Jin Ma is a Professor in the Department of Mathematics at the University of Southern California (USC), where he has served since 2007. He previously held professorships at Purdue University (1994–2008). His research focuses on stochastic analysis, stochastic differential equations, mathematical finance, and control theory. He directs USC's Mathematical Finance Program and serves on editorial boards for journals like Probability, Uncertainty and Quantitative Risk and SIAM Journal on Control and Optimization . Ma received his Ph.D. in Mathematics from the University of Minnesota (1992) and M.S./B.S. in Applied Mathematics from Fudan University (1985/1982). His work bridges theoretical stochastic analysis and applied domains like finance and insurance, with notable contributions to forward-backward SDEs and mean-field games. Research Highlights: Developed frameworks for stochastic control and backward SDEs in financial and insurance contexts. Advanced mean-field game models for limit order book dynamics and equilibrium analysis. Explored set-valued stochastic differential equations and their applications in risk management. Grants & Advising: Advised numerous graduate students in stochastic processes and mathematical finance. Research supported by NSF grants and industry collaborations.
Peng Shige is a Professor of 1st class at the School of Mathematics, Shandong University, China. He has held the Distinguished Professor title under the Ministry of Education (Cheung Kong Scholarship) since 1999. His academic journey includes degrees from Shandong University (Physics diploma, 1971-1974), Paris-IX (1985), and Aix-Marseille University (PhD 1986, Habilitation 1992). Research focuses on nonlinear expectations, stochastic calculus, partial differential equations, and financial mathematics. Key contributions include foundational work on backward stochastic differential equations (BSDEs), the g-expectation framework, and the G-expectation theory extending probability axioms to nonlinear settings. These innovations have advanced stochastic control, financial risk modeling, and differential games. Honors include the 2020 Future Science Award, 2011 Princeton Global Scholar, and 2005 Chinese Academy of Sciences Academician status. He delivered a plenary lecture at the 2010 International Congress of Mathematicians. Peng's work integrates theoretical breakthroughs with applied domains like financial engineering. His research has been widely cited (~8k citations) and shaped modern stochastic analysis methodologies.
Ali Lazrak is an Associate Professor at the Sauder School of Business , University of British Columbia , specializing in Finance . He holds the Peter Lusztig Professorship in Finance and teaches courses such as International Financial Markets and Institutions and Theory of Finance (2024-2025). His research bridges Political Economy , Asset Pricing , and Behavioral Finance , with a focus on ESG concerns , Voting Theory , and Time Inconsistency . Education: ENSAE (B.Sc.), Sorbonne (M.Sc.), Toulouse (Ph.D.) Contact: Henry Angus Building (HA 872), +1 604.822.9481, ali.lazrak@sauder.ubc.ca His work explores group decision-making in corporate investment, green finance (e.g., the green premium in ESG markets), and time-inconsistent preferences in continuous games. Recent publications highlight how responsible consumption and demand elasticity shape asset prices, and how institutional divestiture impacts harmful asset stranding through informational and economic channels. Scientific accolades include the Jacob Gold & Associates Best Paper Prize (2019), Best Paper Awards at HEC-McGill, UBC, Luxembourg, and Stanford conferences, and the Peter Lusztig Professorship . His methodological expertise spans stochastic control , recursive utility , and dynamic equilibrium analysis .
Professor Susan Thorp is a Finance academic at the University of Sydney Business School . With a PhD in Economics from UNSW and prior roles at University of Technology Sydney and the Reserve Bank of Australia, she focuses on household finance , retirement planning , and financial market behavior . BEc (Hons) - University of Sydney Dip. Ed. - University of New England PhD - University of New South Wales Her research interests include: Life-cycle financial decision-making Behavioral influences on savings and investments Superannuation policy and market integration Commodity market dynamics Economic impacts of financial literacy Crises-driven market contagion Recent publications analyze retirement decumulation , financial trust , and commodity-equity market correlations . She leads cross-disciplinary teams applying dynamic programming , econometric modeling , and experimental design to financial challenges. Her grants include ARC Linkage Projects and ASIC commissions for improving financial communication and regulatory frameworks . Media outlets frequently cite her expertise on superannuation policy , market volatility , and retirement savings behavior .
Tomasz Strzalecki is a Professor in the Department of Economics at Harvard University. His research centers on decision theory, with a focus on ambiguity aversion , temporal preferences , stochastic choice , and bounded rationality . He earned his PhD in Economics from Northwestern University in 2008. Education: PhD in Economics (2008), Northwestern University His scholarly work spans theoretical and applied economics, including key contributions to random utility models , dynamic decision-making , and neuroeconomic modeling . Recent publications, such as Stochastic Choice Theory (2025) and Variational Bayes and non-Bayesian Updating (2024), reflect his ongoing exploration of Bayesian inference and behavioral deviations. Earlier work in Econometrica and American Economic Review established foundational models for choice aversion , time inconsistency , and ambiguity evaluation . Tomasz’s research has been published in top journals like Econometrica , American Economic Review , and Proceedings of the National Academy of Sciences , covering themes such as probabilistic sophistication , decision timing , and collective action in development economics. His co-authors include prominent economists like Drew Fudenberg, Mira Frick, and Larry Epstein.
Anders Karlström is a Professor at KTH Royal Institute of Technology, specializing in Transport Modelling and Economics. His research focuses on sustainable transportation systems, emissions reduction, and energy efficiency. Key interests include activity-based modelling, dynamic discrete choice frameworks, and policy analysis for urban mobility. He has contributed to studies on travel behavior, infrastructure planning, and environmental impacts of transport systems across multiple international cities. His work integrates advanced methodologies such as recursive logit models, spatial regression, and machine learning for predictive analytics. Notable research areas involve evaluating weather variability effects on travel patterns, optimizing traffic state estimation with sensor data, and developing scenario-based models for future employment growth. Karlström collaborates with industries to enhance the competitiveness of sustainable transport solutions globally.
John C. Heaton is the Myron S. Scholes Distinguished Service Professor of Finance at the University of Chicago Booth School of Business and Director of the Anthony Pritzker Family Foundation - Family Office Initiative. He joined Chicago Booth in 2000 after serving as the Nathan S. and Mary P. Sharp Distinguished Professor of Finance at Northwestern University's Kellogg School of Management, with additional positions at MIT's Sloan School of Management and the Hoover Institution. Heaton maintains an active research affiliation as a research associate of the National Bureau of Economic Research. His educational background includes: Bachelor's degree in commerce from the University of Windsor (1982) Master's degree in economics from the University of Western Ontario (1984) PhD in economics from the University of Chicago (1989) Heaton's research program centers on asset pricing, portfolio allocation, and time-series econometrics , with particular emphasis on understanding how macroeconomic fluctuations affect financial markets. His work investigates the long-run risk-return tradeoff in asset valuation and how background risks from labor and entrepreneurial income influence investment decisions. He approaches these questions through rigorous econometric analysis combined with economic theory, seeking to bridge the gap between academic research and practical investment challenges. Analysis of Heaton's publications reveals a consistent focus on market frictions and their implications for asset pricing and portfolio choice. His research demonstrates how transaction costs, borrowing constraints, and incomplete markets affect investor behavior and market outcomes. A distinctive contribution is his work on long-run risk components that influence asset valuations despite being realized far into the future. Heaton's scholarly achievements have been recognized through: Alfred P. Sloan Research Fellowship (1993-1995) National Science Foundation Fellowship (1993-1998) Ongoing research affiliation with the National Bureau of Economic Research As an educator, Heaton teaches advanced courses in asset pricing, financial instruments, fixed income, and investments, with a focus on connecting theoretical frameworks to real-world investment challenges. His directorship of the Family Office Initiative reflects his expertise in wealth management across generations. His research continues to influence both academic discourse and practical approaches to understanding risk in financial markets, with current teaching commitments extending through 2026.
Pablo Beker is an Associate Professor of Economics at the University of Warwick's Department of Economics. He holds a Ph.D. from Cornell University (2002) and a B.A. from the Universidad de Buenos Aires (1994). His research focuses on dynamic economic theory, including rationality foundations, asset price dynamics, and industry evolution. He has held academic roles since 2001, including prior positions at the Universidad de Alicante and visiting roles at Cornell University. Research interests span macroeconomic dynamics, financial market efficiency, and heterogeneous beliefs. Key contributions include studies on bidding market stability with financial constraints, consumption dynamics under market incompleteness, and asset trading efficiency. His work has been published in leading journals like the Journal of Economic Theory . Awarded the European Economic Association's Outstanding Young Economist distinction and multiple teaching awards, Beker has secured research grants totaling over £50,000. He advises doctoral students and supervises research projects on wealth inequality, bargaining power evolution, and monopolistic pricing dynamics. His service roles include Ph.D./MRes Director and leadership in academic recruitment committees.
Prof. Antoine Bommier is a Full Professor at ETH Zurich's Department of Management, Technology, and Economics, serving as Deputy Head of the department. He holds a Chair in Integrative Risk Management and Economics and is a member of the ETH Risk Center's Steering Committee. His academic journey includes a PhD in Mathematics from École Polytechnique (1993) and a Habilitation à Diriger des Recherches in Economics from the University of Toulouse (2005). Prior roles include positions at CNRS (France), University Paris-Nanterre, and Berkeley. His research focuses on risk management, intergenerational equity, uncertainty modeling, and public policy. Key areas include climate change mitigation, annuity markets, and the valuation of catastrophic risks. Bommier has been recognized with the Robert C. Witt Award (2013) and a best-paper award from the Journal of Risk and Insurance (2012). Recent work explores ambiguity aversion's impact on savings and insurance, dynamic preferences in risky environments, and equity considerations in exhaustible resource management. He also investigates mortality-linked retirement policies and the societal value of risk reduction. Editorial Roles: Associate Editor of Decisions in Economics and Finance Professional Activities: Visiting appointments at Paris School of Economics and University Paris-Nanterre Key Themes: Climate policy, actuarial fairness, recursive utility, and sustainable development
Siamak Ravanbakhsh is an Associate Professor at McGill University's School of Computer Science and a Canada CIFAR AI Chair at Mila. His research focuses on machine learning, particularly representation learning with an emphasis on geometry, symmetry, and probabilistic inference. He has held academic positions at the University of British Columbia and was a postdoctoral fellow at Carnegie Mellon University. Education: B.Sc. in Computer Science, Sharif University of Technology M.Sc. and Ph.D. in Computer Science, University of Alberta (supervised by Russ Greiner) Postdoctoral Fellowship at Carnegie Mellon University (with Barnabás Póczos and Jeff Schneider) His research interests span geometric deep learning, equivariant networks, reinforcement learning, and AI for scientific applications. Notable contributions include work on symmetry-aware models, diffusion processes, and equivariant representation learning. Publications highlight advancements in causal abstraction, diffusion-based anomaly detection, and equivariant architectures for crystals and hierarchical structures. His work often bridges theory and application, emphasizing symmetry principles. Advising & Grants: Supervised over 20 graduate students and postdocs, including recent PhD graduates Daniel Levy and Mehran Shakerinava Active in mentoring M.Sc. and internship students He contributes to academic leadership roles at Mila and McGill, fostering interdisciplinary collaborations in AI research.
Anthony W. Lynch is a Professor of Finance at the Leonard N. Stern School of Business, New York University, where he has been a faculty member since 1994. He is also a Research Associate at the National Bureau of Economic Research since 2002 and has held visiting positions at Columbia University and the Wharton School of the University of Pennsylvania. Education: PhD in Finance and Economics, University of Chicago, 1994 Bachelor of Commerce (Honours), University of Queensland, 1989 Bachelor of Laws (Honours), University of Queensland, 1989 Master of Financial Management, University of Queensland, 1988 Bachelor of Commerce, University of Queensland, 1986 Professor Lynch's research centers on asset pricing , portfolio choice , and mutual funds , with a strong emphasis on modeling investor behavior under uncertainty, transaction costs, and habit formation. His work integrates macroeconomic factors with financial decision-making, particularly in life-cycle investing and retirement planning. He has made significant contributions to understanding how frictions such as taxes, liquidity, and borrowing constraints impact optimal investment strategies. His recent publications demonstrate a consistent focus on dynamic portfolio optimization, stochastic volatility, and the implications of behavioral and structural frictions in financial markets. Themes across his work include time-consistency in decision-making, risk premia estimation, and the interaction between human capital and financial wealth. Scientific Awards and Honors: Glucksman Prize (twice) for best finance research paper by an NYU professor Research Associate, National Bureau of Economic Research (since 2002) Associate Editor, Review of Finance Session Chair, American Finance Association (AFA) and Western Finance Association (WFA) Meetings Professor Lynch advises doctoral students and contributes to academic leadership through editorial and conference roles. He has not received mention of external research grants in the provided text, but his NBER affiliation suggests involvement in collaborative, funded research initiatives. He teaches foundational courses including Foundations of Finance (MBA), Finance Theory I , and Seminar in Asset Pricing Theory (PhD level), shaping the next generation of finance scholars and practitioners. He is affiliated with the Department of Finance at NYU Stern and conducts research that bridges theoretical models with empirical validation, often using advanced econometric and computational methods. His academic network includes leading institutions such as Chicago, Columbia, and Wharton, reflecting his prominence in the finance community.
Olle Häggström is a Professor of Mathematical Statistics at Chalmers University of Technology, specifically in the Department of Applied Mathematics and Statistics. His academic career spans several decades with a significant shift in research focus over time. Häggström's research interests have evolved from traditional probability theory to encompass broader future-oriented topics. Initially focused on mathematical statistics and probability theory, including percolation theory and stochastic processes, he has increasingly turned his attention to futurology, existential risk, and AI safety in recent years. His work demonstrates a unique interdisciplinary approach, bridging rigorous mathematical analysis with philosophical considerations about humanity's technological trajectory. The trends in Häggström's publications reveal a clear evolution from purely mathematical research toward interdisciplinary studies examining the societal implications of emerging technologies. His recent work focuses heavily on AI safety, existential risk assessment, and long-term futures thinking, while still maintaining connections to his mathematical foundations. This shift is evident in publications ranging from technical mathematical papers to broader philosophical discussions about technology's impact on civilization. Häggström has received research funding from notable sources including the FTX Foundation Future Fund for his project "Topics in the theory of xrisk and longtermism" (2022-2025), indicating recognition of the importance of his work in the existential risk community. His book "Here Be Dragons: Science, Technology and the Future of Humanity" (2016) represents a significant synthesis of his thinking on these topics. While specific details about his advising activities are not provided in the source material, his research projects suggest engagement with interdisciplinary teams working at the intersection of mathematics, computer science, and future studies. His work appears to influence both academic and policy discussions regarding technological risk and long-term planning.
Anis Matoussi is a Professor of Applied Mathematics at Le Mans University and serves as the Director of the Institut du Risque et de l'Assurance du Mans. He coordinates the master's program in Actuarial Science and leads multiple research initiatives, including ANR DREAMeS (2021-2025) and ITCA (Groupama, Fondation du Risque). Role: Professor, Applied Mathematics Institution: Le Mans University Research Leadership: Director of Institut du Risque et de l'Assurance, Head of Master Actuarial Science His research focuses on stochastic control, backward stochastic differential equations (BSDEs), and their applications in finance, insurance, and energy systems. He has developed numerical methods for second-order BSDEs and studied stochastic nonlinear PDEs, maximum principles for SPDEs, and extended mean field control models. Recent projects include the application of deep learning to forward utilities via ergodic BSDEs and multivariate risk measures. Matoussi has supervised numerous PhD students, including current advisees Zakaria Bensa (industrial thesis with Natixis) and Lucas Da Silva (co-supervised with Caroline Hillairet). Former students like Achraf Tamtalini (Bank of America) and Jing Zhang (Fudan University) hold prominent positions globally. His work includes collaborations on smart grids, control of electrical systems, and robust utility maximization under uncertainty. Publications span journals in applied mathematics, optimization, probability, and financial mathematics, with recent emphasis on numerical schemes and probabilistic representations.
Summary Fabio Angelo Maccheroni is a Full Professor at Bocconi University's Department of Decision Sciences, affiliated with the IGIER research center. He holds a Laurea in Mathematics from the University of Milan (1995) and a PhD in Applied Mathematics from a joint program of several Italian universities (1999). His research focuses on decision theory, game theory, mathematical economics, and ambiguity aversion, with contributions to risk analysis and behavioral economics. He has been recognized with awards including the Economic Theory Fellow (2019) and the Carlo Alberto Medal (2010). Education: University of Milan (Laurea), Joint PhD Program (1999) Professional Roles: Full Professor since 2005, IGIER Fellow since 2008 Research interests include axiomatic foundations of decision making, ambiguity preferences, and applications to finance and insurance. His work bridges economics, mathematics, and neuroscience, particularly through diffusion models of decision processes. Over 50 journal articles span top venues like Econometrica , Journal of Economic Theory , and Management Science . Awards Economic Theory Fellow (2019) Cours Bachelier (2012) Carlo Alberto Medal (2010)
Ian Dew-Becker serves as an Adjunct Associate Professor of Finance at the University of Chicago Booth School of Business and as a Senior Economist at the Federal Reserve Bank of Chicago. His academic work centers on theoretical and empirical asset pricing and macroeconomics, with particular emphasis on uncertainty, skewness, and tail risk in economic systems. He received his PhD in economics from Harvard University and has held prior positions at Northwestern University, Duke University, and the Federal Reserve Bank of San Francisco. His educational background includes: PhD in Economics, Harvard University Dew-Becker's research explores how agents form beliefs about economic fundamentals and how these beliefs translate into asset prices and macroeconomic outcomes. He investigates the dynamics of uncertainty and skewness across business cycles, develops novel measures using options data, and examines how production networks propagate economic shocks. His work demonstrates that firm-level uncertainty does not significantly forecast aggregate output, challenging existing models, while revealing how interconnectedness can reduce sensitivity to small shocks while amplifying vulnerability to large ones. Recent studies focus on real-time skewness measurement and tail risk transmission through input-output structures. Analysis of his publication record shows a consistent focus on risk measurement and pricing across financial and macroeconomic domains. Collaborating frequently with Stefano Giglio, he has pioneered methodologies using options data to construct cross-sectional uncertainty indices and measure conditional skewness. His research demonstrates that while exchange-traded options earn negative alphas implying rising risk aversion during downturns, synthetic options show constant risk aversion, suggesting intermediary frictions drive pricing anomalies. Key contributions include establishing empirical regularities about macro skewness and demonstrating how production networks generate left-skewed economic activity. No scientific awards were mentioned in the available information. Information regarding graduate student advising, research grants, or specific funding sources was not provided in the source materials. Dew-Becker teaches the Investments course at Chicago Booth during Autumn quarters but no details about mentored students or grant-supported projects are available. Dr. Dew-Becker actively collaborates with researchers across institutions including Stefano Giglio (Yale University), Andrea Vedolin (London School of Economics), and Bryan Kelly (Yale University), forming a network focused on financial economics and macro-finance linkages. His work bridges theoretical modeling with empirical analysis of market data, particularly options markets, to address fundamental questions about risk and uncertainty in economic systems.
