Martin Herdegen is a Reader in Financial Mathematics at the Department of Statistics, University of Warwick. He previously served as a postdoc at ETH Zürich under Johannes Muhle-Karbe and holds a PhD in Mathematics from ETH Zürich (2014) under Martin Schweizer. His research focuses on equilibrium theory, utility maximization, stochastic processes, and risk measures, with applications to financial bubbles and market microstructure. Herdegen’s academic career includes supervising multiple PhD students (e.g., Florian Gutekunst, Andreea Popescu) and postdocs (e.g., Nazem Khan). His research group explores topics like ρ-arbitrage, recursive utility, and liquidity provision under adverse conditions. He has contributed to foundational work on strict local martingales and their implications for financial markets. Publications span leading journals such as Finance and Stochastics , Mathematical Finance , and Annals of Applied Probability , addressing equilibrium models with transaction costs, optimal investment strategies, and risk measurement techniques. His work frequently integrates stochastic analysis and control theory to solve practical finance problems. Herdegen’s research also intersects with reinforcement learning applications in trading, as seen in the Mbt-gym framework for limit order book simulations. His contributions emphasize rigorous mathematical foundations while addressing real-world market frictions and liquidity dynamics.
Nabil Al-Najjar is the John L. and Helen Kellogg Professor of Managerial Economics & Decision Sciences at Northwestern University's Kellogg School of Management. He holds a PhD in Economics from the University of Minnesota (1989), preceded by an MA from the University of Ottawa (1982) and a BA from Al-Mustansiriah University (1979). Prior to joining Kellogg in 1995, he taught at the University of Quebec in Montreal. His research focuses on decision theory, game theory, and learning-based models in markets and contracts. Notable contributions include frameworks for uncertainty modeling, aggregate risk analysis, and recursive utility theory. He has published in top journals such as the Journal of Economic Theory, Econometrica, and the American Economic Review. Award-winning educator, Al-Najjar twice received the Sidney J. Levy Teaching Award (1996-97, 2006-07) for excellence in microeconomics and competitive strategy instruction. He also holds editorial roles at the International Journal of Game Theory and Journal of Mathematical Economics. His work bridges theoretical economics with practical applications, addressing issues like market fundamentals, contractual complexity, and policy design under uncertainty. Over 49 peer-reviewed publications and 12 case studies reflect his interdisciplinary impact across economic theory and applied fields.
Andrzej Nowak is a Professor at the Institute of Mathematics, University of Zielona Gora, specializing in game theory, mathematical economics, and applied mathematics with significant applications in economics and finance. His academic profile includes: Research on Nash equilibria in non-zero-sum stochastic games with constraints on player strategies Work on Recursive Utilities in Dynamic Economic Models and General Equilibrium Theory Investigations of Risk Measures in Dynamic Programming and Markovian Decision Processes Analysis of multivariate linear models and Inclusions and multivalued stochastic equations Studies of Preference models using graded and interval relations for decision support systems Professor Nowak teaches fundamental courses in game theory, mathematical economics, and mathematical foundations of economics in finance (including portfolio analysis, capital market lines, and time series). He also covers probability theory and stochastic processes with applications to economics and finance, particularly Markov chain theory and discrete-time martingales. His broader research encompasses: Approximation theory using Fourier series and summability methods Combinatorial geometry including partitions of n-dimensional space Mathematical means and their invariance properties Applications of computer science to secure data transmission and privacy standards
Christine Rizkallah is a Senior Lecturer in the School of Computing and Information Systems at the University of Melbourne, Australia. She joined the university in December 2021 after serving as a Lecturer at the University of New South Wales (UNSW) from April 2018 to December 2021. Her research focuses on interactive theorem proving, formal verification, programming languages, and systems, with an emphasis on building practical tools for high-assurance software development. She leads a research group working on the Cogent and Dargent languages, aiming to reduce the burden of formal verification in systems programming. Education: PhD in Computer Science, Universität des Saarlandes and Max-Planck-Institut für Informatik, Germany (2015), thesis: Verification of Program Computations , supervised by Prof. Dr. Kurt Mehlhorn. MSc in Computer Science, Universität des Saarlandes, Germany (2009), thesis: Proof Representations for Higher Order Logic , supervised by Prof. Dr. Gert Smolka and Dr. Chad E. Brown. BSc in Computer Science, German University in Cairo, Egypt (2007), thesis: X2-Planner: A Hierarchical Task Network Planner for Real Time Gaming Applications , supervised by Prof. Dr. Slim Abdennadher and Dr. Thorsten Maier. Her research interests lie at the intersection of programming languages and formal methods. She develops domain-specific languages with strong type systems and verified compilers to enable trustworthy software systems. Her work spans algorithms, logic, security, and social choice theory, reflecting a strong interdisciplinary approach. She has published extensively in top venues such as POPL, ICFP, ASPLOS, JAR, and PACMPL, with a focus on certifying compilation, refinement verification, and mechanized reasoning. Her recent publications reveal a consistent focus on formal verification of systems software, particularly through the Cogent language and its ecosystem. Key themes include verified data layout refinement (Dargent), property-based testing, termination analysis, cost modeling, and integration with foreign functions. Her work combines theoretical rigor with practical implementation, often involving mechanized proofs in Isabelle/HOL and Coq. Scientific Awards and Recognition: Distinguished Artefact Award at SLE'22 (awarded to Zilin Chen for work under her supervision). First Prize, SPLASH'22 Student Research Competition (undergraduate), won by Raphael Douglas Giles. Second Prize, ACM-wide Student Research Competition (undergraduate, 2023), won by Raphael Douglas Giles. She has supervised numerous PhD, Masters, and Honours students, many of whom have continued in academia or industry research roles. She has received research funding through institutional support and collaborative grants, though specific grants are not detailed in the provided text. She is actively involved in the programming languages community, serving on program committees for POPL, ICFP, CPP, PLDI, and others, and holding leadership roles such as Program Chair for FUNARCH'25 and Diversity and Inclusion Co-Chair for PLDI'25. She teaches core courses including Declarative Programming and Models of Computation at the University of Melbourne. She leads a vibrant research team and collaborates widely across institutions including UNSW, University of Pennsylvania, and international partners. Her lab focuses on building verified systems using functional programming and formal methods, with strong ties to the DeepSpec project and the Isabelle/HOL community.
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.
Angelo Melino is a Professor of Economics at the University of Toronto, holding a Ph.D. from Harvard University (1983) and a B.A. from the University of Toronto (1977). He has been affiliated with the University of Toronto since 1981, becoming a full professor in 1991. His research focuses on Econometrics , Macroeconomics , and Financial Economics , with notable contributions to asset pricing, monetary policy, and labor economics. He has held leadership roles, including Associate Chair of the Department of Economics and Director of the MFE program. Research Contributions: Melino’s work spans theoretical and empirical analyses of economic policy, including inflation targeting, business cycle costs, and electricity market dynamics. His methodologies in duration analysis and term structure modeling are widely cited. Notable publications include influential papers on foreign currency options pricing and the equity premium puzzle. Awards: He is a Fellow of the C.D. Howe Institute, a Senior Fellow at the Rimini Centre for Economic Analysis, and recipient of the University of St. Michael’s College Medal in Economics (1977). Professional Activities: Melino has served as a Visiting Professor at Harvard University and the University of California, San Diego. He contributed to policy advisory roles, including Special Adviser to the Bank of Canada, and authored widely adopted textbooks on macroeconomics tailored to Canadian contexts.
Dorsa Amir is an Assistant Professor of Psychology & Neuroscience and Evolutionary Anthropology at Duke University. She directs the Mind & Culture Lab, focusing on interdisciplinary research that bridges psychology, anthropology, and behavioral economics. Education: PhD from Yale University (2018), BS from UCLA (2012) Departments: Psychology & Neuroscience (2024–present), Evolutionary Anthropology (2025–present) Her research investigates how cultural environments shape cognitive development, behavioral variation, and decision-making. Key themes include cross-cultural childhood studies, cultural evolution, and the limitations of Western-centric methodologies in developmental research. Recent publications analyze topics such as WEIRD visual perception, scarcity effects on child generosity, and cross-cultural acoustic communication patterns. She emphasizes fieldwork in diverse societies (e.g., Shuar, Hadza) and experimental validation of cognitive models. At Duke, she teaches courses like PSY 203: Practicum and participates in faculty development programs. Her outreach work includes public science communication in outlets like TED , Science , and The New York Times .
Ozgur Evren serves as an Associate Professor with tenure at the New Economic School (NES) in Moscow, a position he has held permanently since 2016 after joining the institution in 2011. He teaches core graduate courses including Microeconomics 1 and 3, Mathematics for Economists 1 and 2, and Decision Theory within the Master of Applied Economics program, demonstrating deep integration into NES's academic framework. He earned his PhD in Economics from New York University in 2011 and Master of Economics from Bilkent University (Turkey) in 2004, establishing a foundation for his theoretical research career. His scholarly work centers on Decision Theory and Economic Theory, with significant contributions to understanding behavioral anomalies in individual choice and social preference aggregation. Research specifically examines how ambiguity affects risk preferences, flexibility in decision outcomes, and applications in political economy and charitable giving behavior through rigorous mathematical modeling. Analysis of his 10 publications (2007-2021) reveals a cohesive trajectory in mathematical economics, predominantly published in elite journals like Journal of Economic Theory and Games and Economic Behavior. The work consistently develops formal frameworks for preference representation under uncertainty, with increasing focus on non-expected utility models and social choice implications in later publications. No scientific awards are documented in available sources, and details regarding student supervision, grant funding, or research teams remain absent from current institutional documentation.
Lefort Jean-Philippe serves as a Lecturer at Paris Dauphine University, where he is affiliated with the LEDa research center (Laboratoire d'Economie de Dauphine). His academic work centers on theoretical economics with a specialized focus on decision-making under uncertainty and ambiguity, contributing significantly to the advancement of non-expected utility frameworks. His research spans Decision Theory , Ambiguity Modeling , and Game Theory , particularly examining neo-additive capacities, dynamic rationality, and probabilistic information processing. Key contributions include the development of generalized pricing rules under ambiguity, dynamic extensions of the Ellsberg paradox, and foundational work on belief updating mechanisms. His methodological approach integrates rigorous mathematical economics with experimental validation, yielding insights applicable to financial economics and strategic interaction analysis. Analysis of his publication trajectory (2008-2021) reveals consistent innovation in ambiguity modeling, with increasing focus on dynamic applications and financial contexts. His work demonstrates strong continuity in exploring how agents process probabilistic information under uncertainty, bridging theoretical economics with practical market phenomena through sophisticated non-additive probability frameworks. Lefort maintains active research collaboration within the LEDa center, contributing to its mission of advancing economic theory through interdisciplinary approaches that combine mathematical rigor with behavioral insights.
Dr. Anh Le is an Associate Professor of Finance at the Smeal College of Business, The Pennsylvania State University. His expertise lies in fixed income markets and quantitative finance. He holds a PhD in Finance from New York University's Stern School of Business (2008), and dual bachelor's degrees in Commerce with First-Class Honors (University of Queensland, 2001) and Accounting & Finance (Monash University, 2000). His research focuses on term structure models, interest rate volatility, risk premia, and structural credit risk. Notable contributions include analyzing no-arbitrage frameworks, stochastic volatility dynamics, and cross-currency bond yield comovements. His work bridges macro-finance econometrics with asset pricing theory, with applications to derivatives markets and macroeconomic risk factors. Key publications include Management Science and Journal of Financial Economics articles on tractable term structure models, variance risk pricing, and default risk decomposition. His methodologies emphasize analytical tractability and empirical rigor in modeling financial markets. Dr. Le's research has explored linkages between macroeconomic variables and bond yields, the role of inflation in global financial markets, and equilibrium models with recursive preferences. He has also contributed to understanding gold leasing markets and volatility components in Treasury returns.
Ole Wilms holds a dual academic role as an Assistant Professor of Macroeconomics at Universität Hamburg (since 2021) and a part-time Associate Professor of Finance at Tilburg University (since 2021). He earned his Ph.D. in Management and Economics from the University of Zurich (2016), with prior studies including a M.Sc. in Quantitative Finance (Kiel University, 2012) and B.Sc. in Economics (Kiel University, 2010). His research focuses on asset pricing, climate finance, macro-finance, and computational methods, particularly exploring investor heterogeneity and climate risk impacts on financial markets. His recent publications address topics such as pricing kernels, recursive utility models, and the performance of green vs. brown stocks. Wilms has also contributed to econometric methods for analyzing dynamic models with occasional state observations. His work has appeared in journals like the Review of Financial Studies and Journal of Economic Theory . Prior to his academic roles, Wilms worked as a Quantitative Investment Analyst at Sal. Oppenheim Jr. & Cie. AG (2016–2017) and held visiting researcher positions at RWTH Aachen and the University of Zurich. He currently teaches courses in asset pricing and data science methods in finance at Tilburg University.
Paulo M.M. Rodrigues is a Full Professor at Nova School of Business and Economics, Universidade Nova de Lisboa, and a permanent Researcher at Banco de Portugal's Economics and Research Department since September 2008. His work bridges academic research with central banking policy. Educated with a PhD in Econometrics (1998) and MA in Economics and Econometrics (1995) from University of Manchester Received Agregação (2005) in Business Management from Universidade do Algarve Research spans time series econometrics, financial risk modeling, tourism economics, and decision analysis, focusing on: Nonlinear threshold effects in credit risk Structural breaks and unit root testing Banking crisis forecasting models Regional tourism development dynamics Fractional integration in economic time series Publications show consistent contributions to: Central banking and financial stability Econometric methodology Tourism demand analysis Operational research applications Policy impact assessment
Anastasios Karantounias is an Associate Professor of Economics at the School of Economics, University of Surrey. He also holds several prestigious affiliations including being an Academic Visitor at the Bank of England, an Associate of the Centre for Macroeconomics (LSE branch), a Fellow of the Institute for Sustainability at the University of Surrey, and a member of the Macro Finance Society. Dr. Karantounias received his academic training at New York University, earning his PhD in Economics in 2008 and a Master's degree in Economics in 2004. He completed his undergraduate studies at the Athens University of Economics and Business in Athens, Greece, where he earned his Bachelor's degree in Economics in 2001. His major research interests focus on macroeconomics with particular emphasis on optimal fiscal and monetary policy, macro-finance, ambiguity, imperfect information, and optimal carbon taxation. His work bridges theoretical macroeconomic frameworks with practical policy applications, often incorporating behavioral elements and uncertainty into traditional models. He has published extensively in top journals including the Review of Economic Studies, American Economic Journal: Macroeconomics, Journal of Economic Theory, and Theoretical Economics. Dr. Karantounias' recent publications demonstrate a clear trajectory toward increasingly sophisticated modeling of uncertainty in macroeconomic policy. His work on model uncertainty, fiscal policy under ambiguity, and behavioral factors in macroeconomic outcomes represents cutting-edge research at the intersection of macroeconomics and decision theory. His most recent work extends into climate policy, examining optimal carbon taxation in a global economy context. Dr. Karantounias has been actively involved in the academic community through organizing major workshops including the Surrey Workshop on Macroeconomics (May 2022), the Macroeconomics Network in the Southwest Workshop (November 2023), and the Bristol-Surrey Workshop in Macroeconomics (March 2024). He has also organized multiple contributed sessions at the Annual Meetings of the American Economic Association (2013, 2017, 2019, 2025). Prior to joining the University of Surrey, Dr. Karantounias worked as a research economist in the Research Department of the Federal Reserve Bank of Atlanta. He also gained research experience at the Federal Reserve's Board of Governors and the European Central Bank. He has served as a Visiting Scholar at Northwestern University and as a Visiting Professor at LUISS Guido Carli and the Einaudi Institute for Economics and Finance. His previous teaching appointments include Emory University.
Eric T. Swanson is a Professor in the Department of Economics at the University of California, Irvine. He specializes in Monetary Economics, Macroeconomics, and Macro-Finance, with a focus on unconventional monetary policy, central bank communication, and financial markets. His research includes analyzing the effects of Federal Reserve policies, such as forward guidance and asset purchases, on economic outcomes and financial markets. Swanson holds a Ph.D. in Economics from Stanford University (1998), an M.S. in Mathematics from Stanford (1994), and a B.A. in Mathematics from Williams College (1992). He has held positions at the Federal Reserve Bank of San Francisco and the Federal Reserve Board, contributing to policy analysis and FOMC deliberations. His awards include the 2022 Journal of Monetary Economics Best Paper Prize and Excellence in Refereeing Awards from the American Economic Review. He is a co-editor of the Journal of Monetary Economics and has presented at numerous international conferences, including the NBER Macroeconomics Annual and the Society for Nonlinear Dynamics and Econometrics. Swanson’s work integrates theoretical models with empirical analysis, emphasizing high-frequency data to identify monetary policy effects. His research on Fed Chair speeches and FOMC announcements demonstrates their significant impact on market expectations, challenging earlier assumptions about policy communication channels. He advises numerous graduate students, many of whom hold academic and policy positions globally. His contributions span teaching, research, and public service, including roles on the Federal Reserve Bank of San Francisco’s Academic Advisory Panel and the Financial Times/Chicago Booth IGM Economic Outlook Panel.
Juan Pablo Rincón-Zapatero is a Professor of Economics at Universidad Carlos III de Madrid , serving as Director of the Graduate School of Economics and Political Science . His research focuses on mathematical economics, game theory, dynamic programming, and financial mathematics. He holds a prominent role in advancing theoretical frameworks for economic modeling under uncertainty. He teaches Advanced Mathematics for Economics (undergraduate) and Mathematics (graduate) courses. His work bridges pure mathematics with applied economics, particularly in stochastic processes and recursive utility models. His publications address core topics like Bellman equations, stochastic differential games, and value function analysis. Notable contributions include applying Euler-Lagrange methods to economic asset games and proving differentiability in unbounded dynamic models. Though no awards are listed here, his extensive publication record reflects sustained academic impact. He currently oversees the graduate economics program, fostering interdisciplinary research between mathematics and economics.
