Find Academic Supervisors

Alessio LomuscioView profile

Professor

• Artificial Intelligence
• Machine Learning Verification
• Neural Network Verification
• +5 more

Alessio Lomuscio is a Professor of Safe Artificial Intelligence at Imperial College London, holding the prestigious Royal Academy of Engineering Chair in Emerging Technologies and recognized as an ACM Distinguished Member. He leads the Safe AI Lab, which focuses on developing methods and tools for the verification of AI systems to ensure their safe and secure deployment in applications of societal importance. His research spans verification and robust learning for neural networks and decision trees, robust machine learning in aviation and finance, monitoring of machine learning systems, assurance for autonomous systems and AI, and verification and validation of neuro-symbolic systems. Lomuscio has made significant contributions to formal verification methods for AI systems, particularly in the context of safety-critical applications. His recent publications demonstrate a strong focus on neural network verification techniques, with applications across multiple domains including finance, aviation, and autonomous systems. His work bridges theoretical advances in formal methods with practical applications in real-world AI systems, addressing critical challenges in AI safety and trustworthiness. Scientific Awards: Royal Academy of Engineering Chair in Emerging Technologies ACM Distinguished Member Lomuscio has served in numerous leadership roles, including as Co-Director (2023-present) and Deputy Director (2019-2023) of the UKRI Centre for Doctoral Training in Safe and Trusted Artificial Intelligence. He has also held positions as Director of Strategy and Planning (2017-2020), Member of Management Committee (2013-2020), and Deputy Head of Department (2016-2017). His editorial service includes roles as Associate Editor for Artificial Intelligence Journal and Editorial Board Member for Journal of Artificial Intelligence Research and Journal of Autonomous Agents and Multi-agent Systems. His research group actively mentors students and researchers, with current openings for PhD and postdoctoral positions focused on AI verification and safety. Lomuscio's work has established him as a leading figure in the field of safe and verifiable AI systems, with significant contributions to both theoretical foundations and practical applications.

Martin T. WellsView profile

Professor

• Applied Statistics
• Theoretical Statistics
• Bayesian Statistics
• +7 more

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 WilsonView profile

Professor

• Asset Pricing
• Macroeconomics
• Credit Risk
• +3 more

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.

Andrew PostlewaiteView profile

Professor

• Game Theory
• Behavioral Economics
• Social Norms
• +3 more

Andrew Postlewaite is the Harry P. Kamen Professor of Economics and Professor of Finance at the University of Pennsylvania's School of Arts and Sciences. He holds dual roles in the Department of Economics and the Ronald O. Perelman Center for Political Science and Economics. As a distinguished academic, he is a member of the American Academy of Arts and Sciences and serves as a director at the National Bureau of Economic Research (NBER). Additionally, he is the founding editor of the American Economic Journal: Microeconomics and a research associate at Penn's Population Studies Center and Institute for Law and Economics. Postlewaite's research focuses on game theory, behavioral economics, and social norms, with contributions to mechanism design, repeated games, and intergenerational transmission of preferences. His work bridges theoretical foundations with applied economic analysis, particularly in areas like consumer behavior, decision-making, and institutional design. He has held visiting positions at institutions including Caltech, Harvard, and Stanford, reflecting his academic prominence. His scholarly contributions include pioneering studies on future-oriented decision-making, interdependent valuations in markets, and equilibrium concepts in repeated games. Recent publications explore topics such as the impact of local media accessibility in the digital age and the welfare implications of consumption fluctuations. His editorial leadership at journals like Econometrica and International Economic Review underscores his influence in shaping economic discourse. Awarded prestigious fellowships and editorial roles, Postlewaite's career exemplifies a blend of rigorous theoretical research and practical applications in economics. His current research trends emphasize behavioral insights and the methodological underpinnings of economic models, reflecting a commitment to advancing both theory and real-world relevance.

Nikolai RoussanovView profile

Associate Professor

• Asset Pricing
• Econometrics
• Household Finance
• +1 more

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.

• Financial Engineering
• Operations Research
• Stochastic Modeling
• +3 more

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).

Shan LuView profile

Lecturer

• Financial Derivatives
• Option Pricing
• Quantitative Finance
• +3 more

Dr. Shan Lu is a Lecturer in Finance at the Department of Accounting and Finance, Kent Business School, University of Kent, since August 2021. He previously held positions at the University of Aberdeen and the University of Bradford and earned his PhD from the University of Aberdeen. Research interests: Financial derivatives, option pricing, and quantitative finance. His work focuses on volatility modeling, risk-neutral density estimation, and computational finance, with publications in journals such as the European Journal of Finance, Journal of Futures Markets, and Economics Letters. Teaching: Covers financial markets, derivatives, econometrics, and quantitative methods at undergraduate and postgraduate levels. Scientific awards: Fellow (FHEA) of Higher Education Academy Advising: Offers PhD supervision in topics aligned with his research interests, including financial derivatives and quantitative finance. He emphasizes collaboration on research ideas directly related to his expertise. Publications: Recent work explores volatility dynamics in VIX/VXX options, risk-neutral density extraction, and implied volatility forecasting, leveraging computational methods and empirical finance techniques.

Suzanne S. LeeView profile

Associate Professor

• Financial Econometrics
• Empirical Finance
• Asset Pricing
• +6 more

Suzanne S. Lee is an Associate Professor of Finance at the Scheller College of Business, Georgia Institute of Technology, where she has been a faculty member since 2005. She also serves as the Ph.D. Coordinator, playing a key role in graduate education and research training. Her educational background is highly quantitative and interdisciplinary: Ph.D., University of Chicago MBA, University of Chicago M.S. in Statistics, University of Chicago Dr. Lee's research lies at the intersection of asset pricing and financial econometrics, with a strong focus on jump processes, market microstructure, and derivative markets. She investigates how sudden price movements (jumps) impact asset returns, risk, and information flow in financial markets. Her work extends to cryptocurrency, currency markets, and carry trade strategies, combining theoretical rigor with empirical validation using high-frequency data. The analysis of her recent publications (2008–2024) reveals a consistent and influential research program centered on detecting and modeling jumps in financial time series. Her work spans equity, currency, and cryptocurrency markets, often employing advanced nonparametric and econometric techniques. A recurring theme is the role of jumps in pricing anomalies, risk measurement, and market efficiency, with increasing attention to digital assets in recent years. Dr. Lee is actively engaged in the academic community through editorial service: Associate Editor, Journal of Banking and Finance Associate Editor, Asia-Pacific Journal of Financial Studies She has presented her research at premier conferences such as the American Finance Association, European Finance Association, Econometric Society, and Society for Financial Econometrics. Her publications appear in the most prestigious journals in finance and econometrics, including the Journal of Finance , Review of Financial Studies , Journal of Financial Economics , and Journal of Econometrics . While specific grant details are not listed, her sustained publication record in top journals indicates significant research funding and academic impact. She advises Ph.D. students through her role as Ph.D. Coordinator, though individual advisees are not named in the text. Dr. Lee's work contributes to both theoretical and applied finance, improving our understanding of market dynamics, risk modeling, and asset pricing under extreme events. Her research has practical implications for risk management, trading strategies, and financial regulation.

• Applied Financial Economics
• Economics of Security
• Financial Risk Management
• +3 more

Konstantinos Drakos is a Professor at the Department of Accounting and Finance, Athens University of Economics and Business (AUEB). Previously, he served as Assistant Professor at AUEB (2009–2012), Assistant Professor at the University of Patras (2003–2008), and Lecturer at the University of Essex (2001–2002). He holds a PhD in Economics from the University of Essex, preceded by an MSc and undergraduate studies in Economics at the University of Athens. His research focuses on Applied Financial Economics and the Economics of Security, with recent work analyzing hedge fund leverage, geopolitical risk impacts, cryptocurrency markets, and green banking. Teaching responsibilities include Macroeconomic Theory, Finance for Banking, and Risk Management at both undergraduate and postgraduate levels. Drakos' publications span over two decades, addressing topics such as terrorism's economic effects, bank lending behavior, and investment under uncertainty. His recent articles (2022–2025) emphasize cryptocurrency dynamics, geopolitical risk interactions, and financial stability in green banking. Notable themes include market volatility, capital allocation under uncertainty, and policy responses to systemic risks. No scientific awards are listed in the provided materials. His research has explored structural shifts in financial risk, macroeconomic sentiment, and cross-market linkages following major global events like 9/11 and the 2008 crisis. Drakos has advised on policy-related topics related to financial markets and regulatory frameworks, though specific grants or lab affiliations are not detailed here.

Christian WolfView profile

Assistant Professor

• Macroeconomics
• Monetary Economics
• Time Series Econometrics
• +3 more

Christian Wolf is an Assistant Professor at the Massachusetts Institute of Technology (MIT) Department of Economics and a Faculty Research Fellow at the National Bureau of Economic Research (NBER). His work bridges macroeconomics, monetary economics, and econometric methodology. Research Interests: Wolf specializes in macroeconomics and monetary policy , with a focus on econometric techniques like structural vector autoregressions (VARs) and local projections . His research explores policy counterfactuals, heterogeneous-agent models, and fiscal-monetary interactions. Recent Publications: His work spans topics such as equivalence between fiscal and monetary tools in HANK models, robust identification in VARs, and the interplay between inequality and macroeconomic dynamics. Articles appear in journals like Econometrica , Journal of Political Economy , and American Economic Review . Awards: Faculty Research Fellow, NBER Contact: ckwolf@mit.edu | Office: E52-554, MIT

Peter K. KitanidisView profile

Professor

• Groundwater Flow
• Hydrologic Modeling
• Inverse Problems
• +3 more

Peter K. Kitanidis is a Professor in the Department of Civil and Environmental Engineering and the Institute for Computational and Mathematical Engineering at Stanford University . His research focuses on groundwater flow , hydrologic forecasting , and stochastic inverse modeling , with applications to pollutant remediation and CO₂ storage monitoring . Education : Diploma, National Technical University of Athens (1974) M.S., MIT (1976) Ph.D., MIT (1978) Research Interests : Groundwater modeling and contaminant transport Hydraulic tomography and aquifer characterization Stochastic methods for uncertainty quantification Bioremediation and enhanced in-situ pollutant decay Dilution and mixing processes in heterogeneous media Real-time river flow forecasting Scientific Awards : L.G. Straub Award (1979) W.L. Huber Research Prize (1994) ISI Highly Cited Researcher (2001) AGU Hydrologic Sciences Award (2011) ASCE Pioneers in Groundwater Lecturer (2011) Advising and Grants : Advised 20+ PhD and MS students (1978–2018) Principal investigator on NSF, EPA, and DOE-funded projects Developed software for groundwater data analysis and CO₂ monitoring Contributed to bioremediation protocols and hydraulic tomography algorithms Labs and Teams : Kitanidis Laboratory for groundwater crisis solutions Collaborated with Oak Ridge National Laboratory and Stanford Hydrogeology Group Mentored postdocs (2000–2017) in reactive transport and inverse modeling

Gary RochelleView profile

Professor

• Chemical Engineering
• Carbon Capture
• Amine Scrubbing
• +3 more

Gary Rochelle is the Carol and Henry Groppe Professor in Chemical Engineering and a faculty member at the University of Texas at Austin . His research focuses on developing fundamental insights into kinetic and mass transfer phenomena in aqueous technologies for air pollution control and acid gas treating, particularly for carbon dioxide and mercury removal. Education: Ph.D. in Chemical Engineering from UC Berkeley (1977), M.S./B.S. from MIT (1971) His work addresses critical challenges in CO2 capture using amine scrubbing, including process design optimization, solvent degradation mitigation, and pilot plant validation. Recent studies emphasize energy efficiency, oxidation inhibition, and environmental impacts such as amine aerosol emissions. The Texas Carbon Management Program , which he contributes to, aims to improve amine scrubbing technologies for retrofitting power plants and enabling geological sequestration or enhanced oil recovery. His group has validated concentrated aqueous piperazine (PZ) with an advanced flash stripper as the most efficient open-literature system.

Carolin PfluegerView profile

Associate Professor

• Macroeconomics
• Finance
• Monetary Policy
• +6 more

Carolin Pflueger is an Associate Professor at the Harris School of Public Policy , University of Chicago, and holds affiliations as a NBER Faculty Research Fellow and CEPR Research Affiliate . Her work bridges macroeconomics and finance, focusing on inflation dynamics, monetary policy impacts, and financial market risk perception. University: University of Chicago School: Harris School of Public Policy Affiliations: NBER, CEPR Role: Associate Professor Her research explores how inflation and monetary policy influence financial markets, including models connecting Treasury bond risk to stagflation drivers and analyzing economic agents' perceptions of policy uncertainty. Recent work leverages cross-sectional data of stock prices and economic forecasts to quantify macrofinancial linkages. Notable scientific recognitions include the Fama DFA Prize (2023), AQR Insight Award Finalist (2018), and the Arthur Warga Award (2014). She has received NSF Grant 2149193 for macrofinance research. Contact: cpflueger@uchicago.edu | GitHub Code Repositories

Ying ChenView profile

Associate Professor

• Financial Statistics
• Machine Learning
• Quantitative Finance
• +7 more

Assoc Prof Ying Chen is an Associate Professor at the National University of Singapore , affiliated with the Department of Mathematics, Asian Institute of Digital Finance (as Academic Director of PhD Program in Digital FinTech 2022–2024), Risk Management Institute (2019–2023), Department of Statistics and Data Science (2019–2023), and Department of Economics (2018–2023). She also contributes to NUS Graduate School for Integrative Sciences and Engineering since 2016. Research Interests include: AI forecasting and quantum computing for finance Nonstationary time series and functional data analysis Energy data analytics and precision medicine Network autoregression and spatial-temporal modeling Explainable AI and citation metrics Portfolio liquidation and market-making algorithms Article Trends demonstrate expertise in: Adaptive forecasting for gas flows and electricity prices Blockchain network influence detection Quantum computing applications in finance Functional autoregression with mixed predictors Credit rating fairness and explainability High-resolution implied volatility modeling Scientific Awards include: ISI Elected Member (2016–) International Statistical Institute Council (2023–2027) IASC Scientific Secretary (2017–2019, 2023–2025) Advisory roles for EU FIN-TECH and xAIM projects

John CotterView profile

Professor

• Finance
• Quantitative Finance
• Volatility Modelling
• +5 more

John Cotter is a Full Professor of Finance and Chair in Quantitative Finance at University College Dublin's Smurfit School of Business. He holds a PhD from Queen's University Belfast and prior academic roles include Associate Professor (2006-2012) and Senior Lecturer (2004-2006). His research focuses on volatility modeling, risk management, and asset pricing with applications in equity, real estate, and derivative markets. Cotter directs the Centre for Financial Markets and the Financial Mathematics Computation Cluster (FMC2), a multi-university research initiative funded by Science Foundation Ireland. Education: BComm and MEconSc from University College Cork, PhD in Finance from Queen's University Belfast. Research interests span asset pricing, volatility modeling, risk management, and financial market integration. His work has been published in top journals like Journal of Banking and Finance and Journal of International Money and Finance . He has secured grants including the ADAPT Phase 2 project (2021-2026). Cotter advises the European Securities Markets Authority (ESMA) and has consulted for numerous organizations globally. Notable awards include the UCD Outstanding Educator Teaching Award and UCD School of Business Research Contribution Award. He serves as Associate Editor for three journals and has supervised numerous PhD students through FMC2.