Dr. IKM Mokhtarul Wadud is a Senior Lecturer in the Department of Economics at The University of Sydney, Australia. Previously, he held roles as Senior Lecturer at Deakin University, Lecturer at Monash University Malaysia, and Assistant Professor at the University of Rajshahi, Bangladesh. He earned his PhD in Economics from the University of Wollongong in 2001. His research focuses on productivity analysis, macroeconomic policy, energy economics, and applied econometric modeling. Notable contributions include co-authoring the Asia Pacific edition of Introductory Econometrics (Cengage Learning) and publishing in journals like Economic Modelling and Energy Policy . His recent work addresses financial sustainability strategies in higher education during the pandemic and the impact of economic policy uncertainty on property prices in Australia. Dr. Wadud has presented at international conferences and served as a reviewer for multiple journals. His research spans diverse regions, including Australia, Thailand, Malaysia, and Bangladesh, with analyses of oil price volatility, monetary policy effects, and industrial competitiveness.
Jim Hall is a Professor of Climate and Environmental Risk at the University of Oxford's School of Geography and the Environment, and serves as Director of Research there. He is also a Visiting Fellow at Linacre College and holds leadership roles including Chair of the Science Advisory Committee at IIASA, and Expert Advisor to the UK's National Infrastructure Commission. His work focuses on systemic risk analysis, infrastructure resilience, and policy implications of climate change adaptation. Prof Hall has pioneered methodologies like the National Infrastructure Systems Model (NISMOD) and chairs the Data and Analytics Facility for National Infrastructure (DAFNI). His research spans flood risk management, energy systems decarbonization, and transboundary water resource conflicts in regions such as the Eastern Nile Basin and the Caribbean. Key research areas include robust decision making under uncertainty, info-gap theory applications, and integrated assessments of human-environmental systems. He has contributed to major international assessments, including the IPCC's Fourth Assessment Report, and developed frameworks for multi-hazard stress testing of infrastructure networks. Scientific Awards: George Stephenson Medal (2001), Prince Sultan Prize for Water (2018), Royal Academy of Engineering Fellowship (2010) His advising and grants work includes mentoring a DPhil student Erin Canning and leading projects like MARIUS and ENHANCE. He has also developed innovative modeling tools for coastal erosion prediction and probabilistic assessments of global shipping fuel transitions. Prof Hall’s research groups actively engage in interdisciplinary projects, including the Oxford Martin Programme on Resource Stewardship and the UK Infrastructure Transitions Research Consortium. His work emphasizes bridging scientific analysis with actionable policy solutions for climate adaptation.
Professor Ben Goldys is a distinguished academic at The University of Sydney's School of Mathematics and Statistics, where he conducts research at the intersection of pure mathematics and applied sciences. His work spans multiple disciplines including stochastic analysis, partial differential equations, and financial mathematics, with significant contributions to both theoretical frameworks and practical applications in science and finance. Goldys' research interests center on stochastic (ordinary and partial) differential equations and their applications. His specific focus areas include stochastic partial differential equations, stochastic geometric PDEs, stochastic boundary value problems, stochastic fluid dynamics, ergodic theory of infinite-dimensional diffusions, and applications in financial mathematics such as interest rate derivatives, credit risk, and stochastic volatility. His work bridges pure mathematical theory (Functional Analysis, PDEs, Ergodic Theory) with complex real-world problems across multiple domains. His research aligns with the University of Sydney Faculty of Science Research Strengths including Understanding the Universe, Fundamental Laws of Nature, Complex Systems, and Next Generation Materials. Professor Goldys has secured multiple significant research grants from the Australian Research Council, including recent projects such as 'Mathematics for future magnetic devices' (2024), 'Mathematics for breaking limits of speed and density in magnetic memories' (2019), and 'Novel Approaches for Problems with Uncertainties' (2015). His current research projects focus on geometric stochastic partial differential equations and applications in micromagnetism, mean field games in finance, stochastic boundary value problems, and stochastic Navier-Stokes equations on the rotating sphere. He maintains extensive international collaborations with institutions in Germany (University of Tuebingen), Italy (LUISS University), Poland (Institute of Mathematics Polish Academy of Sciences), and the United Kingdom (University of York), working on projects involving optimal control, stochastic systems with memory, and geometric stochastic PDEs. Goldys is an active member of the Applied Mathematics Research Group and The University of Sydney Nano Institute, contributing to interdisciplinary research initiatives that connect mathematical theory with cutting-edge technological applications.
Olivier David Zerbib is an Assistant Professor of Sustainable Finance at CREST, ENSAE, Institut Polytechnique de Paris, and serves as an Associate Editor for the Review of Finance. His research bridges financial theory with environmental sustainability, focusing on market mechanisms for ecological challenges. His primary research areas include sustainable finance, environmental finance, and asset pricing, with specific expertise in green bonds, biodiversity valuation, and climate impact investing. He investigates how pro-environmental preferences influence pricing mechanisms, develops sustainable asset pricing models, and examines shareholder engagement strategies to curb greenwashing through quantitative methodologies. Analysis of his publications reveals a cohesive trajectory toward integrating environmental metrics into core financial frameworks, with significant contributions spanning green bond markets, sustainable CAPM development, and biodiversity economics. His work demonstrates methodological rigor through score-driven conditional betas and empirical validation across global markets. Dr. Zerbib's scientific recognition includes: #1 most cited article in the Journal of Banking and Finance over 3 and 5 years (2019) SUERF/UniCredit Research Prize (2018) Multiple Best Paper Awards at international finance conferences (2017-2020) European Investment Forum Research Prize Finalist (2021) He co-organizes the CMAP-CREST Quantitative Sustainable Economics and Finance seminar series with Patricia Crifo, Emmanuel Gobet, Peter Tankov, and Gauthier Vermandel, fostering collaboration between Ecole Polytechnique and ENSAE on quantitative approaches to sustainability challenges. His presentation record spans elite institutions including LSE, Yale, and the European Commission Joint Research Center.
Scientia Professor Robert Kohn is a distinguished academic at the University of New South Wales, holding a position in the School of Economics within the UNSW Business School. With a career spanning several decades, Professor Kohn has established himself as a leading expert in statistical methodology and econometric modeling. His research has significantly contributed to Bayesian statistics and computational methods for complex data analysis. Professor Kohn's research focuses on advanced statistical methodologies including Bayesian methodology, variable selection and model averaging, nonparametric regression models, time series modeling, multivariate Gaussian and non-Gaussian regression, and Markov chain Monte Carlo simulation algorithms. His work bridges theoretical statistics with practical applications across economics, finance, and cognitive science. His research demonstrates a consistent trajectory toward developing more efficient computational methods for complex statistical models, with recent work emphasizing variational Bayesian methods, particle filtering techniques, and applications to time series analysis. Analysis of his recent publications (2022-2025) reveals a strong focus on advancing computational statistical methods, particularly in Bayesian inference for complex models. His work shows increasing integration of machine learning techniques with traditional statistical methods, especially in handling high-dimensional data and complex time series structures. Professor Kohn has made significant contributions to variational inference methods, particle-based computational techniques, and applications to financial time series and cognitive modeling. Professor Kohn has maintained an exceptionally productive research career with continuous publication output since the 1970s, demonstrating remarkable longevity and adaptability in his research focus as statistical methodologies have evolved. His work shows strong international collaboration, particularly with researchers in Australia, the United States, and Europe, reflecting his standing in the global statistical community.
Ronnie Sircar is the Eugene Higgins Professor of Operations Research and Financial Engineering at Princeton University , where he contributes to the Department of Operations Research and Financial Engineering (ORFE). His work spans financial mathematics, stochastic modeling, and applied probability, with a focus on market volatility, optimal investment strategies, and dynamic game theory. Email: sircar@princeton.edu Office: Sherrerd Hall, Room 208, Princeton, NJ 08544 His research interests include: Stochastic Volatility: Asymptotic analysis, calibration, and impact on option pricing and portfolio optimization. Mean Field Games: Applications to cryptocurrency mining, energy markets, and interbank network formation. Portfolio Theory: Forward performance processes, drawdown constraints, and risk-averse strategies. Credit Risk: Multi-name credit derivatives, CDO valuation, and risk measures. Energy Systems: Renewable reliability, unit commitment, and electricity market design. Recent publications emphasize mean field games in energy and blockchain, stochastic volatility in portfolio optimization, and machine learning applications for financial engineering. He has advised graduate students such as Giulia Crippa, Nicolas Garcia, and Burak Aydin, often collaborating with researchers including M. Soner, P. Chan, and A.M. Reppen.
Rama Cont is Statutory Professor of Mathematics at the University of Oxford and Head of the Oxford Mathematical and Computational Finance Group. He holds additional positions as Senior Research Fellow at the Institute for New Economic Thinking and Director of the Oxford Martin Programme on Systemic Resilience. Cont's research focuses on stochastic analysis and mathematical finance, particularly modeling extreme market risks, systemic risk, and developing pathwise approaches in stochastic analysis. His recent work explores causal functional calculus, fractional Ito calculus, and analysis of deep neural networks. His publications demonstrate consistent development of mathematical frameworks for financial risk analysis, including recent advances in causal transport theory and market microstructure modeling. Cont received the Louis Bachelier Prize in 2010 and was elected SIAM Fellow in 2017 for contributions to stochastic analysis and financial modeling.
Stephen Graves is the Abraham J. Siegel Professor of Management and a Professor of Operations Management at MIT Sloan School of Management, with a joint appointment in Mechanical Engineering. He holds a PhD in Operations Research from the University of Rochester. His research focuses on operations research models applied to manufacturing systems, supply chains, and service operations, including strategic inventory positioning and order fulfillment optimization. Graves has served as MIT Sloan’s Deputy Dean and Chair of MIT’s Faculty Council (2001-2003). He is a Fellow of INFORMS, recipient of the Kimball Medal, and member of the National Academy of Engineering. Education: PhD in Operations Research, University of Rochester MBA and AB in Mathematics/Social Sciences, Dartmouth College Research Interests: Graves develops analytical frameworks for supply chain optimization, inventory management, and production planning. His recent work addresses post-pandemic supply chain resilience, digital twins for production systems, and closed-loop supply chains. Current projects explore operational challenges in e-commerce fulfillment and global supply networks. Awards: INFORMS Kimball Medal (2023) Elected to National Academy of Engineering INFORMS Prize for Operations Research President of INFORMS (2020) Advising & Grants: Supervisor to 25+ PhD students across manufacturing, supply chain analytics, and healthcare operations. Active in industry collaborations with companies like Intel, Polaroid, and Monsanto. Leads MIT initiatives including the Leaders for Global Operations program. Labs/Teams: Core member of MIT’s Institute for Data, Systems, and Society (IDSS). Co-director of the MIT Operations Research Center. Involved in interdisciplinary projects combining data science with operations management.
Dr Yizhi Wang, FHEA, is a Lecturer (Assistant Professor) in Finance at Cardiff Business School, Cardiff University, UK. He serves as Co-Director of the Cardiff Fintech Research Group and is the Editor-in-Chief of Elsevier’s Finance Research Letters . He is also Associate Editor for International Review of Financial Analysis and Research in International Business and Finance , and Guest Editor for International Review of Economics & Finance and Journal of Chinese Economic and Business Studies . Research Interests: Financialization and Econometrics Climate finance and carbon markets Cryptocurrency and FinTech indices Energy economics and risk management Green finance and ESG investing Behavioral and institutional finance Dr Wang has published extensively in world-leading journals such as Risk Analysis , European Journal of Operational Research , Journal of Economic Behavior & Organization , Energy Economics , and Journal of International Money and Finance . His work spans theoretical modeling, empirical econometrics, and policy-oriented studies. Scientific Awards: Shanghai Institute of International Finance and Economics Best Paper Award Teaching & Supervision: As a Fellow of the UK Higher Education Academy (FHEA), Dr Wang is module leader for undergraduate BS2514: Financial Markets and Institutions and postgraduate BST158: Big Data Analytics for Finance , earning consistently high teaching evaluations (4.8–4.9/5). He is available to supervise doctoral students in Financialization and has mentored graduates now employed at the University of Oxford, Morgan Stanley, and JPMorgan Chase. Labs & Research Groups: Co-Director, Cardiff Fintech Research Group Member, Cardiff Sustainable Finance Research Group Member, Environmental, Ecological, Extinction Accounting, Governance and Economics Research Group Member, Cardiff Business School Research Committee Dr Wang also curates multiple quarterly-updated indices (UCRY, ICEA, CBDCAI, NFTsAI, ACCC, FinTech Index) publicly available at https://sites.google.com/view/cryptocurrency-indices/home .
Martin Larsson is a Professor in the Department of Mathematical Sciences at Carnegie Mellon University (CMU), affiliated with the Mellon College of Science. He holds a Ph.D. from Cornell University and completed a postdoctoral appointment at the Swiss Finance Institute at EPFL, Lausanne, Switzerland. His research focuses on Mathematical Finance, stochastic analysis, probability, and statistics, with emphasis on affine and polynomial processes, stochastic portfolio theory, and sequential statistics. Key research domains include modeling interest rate term structures, large-scale equity market dynamics, and statistical testing in online settings. He serves as the Departmental representative for the Master of Science in Computational Finance (MSCF) program at CMU. Larsson has received the Bruti-Liberati Visiting Fellowship from the University of Technology Sydney. His work bridges theoretical probability with applications in finance, including contributions to stochastic volatility modeling, optimal contracts in trading, and robust portfolio optimization under uncertainty. Publications span topics such as martingale exit times, Wasserstein distance convergence, and ergodic control in stochastic systems, reflecting his interdisciplinary approach to mathematical finance and probability theory. His research often combines analytical techniques with stochastic control and geometric flows.
W. Brent Lindquist is a Professor in the Department of Mathematics and Statistics at Texas Tech University, affiliated with the TTU Mathematical Finance Program. His contact details include office location in the Mathematics & Statistics building (Room 104), phone (+1 806 834 2348), and email brent.lindquist@ttu.edu. His research spans computational financial mathematics, porous media flow, neuroscience applications, and quantum electrodynamics. Key contributions include dynamic asset pricing with market microstructure integration, pore-scale flow modeling using 3D micro-tomography, automated neuron morphology identification, and QED computations for electron magnetic moments. Recent work emphasizes ESG factor incorporation into financial models. Analysis of 2023–2025 publications reveals a dominant focus on sustainable finance, particularly ESG-integrated option pricing and portfolio optimization. Methodologies include random forests for market microstructure analysis, skew random walks for volatility modeling, and Lévy processes for Bitcoin dynamics. Cross-cutting themes involve hedonic real estate models with ESG factors and unified asset pricing frameworks bridging classical finance theories.
Prof. Claudio J. Tessone is a Professor of Blockchain and Distributed Ledger Technologies at the Department of Informatics, University of Zurich. He serves as Head of the Blockchain and Distributed Ledger Technologies group, Chairman of the UZH Blockchain Center, and is incharge of the NetSci Society. His academic background includes a PhD in Physics (Complex Systems) and an Habilitation in Complex Socio-Economic Systems from ETH Zurich. Education: PhD in Physics (2006): Thesis on synchronization in stochastic systems, Universitat de les Illes Balears, Spain Habilitation (2015): Thesis on agent-based modeling of socio-economic systems, ETH Zurich Master in Physics (1999): Thesis on stochastic resonance, Instituto Balseiro, Argentina Research Interests: Prof. Tessone specializes in modeling complex socio-economic and socio-technical systems, with a focus on blockchain-based systems. His work explores crypto-economics, blockchain scalability, decentralized finance (DeFi), and the interplay between micro-level agent behavior and macro-level emergent properties. Notable areas include transaction network analysis in Bitcoin/Ethereum, consensus mechanisms (Proof-of-Stake/Work), and blockchain governance models. Publications Trends: Recent articles emphasize empirical blockchain analysis (e.g., Ethereum microvelocity, Bitcoin mesoscopic structure), DeFi arbitrage strategies, and privacy-preserving blockchain applications in healthcare. His work bridges theoretical agent-based models with real-world blockchain datasets, addressing both technical and socio-economic dimensions of distributed ledger technologies. Grants & Labs: Director of the UZH Summer School on Blockchain and Certificate of Advanced Studies program. Active in interdisciplinary collaborations through the URPP Social Networks (2015–2021) and ETH Zurich’s Systems Design group (2007–2014). Labs/Initiatives: Leads the UZH Blockchain Center, a hub for academic-industry research on blockchain applications in finance, governance, and digital transformation.
Duane J. Seppi is a Professor of Financial Economics at the Tepper School of Business , Carnegie Mellon University since 2001, currently holding the Richard C. Green Professor chair. His research focuses on market microstructure (price manipulation, limit orders, market liquidity) and derivative pricing for commodities. PhD in Finance from University of Chicago (1988) MBA from University of Chicago (1984) BA from Stanford University (1977) His work bridges financial theory with commodity operations , exploring topics like natural gas storage valuation , electricity price modeling , and merchant commodity asset management . Key publication trends include Nash equilibrium in price impact , latent trading demand analysis , and commodity real options . Scientific awards include: Best Paper Award (2015) WFA/NYSE Prize (2005) George Leland Bach Award (2002) Roger F. Murray Prize (1998) As a dedicated educator , he teaches option pricing , stochastic processes , and algorithmic trading . His editorial board service spans the Journal of Finance , Journal of Financial Markets , and Review of Finance . Duane has held visiting fellowships at the U.S. SEC , University of Vienna , and Nanyang Technical University .
Prof. Dr. Rudi Zagst is a Professor of Mathematical Finance at the Technical University of Munich (TUM), where he serves as Head of the Department of Mathematical Finance within the TUM School of Computation, Information and Technology. He has held this position since 2001 and is actively involved in teaching, research, and academic leadership. In 2003, he was appointed as a second member of the Faculty of Economics, and since 2004, he has served as Deputy Chairman of the joint elite degree program 'Finance & Information Management' of the University of Augsburg and TUM. Prof. Zagst earned his doctorate in business mathematics from the University of Ulm, where he later completed his habilitation in 2000. His academic journey began with a professional career at HypoVereinsbank AG, where he served as Head of Product Development in Institutional Investment Management before becoming Managing Director of RiskLab GmbH in 1997. His research focuses primarily on financial engineering, risk management, and asset management, with particular emphasis on portfolio optimization, mathematical finance, and quantitative risk management. His work bridges theoretical finance with practical applications, often incorporating advanced mathematical techniques to solve complex financial problems. Recent publications demonstrate his continued interest in GARCH models, portfolio optimization under various constraints, and the application of machine learning techniques to financial problems. Analysis of his recent publications (2024-2025) reveals a strong focus on portfolio optimization under complex market conditions, particularly using GARCH models to capture volatility dynamics. His work increasingly incorporates machine learning techniques (as seen in the credit spread analysis paper) while maintaining rigorous mathematical foundations. Many papers explore the intersection of theoretical finance with practical investment strategies, reflecting his commitment to bridging academic research with real-world financial applications. Professor of the Year 2007 (awarded by Unicum Profession magazine) Prof. Zagst has supervised numerous bachelor's, master's, and doctoral theses through TUM's Finance and Actuarial Science research group. His collaborative work with industry partners through the TUM CAIR Labs and RiskFactory demonstrates strong connections between academic research and practical financial applications. He has received research funding through various industry partnerships with major financial institutions including Allianz, Munich Re, and ERGO Group AG. Prof. Zagst leads the Research Group Finance and Actuarial Science at TUM, which includes Professors Matthias Scherer, Aleksey Min, and Christoph Knochenhauer. The group maintains strong industry connections through the TUM CAIR Labs initiative, collaborating with over 25 financial institutions including Allianz, Munich Re, Deloitte, PwC, and KPMG. Their RiskFactory laboratory serves as a bridge between academic research and practical financial risk management applications in the industry.
Christopher Polk is Professor of Finance at LSE and former Head of the Finance Department. His research on asset pricing and investment strategies has received numerous awards including the Fama-DFA Prize for best paper in capital markets. Polk developed influential models integrating stochastic volatility into intertemporal asset pricing theory and has made significant contributions to understanding value investing cycles. He currently teaches Sustainable Finance and Impact Investing while leading research on factor premia variation across business cycles. Fama-DFA Prize (2018) AQR Insight Award (2014) Jensen Prize (2002) Q Group Research Award Inquire Europe Research Award
