Systems Engineering Department at the University of North Carolina at Charlotte. He also functions as the Undergraduate Program Director and teaches across both graduate and undergraduate engineering programs. His academic credentials include: Ph.D. in Industrial and Systems Engineering from Virginia Polytechnic Institute and State University M.S. in Management Engineering from Korea Advanced Institute of Science and Technology B.S. in Management Science from Korea Advanced Institute of Science and Technology Dr. Lim's research centers on Operations Research and Mathematical Optimization , with specialized expertise in nonlinear programming, global optimization, and network interdiction problems. His theoretical work addresses nondifferentiable optimization for Lagrangian duals of large-scale mixed integer programs and network games using multilevel programming. Practical applications of his research span supply chain analysis, project risk management, and production planning systems including the flexible requirements profile (FRP) methodology. Recent work explores new service development in autonomous EV charging systems within machine-to-machine environments. His scholarly contributions have been recognized with significant awards: IIE Transactions Best Paper Award (2008) IIE Pritsker Doctoral Dissertation Award, 2nd Place (2005) Grado Fellowship at Virginia Tech (2001-2004) INFORMS Doctoral Colloquium Participant (2003) Dr. Lim teaches graduate courses including Engineering Systems Optimization, Integer Programming, and Processing Systems Simulation, along with undergraduate courses in deterministic and stochastic systems analysis. His instructional approach integrates theoretical frameworks with real-world engineering applications. As Associate Chair and Curriculum Director, he plays a key role in academic program development and educational leadership within the department.

Gechun Liangمشاهده پروفایل

دانشیار

• Mathematical Finance
• Stochastic Control
• Backward Stochastic Differential Equations
• +۸ مورد دیگر

Gechun Liang is a Reader in the Department of Statistics at the University of Warwick, a position equivalent to Associate Professor. He has previously held academic roles as Associate Professor at the University of Warwick, Lecturer at King’s College London, and Postdoctoral Research Fellow at the Oxford-Man Institute of Quantitative Finance. He earned his D.Phil. in Mathematics from Oxford University in 2011. His research focuses on mathematical finance and stochastic control , with particular emphasis on: Stochastic control and backward stochastic differential equations (BSDEs) Optimal stopping and free boundary problems Viscosity solutions and numerical methods Optimal investment and forward performance processes Credit and funding liquidity risks His recent publications span top journals in applied mathematics and financial engineering, demonstrating a strong trend in robust mathematical modeling under uncertainty, ergodic control, and forward performance criteria. The research integrates deep analytical techniques with financial applications, particularly in risk management and dynamic portfolio optimization. He has been recognized with prestigious fellowships: FRIAS Senior Fellow, Freiburg Institute for Advanced Studies (2018–2019) Marie Curie Fellow, University of Freiburg (2018–2019) Gechun Liang actively collaborates with leading researchers in mathematical finance and has contributed to both theoretical advances and practical financial modeling. His work includes studies on convertible bonds, liquidity constraints, and robust central limit theorems under sublinear expectations. While no formal advising or grant information is listed, his extensive publication record and international collaborations suggest a significant research leadership role. He is based in the Department of Statistics at the University of Warwick, contributing to a vibrant academic environment in quantitative finance and stochastic analysis.