Prof. Sergio Ginebri is an Associate Professor at the Department of Jurisprudence, University of Rome Tre. He holds a PhD in Economics from Sapienza University of Rome and has extensive experience in fiscal policy, pension systems, and public finance research. His work focuses on topics like pension sustainability, social inequality, and the political economy of public debt. Education: PhD in Economics, Sapienza University of Rome (1988–1992) MA in Economics, University of Warwick (1987–1988) Laurea in Statistics and Demography, Sapienza University of Rome (1977–1984) Research Interests: Prof. Ginebri specializes in public policy, fiscal sustainability, and the social impacts of pension reforms. His research explores how demographic trends, wealth distribution, and political dynamics shape economic policies. Recent work includes analyses of longevity risks, pension equity, and fiscal policy integration in the EU. Key Projects: Coordinated studies on pension system sustainability (2002–2018) Developed models for forecasting public pension expenditure Contributed to EU tax policy observatories Awards: Recipient of the national PhD award (1994) and recognition for academic excellence in tax policy research (2001). Teaching: Teaches courses in political economy, public finance, and macroeconomics at undergraduate and graduate levels.
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.
Tomaso Aste is a Professor of Complexity Science at the Department of Computer Science, University College London (UCL). He founded the Financial Computing and Analytics group and co-founded the UCL Centre for Blockchain Technologies. His work bridges complex systems, data science, and finance, with applications in blockchain, fintech, and market modeling. Education: PhD in Physics (Politecnico di Milano, 1994); Laurea in Physics (University of Genoa, 1990) Prior Appointments: Reader at University of Kent's School of Physics; Associate Professor at Australian National University's Applied Mathematics His research focuses on data-driven modeling of complex systems , particularly financial systems, complex networks, and statistical physics. He has pioneered information filtering networks and topological machine learning methods for financial applications, including portfolio optimization, risk assessment, and cryptocurrency analysis. Recent publications highlight his expertise in financial time-series analysis, blockchain technology, and AI-driven modeling. Articles explore topics like limit order books, cryptocurrency market fragility, and topological neural networks. His work has influenced regulatory technology (RegTech) frameworks and digital economy strategies. Scientific Awards : Marie Curie Individual Fellowship University of Genoa graduate study specialization Fellowship Bacheflor Boncompagni-Ludovisi Foundation Fellowship Awarded fellowships from European Commission and academic foundations support his interdisciplinary research. He has held editorial roles at journals like Philosophical Magazine and Granular Matter , and contributed to professional societies including American Physical Society and Australian Research Council panels. Teaching & Academic Leadership : Co-created four UCL Master's programs: Financial Risk Management, Computational Finance, Financial Technologies, Emerging Digital Technologies Coordinates executive training on AI, blockchain, fintech, and regtech for regulators and private firms Teaches graduate-level courses in Data-Driven Modeling, Data Science, and Advanced AI
Avi Turetsky is an Adjunct Professor at the Weatherhead School of Management (Case Western Reserve University) and a Research Fellow in private equity. Currently a Partner and Co-Head of the Quantitative Research Group (QRG) at Ares Management, he oversees original research, quantitative software development, and tools production teams. Previously served as Chief Operating Officer for The Riverside Company's Europe Fund and holds advisory roles at EDHEC and INSEAD . Research Focus: Turetsky’s work bridges private equity practice and quantitative finance, examining distributional patterns in investment outcomes, competency frameworks for financial professionals, and mathematical models for performance evaluation. His recent publications explore robust statistical methods in portfolio construction, direct alpha calculations for skill assessment, and sector-based value creation strategies in private equity-owned companies. Key Article Trends: His research spans 2016–2023, emphasizing quantitative methodologies in private equity, including skew analysis , value creation metrics , and competency clustering . Topics range from alliance changes in intercollegiate athletics to mathematical modeling of investment professional performance. Leadership & Teams: At Ares Management, Turetsky co-leads the QRG, managing cross-functional teams in Original Research , Quantitative Software Development , and Tools Production . He collaborates with investment teams to integrate quantitative strategies into decision-making processes.
Alexandra Livada is a Professor at the Department of Statistics within the School of Information Sciences and Technology at Athens University of Economics and Business (AUEB). She holds office at two locations: 12 Codringtonos Street, 2nd Floor and 76 Patision Street, Antoniadou Wing, 3rd Floor in Athens, Greece. Her contact information includes email livada@aueb.gr and phone number +30 210-8203521. Dr. Livada earned her BA and MA in Economics from Athens School of Economics and Business followed by a PhD in Economics from Essex University, UK in 1988. Her academic career has spanned several decades with extensive teaching experience at both undergraduate and postgraduate levels. Her research interests encompass a diverse range of quantitative fields: Quantitative economics and applied econometrics Time series analysis and forecasting techniques Income distribution and inequality measurement Applied financial econometrics Business cycles analysis Medical statistics Index numbers and official statistics Professor Livada's publication record demonstrates consistent scholarly productivity across multiple disciplines, with a noticeable trend toward interdisciplinary work connecting economics with healthcare and social policy. Her recent research shows increasing focus on income inequality across different geographic regions, economic sentiment during crises, and the intersection of medical conditions with statistical analysis. Her scholarly contributions have been recognized through numerous citations in leading journals and books. She has served as a referee for prestigious journals including the European Journal of Political Economy, Journal of Public Economics, and Journal of Insurance, Mathematics and Economics. Professional service highlights include: Member of multiple project teams Marie-Curie project supervisor External evaluator for the Greek State Scholarship Foundation (IKY) External evaluator for the Social Sciences and Humanities Research Council of Canada Co-author of the book "Index Numbers and Official Statistics" Professor Livada maintains an active research agenda with collaborations spanning economics, statistics, and medical fields, demonstrating the interdisciplinary nature of contemporary quantitative research.
Professor Hendrik Vollmer is a faculty member in the Accounting Group at Warwick Business School , University of Warwick, since 2020. He previously served as Head of the Accounting Division at the University of Leicester (2015–2020) and worked at Bielefeld University in Germany for 16 years. His research bridges accounting, sociology, and environmental studies, focusing on accounting as a social practice and its role in addressing ecological challenges. Senior Fellow of the Higher Education Academy Associate Editor of European Accounting Review Member of editorial boards for Zeitschrift für Soziologie, Accounting, Organizations and Society, and Social and Environmental Accountability Journal Active in sustainability accounting research and education Contributor to interdisciplinary accounting literature Recent publications explore accounting's role in climate change mitigation, public value creation, and the spatialization of worth. His teaching modules include Accounting for Sustainability, People, Planet and Financial Accounting: Theory and Context .
Timothy M. Hospedales is a Professor of Artificial Intelligence at the Institute of Perception, Action and Behaviour within the School of Informatics at the University of Edinburgh . He also serves as VP AI and Head of Samsung AI Research Centre Europe . His research focuses on efficient and robust AI , emphasizing meta-learning , lifelong transfer-learning , and domain adaptation in both probabilistic and deep learning frameworks. Applications span computer vision , vision and language , reinforcement learning for robotics , and finance . Professor at University of Edinburgh (2020–present) ELLIS Fellow (2021) Head of Samsung AI Research Europe (2020–present) Founding Director of Applied Machine Learning Lab at QMUL (2012–2016) His work includes pioneering contributions to meta-learning , few-shot learning , and self-supervised methods , with notable awards such as the Best Paper Prize at ICML AutoML 2018 and Best Student Paper at ICPR 2018 . He has co-authored 15+ recent papers on topics like Vision-Language Models , Medical AI Fairness , and Diffusion Model Optimization . He served as Program Co-Chair for BMVC 2018 and AAAI 2022 , and authored a book on Visual Adaptation in the Deep Learning Era (2022). Co-Chair, BMVC 2018 Guest Editor, IET CV Special Issue (2016) Keynote Speaker at TASK-CV Workshop (ECCV 2016) Special Issue on Fewer Labels (IEEE PAMI 2020) His leadership extends to organizing workshops like the Learning-to-Learn Workshop at ICLR 2021 , Meta-Learning Workshop at NeurIPS 2020 , and Domain Generalisation Workshop at ICLR 2023 . Current projects include Meta-Omnium (CVPR 2023) for general-purpose meta-learning and MetaAudio (ICANN 2022) for few-shot audio classification benchmarks.
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
Mungo Wilson is a Professor of Finance at the Saïd Business School , University of Oxford, and an associate member of the Oxford-Man Institute of Quantitative Finance. He holds a PPE degree from Oxford, an MSc in Economics from LSE, and a PhD in Economics from Harvard. His research focuses on asset pricing, credit risk, mutual funds, and macroeconomic influences on financial markets. He has published extensively in top journals and engages actively with industry through board roles and advisory work. Education : Bachelor's in Philosophy, Politics & Economics (PPE), University of Oxford MSc Economics, London School of Economics PhD in Economics, Harvard University Research Interests : Assesses how macroeconomic conditions and credit risk shape asset prices Analyzes mutual fund behavior and market information transmission mechanisms Explores political dynamics' impact on financial markets His professional engagements include board memberships with funds like EA Asia Absolute Return Master Fund and advisory roles at Broadwell Capital. Teaching focuses on microeconomics for MBA programs, covering game theory, market structures, and price discrimination. Advisory & Grants : Supervises doctoral students at Saïd Business School and serves on programme committees for major finance conferences (e.g., European Finance Association, CEPR Annual Spring Symposium). Awards : While no specific prizes are listed, his impactful research has been widely cited and presented globally.
Associate Professor Mark Humphery-Jenner is a distinguished faculty member at the University of New South Wales (UNSW) Business School, specifically within the School of Banking and Finance. With an exceptional academic pedigree including multiple PhDs from prestigious institutions worldwide, he has established himself as a leading researcher at the intersection of finance, law, and corporate governance. Dr. Humphery-Jenner's educational background demonstrates remarkable breadth and depth, featuring PhDs from UNSW, Tilburg University, and Leiden University, along with master's degrees from Columbia University and the University of Washington. His undergraduate achievements include a BCom with First Class Honours and University Medal, and an LLB with First Class Honours, both from UNSW. This multidisciplinary foundation spanning business, law, and finance informs his comprehensive research approach. His research spans corporate finance, venture capital, and law, with particular focus on how legal frameworks shape financial decision-making and corporate behavior. Humphery-Jenner has published extensively in top-tier finance journals including the Journal of Financial Economics, Journal of Financial and Quantitative Analysis, Review of Finance, and Journal of Corporate Finance, as well as leading management journals such as Strategic Management Journal and Journal of International Business Studies. His scholarly contributions address critical issues in executive compensation, securities litigation, corporate governance, and private equity markets. Analysis of his recent publications reveals a sophisticated research trajectory increasingly focused on the relationship between litigation risk and financial reporting practices, corporate governance mechanisms, and investor protection frameworks. His work demonstrates particular attention to Australian regulatory contexts while maintaining a strong international comparative perspective, especially regarding Asian capital markets and cross-border investment. With substantial industry experience including work in investment banking and consulting for hedge funds, Humphery-Jenner brings practical insights to his academic work. He has been teaching in various capacities since 2006 and has served as an assistant professor in finance since 2012, contributing significantly to business education at UNSW. His professional background enhances his ability to bridge theoretical research with real-world financial practice.
Andrea Modena is a Lecturer at Ca' Foscari University of Venice and a postdoc researcher at the University of Mannheim , Department of Economics. He is affiliated with the Bonn-Mannheim Center for Collaborative Research (CRC TR 224, Group C03) and the Leibniz Institute for Financial Research SAFE . His research bridges macroeconomic theory and financial economics, focusing on macro-finance dynamics and financial intermediation efficiency. Modena’s scholarly work explores the interplay between financial sectors and macroeconomic stability. His publications analyze business cycle fluctuations, risk pooling mechanisms, and leverage dynamics in financial intermediaries. While no formal awards are listed, his active participation in prestigious research groups (e.g., with Pietro Dindo and Loriana Pelizzon) underscores his contributions to economic theory. He holds a PhD in Economics from Ca' Foscari University of Venice (2020) and maintains dual academic roles, balancing research at Mannheim with teaching and affiliations at Ca' Foscari and Bonn. His expertise spans modeling macro-financial linkages, policy implications for financial sectors, and quantitative economic dynamics.
Nikolai Roussanov is the Moise Y. Safra Associate Professor of Finance at the Wharton School, University of Pennsylvania, and a Faculty Research Fellow at the National Bureau of Economic Research. His research spans asset pricing, econometrics, household finance, and macroeconomics, with a focus on market dynamics and behavioral economic factors. His research interests include: Asset pricing anomalies and risk factor modeling Household financial decision-making under uncertainty Macroeconomic impacts on commodity and currency markets Behavioral finance and mental accounting mechanisms Recent publications analyze inflation risks across asset classes, corporate bond valuation, behavioral retirement strategies, and the role of leisure economics in declining work hours. His work frequently integrates empirical finance and econometric methodologies. Scientific contributions include: Faculty Research Fellow, National Bureau of Economic Research His scholarship bridges technical financial modeling with real-world economic phenomena, covering topics like oil price shocks, mortgage liquidity, and systemic market failures.
Zhi Da is the Howard J. and Geraldine F. Korth Chair in Finance and Professor of Finance at the University of Notre Dame , Mendoza College of Business, Department of Finance. He completed his Ph.D. in Finance at Northwestern University’s Kellogg School of Management (2006), preceded by an M.Sc. in Financial Engineering from the National University of Singapore (2001) and a B.B.A. with First-Class Honors (1999) from the same institution. Holding editorial roles at Journal of Finance , Management Science , Review of Financial Studies and several other top journals, he is a leading voice in empirical finance research. Education Ph.D. in Finance, 2006 – Kellogg School of Management, Northwestern University M.Sc. in Financial Engineering, 2001 – National University of Singapore B.B.A. (1st Class Honors), 1999 – National University of Singapore Research Interests Zhi Da’s scholarship sits at the intersection of asset pricing , behavioral finance , and market microstructure . He investigates how investor attention, institutional trading, liquidity frictions, and information flows jointly determine the cross-section of expected returns. His work delves into retail margin trading, the role of pension-fund flows in exchange-rate dynamics, the informational content of SEC filings, and the efficiency of short-selling mechanisms. By combining large-scale data analytics, textual analysis, and structural modeling, he uncovers novel predictors of returns ranging from presidential approval ratings to real-time attention measures. Recent projects explore fractional trading ’s impact on price efficiency, hedging demand as a driver of intraday momentum, and the hidden effort problem in delegated portfolio management. These themes collectively advance our understanding of limits to arbitrage and the formation of extrapolative beliefs. Publication Landscape Spanning 2025 back to 2009, his 15 most recent articles in Journal of Finance , Review of Financial Studies , Management Science , Journal of Financial Economics , and Journal of Financial and Quantitative Analysis converge on three broad motifs: (1) micro-level trading frictions—liquidity costs, margin requirements, and short-selling constraints; (2) macro-finance linkages—exchange rates, fiscal policy, and global capital flows; and (3) information economics—attention allocation, media analytics, and regulatory disclosures. The collective evidence demonstrates that seemingly small trading or informational frictions aggregate into large, persistent cross-sectional return predictability. Honors and Awards 2017 William F. Sharpe Award for Best Paper, Journal of Financial and Quantitative Analysis Lead-article distinctions in Journal of Finance , Review of Financial Studies , and Management Science Featured coverage in SmartMoney and CNBC Teaching & Mentorship At Notre Dame’s Mendoza College, Professor Da teaches Investments (undergraduate and MBA) and Fixed Income Securities , integrating cutting-edge research insights into the curriculum. While specific advisees are not listed, his extensive co-author network (22+ recurring collaborators) attests to a vibrant mentoring environment. Laboratory & Data Resources He publicly distributes the NAT (Net Arbitrage Trading) dataset, a stock-quarter panel of arbitrage positions used in Chen, Da & Huang (2019). This resource has become a standard tool for researchers studying arbitrage capital movements.
University of Illinois Urbana-ChampaignUnited States
Liming Feng is an Associate Professor at the Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, and has served as Director of the Master of Science in Financial Engineering (MSFE) program since 2022. His academic career at the university spans from Assistant Professor (2006-2012) to his current role. He earned his Ph.D. in Industrial Engineering and Management Sciences from Northwestern University (2006), an M.S. in Mathematics from Northwestern University (2000), and a B.S. in Mathematics from Beijing Normal University (1997). Ph.D., Industrial Engineering and Management Sciences, Northwestern University, 2006 M.S., Mathematics, Northwestern University, 2000 B.S., Mathematics, Beijing Normal University, 1997 Feng’s research focuses on Financial Engineering, Stochastic Modeling, and Computational Methods. He has contributed extensively to quantitative finance, particularly in options pricing, portfolio optimization, and market impact models. His work leverages advanced numerical methods, Fourier transforms, and stochastic calculus to solve complex financial problems. The trends in his publications highlight expertise in Levy processes, jump diffusion models, and numerical algorithms for financial derivatives. He has developed innovative techniques for Bermudan options pricing, discretely monitored barrier options, and portfolio deleveraging strategies. His articles often intersect Operations Research with Financial Engineering, emphasizing computational efficiency and mathematical rigor. ISE Faculty Fellow (2025) INFORMS Financial Services Section Best Student Research Paper (2013) First runner-up of the 2012 Morgan Stanley Prize for Excellence in Financial Markets Feng has served on editorial boards for Operations Research Letters and Mathematical Finance . He has been recognized repeatedly for teaching excellence, including the Sharp Outstanding Teaching Award (2011, 2022) and multiple entries in the List of Teachers Ranked as Excellent by Their Students (2007-2024). He currently leads the MSFE program and contributes to curriculum development through courses like IE 522 (Statistical Methods in Finance) and IE 527 (MSFE Professional Development).
California Institute of Technology (Caltech)United States
Charles D. Sprenger is a Professor of Economics at the California Institute of Technology (Caltech), where he has served since 2020 and held the position of Executive Officer from 2022 to 2025. He is affiliated with Caltech's Division of the Humanities and Social Sciences (HSS) and holds key roles at the Ronald and Maxine Linde Institute of Economic and Management Sciences and the Center for Theoretical and Experimental Social Sciences (CTESS). His external appointments include Board of Editors for the American Economic Review and Associate Editor roles for the Journal of the European Economic Association and Quantitative Economics . His educational background includes a B.A. from Stanford University (2002), an M.Sc. from University College London (2005), and a Ph.D. from the University of California, San Diego (2011). These credentials established his foundation in economic theory and experimental methodology. Sprenger is a leading behavioral and experimental economist specializing in intertemporal decision making and choices under uncertainty. His research designs innovative experiments across diverse contexts—from food deserts in the United States to polio vaccination drives in Pakistan—to test the validity of standard economic models. His work consistently reveals significant deviations from rational choice theory, particularly regarding time inconsistency, risk preferences, and reference-dependent behaviors. He has pioneered methods for measuring time preferences and testing cumulative prospect theory, with implications for public policy and behavioral interventions. Analysis of his 15 most recent publications (2015-2024) shows a cohesive research program centered on behavioral anomalies in decision making. His work bridges laboratory precision with real-world field applications, demonstrating how psychological factors like procrastination and loss aversion manifest in high-stakes environments. Key trends include the development of tailored incentive structures, validation of rank-dependent utility models, and exploration of dynamic inconsistency across domains including health, finance, and public policy. His notable recognition includes: Sloan Foundation Fellowship (2016-2018) Sprenger actively contributes to the academic community through editorial leadership and collaborative research. His work has been featured in Caltech news for projects like "Reducing Procrastination with Tailored Incentives" (2023) and the graduate summer program "Experimental Economics in Theory and Practice" (2023). Though specific advisees aren't listed, his teaching of advanced courses like Experimental Economics (SS 212 abc) indicates mentorship of graduate researchers. He secures significant research funding through fellowships and institutional support, enabling large-scale field experiments. As a core member of CTESS, Sprenger leads a multidisciplinary team conducting cutting-edge experimental economics research. His lab integrates theoretical modeling with empirical validation, focusing on how behavioral insights can improve policy design in areas like tax compliance, vaccination programs, and financial decision making. Current work emphasizes scalable interventions for procrastination and preference-based incentive customization.
