جست‌وجوی استاد و پژوهشگر

Kingsley Yuen Lung Fongمشاهده پروفایل

دانشیار

• Market Microstructure
• Investment
• Wealth Management
• +۵ مورد دیگر

Kingsley Yuen Lung Fong is an Associate Professor of Finance at the UNSW Business School, specializing in Banking and Finance. He has published extensively in leading international finance journals and co-founded the RISE Finance Lab to explore how finance can better foster well-being, relational trust, and long-term stewardship. Institution: University of New South Wales School: UNSW Business School Department: Banking and Finance His academic work is guided by the principle that finance is an evolving design for organizing life and activity across individuals and society. Fong's research expertise spans market microstructure, investment, household finance, and sustainable finance. He has made significant contributions to understanding the connections between finance, society, and nature for a flourishing future. The analysis of his 15 most recent publications reveals a strong focus on market microstructure, trading behavior, and sustainable finance. His work examines algorithmic trading impacts, liquidity measurement, household investment decisions, and regulatory aspects of financial advice. Fong's research demonstrates consistent interest in how financial systems can be designed to better serve societal needs while maintaining market efficiency. 2017 Review of Finance Spängler IQAM Prize 2021 Aspen Institute Ideas Worth Teaching Award 2022 S&P Global Decarbonisation Hackathon As an educator, Fong teaches Wealth Management and Client Engagement, Sustainable Investing, and Sustainable Finance. His leadership roles include serving as Deputy Head of School for Banking and Finance (2011-2019), Co-Founder of UNSW RISE Finance Lab (2025), and member of the Australian Sustainable Finance Institute Sustainable Finance Capability Reference Group (2024). Beyond traditional finance, he created DATKIS, an intellectual framework that grounds common sense and intelligence in truth, awareness, and design.

Moncef Gabboujمشاهده پروفایل

استاد

• Machine learning
• Artificial intelligence
• Signal processing
• +۹ مورد دیگر

Professor Moncef Gabbouj is a distinguished academic and researcher currently serving as Professor of Signal Processing at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University, Finland. Previously, he held the same position at Tampere University of Technology before the merger in 2019. He has also held visiting professorships at prestigious institutions including Hong Kong University of Technology and Science, University of Southern California, and Purdue University. Ph.D. and MSc. in Electrical Engineering from Purdue University, USA (1989 and 1986) B.Sc. in Electrical Engineering from Oklahoma State University, USA (1985) Prof. Gabbouj's research spans multiple domains within signal and image processing, with a strong focus on machine learning applications. His primary research interests include artificial intelligence, machine learning, Big Data analytics, multimedia content-based analysis, indexing and retrieval, nonlinear signal and image processing, voice conversion, and video processing and coding. His work bridges theoretical advancements with practical applications across various industries, particularly in multimedia communications and biomedical applications. His extensive publication record demonstrates a clear evolution from traditional signal processing techniques toward more sophisticated machine learning and deep learning approaches. Recent work shows increasing focus on convolutional neural networks for various applications including ECG classification, video processing, financial time-series analysis, and image recognition tasks, reflecting the broader trend in the field toward deep learning methodologies while maintaining strong foundations in signal processing theory. IEEE Fellow (2011) Member, Finnish Academy of Science and Letters (2014) Knight, First Class, of the Order of the White Rose of Finland (2006) Nokia Foundation Recognition Award (2005) Nokia Foundation Visiting Professor Award (2012) Finnish Cultural Foundation for Art and Science Award (2017) TUT Foundation Grand Award (2015) Prof. Gabbouj has supervised 64 doctoral and 72 Master's theses, demonstrating his significant contribution to academic mentoring. His research has been supported by substantial funding, including research grants totaling 8.5 million Euro (2001-2015). He has served as Academy of Finland Professor during 2011-2015 and has been involved in numerous EU research projects including Horizon, ESPRIT, HCM, IST, COST, Tempus and Erasmus programs. As Editor, Guest Editor or member of the Editorial Board of 6 international scientific journals, he has significantly influenced the academic discourse in his field. He leads the Signal Analysis and Machine Intelligence (SAMI) research group at Tampere University and serves as the Finland Site Director of the NSF IUCRC funded Center for Visual and Decision Informatics. His research unit focuses on applying advanced machine learning techniques to solve complex problems in signal processing, computer vision, and multimedia analytics, with applications ranging from healthcare to multimedia communications and financial analysis.

George Skiadopoulosمشاهده پروفایل

استاد

• Asset Pricing
• Commodities
• Financial Derivatives
• +۳ مورد دیگر

George Skiadopoulos is a Professor of Finance at the University of Piraeus (Department of Banking and Financial Management) and Queen Mary University of London (School of Economics and Finance). He serves as Director of the Institute of Finance and Financial Regulation (IFFR) and holds an Honorary Senior Visiting Fellowship at Bayes Business School, City University of London. His research focuses on asset pricing, commodities, financial derivatives, climate finance, and ESG integration. He has published in prestigious journals like Management Science and Journal of Financial and Quantitative Analysis, and his work influences policy at institutions like the European Securities Markets Authority (ESMA). Education: PhD in Finance from the University of Warwick, M.Sc. in Mathematical Economics from LSE, and a Ptychion in Economics from Athens University of Economics and Business. He has advised financial institutions globally and received grants from the Chicago Mercantile Exchange and others. His notable award is the 2018 German Finance Association best paper prize for work on transaction costs and stock returns. He has also contributed to executive training and policy discussions on climate-related financial risks.

• Corporate Governance
• Earnings Management
• Voluntary Disclosure
• +۶ مورد دیگر

YUE Heng is a Full-time Professor of Accounting at Singapore Management University (SMU), holding dual roles as Director of the SMU-ZJU Doctor of Business Administration (Accounting & Finance) Program and Programme Director of the SMU Tsinghua Joint Master of Science in CFO Leadership. He joined SMU in 2015 after teaching at Peking University, where he earned his Bachelor's degree in Management from the Guanghua School of Management. He holds a PhD in Accounting from Tulane University's Freeman School of Business. His research focuses on corporate governance, earnings management, voluntary disclosure in emerging markets, and capital market dynamics. Notable contributions include studies on tunneling through intercorporate loans, political corruption impacts on reporting quality, and cultural influences on corporate risk-taking. His work has been published in top journals like the Journal of Financial Economics and The Accounting Review . Honors include the Liyining Research Award (2013) and the ICBC Economic Scholar Award (2011). He advises doctoral students in accounting and has contributed to curriculum development in executive education programs. His current research explores green transition challenges, audit quality in anti-corruption contexts, and information asymmetry in emerging markets. Key Research Themes: Corporate Governance Failures, Financial Transparency, Political Economy of Accounting, Emerging Market Financial Systems Teaching Areas: Advanced Financial Accounting, CFO Leadership, Financial Statement Analysis

• Stochastic Analysis
• Rough Analysis
• Functional Ito Calculus
• +۵ مورد دیگر

Prof. Rama Cont is a Statutory Professor of Mathematics at the University of Oxford and a Professorial Fellow at St Hugh's College . He serves as Director of the Centre for Doctoral Training in Mathematics of Random Systems , Faculty Member of the Stochastic Analysis Group , and Senior Research Fellow at the Institute for New Economic Thinking . Additional roles include Director of the Oxford Martin Programme on Systemic Resilience , Principal Investigator at the Oxford Suzhou Centre for Advanced Research , and Editor-in-Chief of Mathematical Finance . His research interests span pathwise methods in stochastic analysis, rough analysis, functional Ito calculus, mathematical modeling in finance, systemic risk, and data-driven decision systems. Recent publications focus on causal transport, rough volatility, and deep residual networks, reflecting his interdisciplinary approach to mathematics and finance. Functional Ito calculus and pathwise integration Rough volatility and financial market dynamics Systemic risk in financial networks Deep learning applications to finance and stochastic processes He has received prestigious awards including the Louis Bachelier Prize , SIAM Fellowship, Royal Society APEX Award, and IMA Fellowship. His editorial roles and seminar leadership underscore his influence in mathematical finance and stochastic analysis.

Justin Sirignanoمشاهده پروفایل

استاد

• Applied Mathematics
• Machine Learning
• Financial Mathematics
• +۷ مورد دیگر

Justin Sirignano is a Professor of Mathematics at the University of Oxford, affiliated with the Mathematical Institute. His research bridges Applied Mathematics, Machine Learning, and Financial Mathematics, developing novel mathematical frameworks and computational methods. Education: B.A. in Mathematics, Princeton University PhD in Mathematics, Stanford University Chapman Fellow, Imperial College London His research focuses on theoretical and applied aspects of machine learning, particularly in mean-field analysis of neural networks , deep learning for PDEs/SDEs , and scientific machine learning . He has pioneered methods for solving complex financial and scientific problems using data-driven approaches. His recent publications emphasize recurrent neural networks, reinforcement learning, and PDE closure models with applications in turbulence simulation and hypersonic flows. These works span numerical methods, optimization, and stochastic processes. Scientific Awards: 2014 SIAM Financial Mathematics and Engineering Conference Paper Prize Grants & Collaborations: He has secured over $16.5 million in funding from agencies like ONR, NSF-EPSRC, and DoE. His PhD students hold positions at J.P. Morgan, Bank of America, and other institutions. Labs & Teams: He leads research groups in Machine Learning and Mathematical Finance at Oxford, collaborating with institutions like Notre Dame, Boston University, and UIUC.

Yukun Liمشاهده پروفایل

دانشیار

• Finite Element Methods
• Numerical Solutions of Stochastic Differential Equations
• Adaptive Methods
• +۳ مورد دیگر

Yukun Li is an Associate Professor in the Department of Mathematics at the University of Central Florida (UCF), part of the College of Sciences. His research focuses on numerical analysis, stochastic partial differential equations, and computational finance. He holds a Ph.D. in Mathematics from the University of Tennessee, Knoxville (2010-2015), followed by postdoctoral roles at Penn State (2015-2016) and The Ohio State University (2016-2019). He has secured grants including NSF REU funding (2023-2026) and led an NSF-funded project on stochastic phase field models (2021-2025). Research interests include: Continuous/Discontinuous Finite Element Methods Numerical Solutions of Stochastic ODEs/PDEs Adaptive Algorithms and Fast Solvers Computational Finance Models Recent publications emphasize stochastic wave equations, phase field models, and financial mathematics. His work spans theoretical analysis and numerical methods for complex systems. Notable recognition includes the 2015 Achievement Award from the University of Tennessee's Mathematics Department. Teaching highlights include advanced graduate courses like Computational Methods for Financial Mathematics and Numerical Linear Algebra, alongside contributions to undergraduate mathematics education. He is proficient in computational tools including MATLAB, Python, FEniCS, and MPI.

• Financial Engineering
• Stochastic Processes
• Data Analytics
• +۳ مورد دیگر

Richard B. Sowers is a Professor at the University of Illinois at Urbana-Champaign, holding joint appointments in the Department of Industrial and Enterprise Systems Engineering, Mathematics, and Statistics (courtesy). He has held faculty positions since 1996, starting as an Assistant Professor in Mathematics and advancing to Professor across multiple departments. His research spans stochastic processes, financial engineering, and data analytics. He also serves as a Research Principal at the Office of Financial Research since 2012. Education: B.S. in Electrical Engineering (Drexel University, 1986), M.S. and Ph.D. in Applied Mathematics (University of Maryland, 1988 and 1991). Research Interests: Financial networks, stochastic systems, and applications in decision-making and control. His work bridges theoretical probability with practical domains like finance and healthcare. Recent articles focus on machine learning applications in gait analysis for neurological disorders and stochastic modeling in financial systems. Professional Contributions: Taught courses in stochastic calculus, deep learning, and financial mathematics. His research often involves interdisciplinary collaboration, including projects on credit risk, algorithmic trading, and wearable technology for health monitoring. Labs/Teams: Active in the Institute for Predictive and Computational Science, focusing on data-driven solutions for complex systems.

Valentyn Panchenkoمشاهده پروفایل

استاد

• Financial Econometrics
• Time Series Analysis
• Dependence Measures and Copulae
• +۱۱ مورد دیگر

Professor Valentyn Panchenko is a leading academic in Economics at the UNSW Business School, specializing in advanced econometric methodologies and financial modeling. Holding a PhD from the University of Amsterdam and an MPhil from the Tinbergen Institute, his research bridges theoretical econometrics with real-world financial applications, emphasizing big data analysis, network structures, and dependence modeling in economic systems. His expertise spans financial econometrics, time series analysis, non-parametric statistics, and agent-based economic simulations. He focuses on Granger causality, model evaluation, structural economic modeling, and bounded rationality with heterogeneous agents. His work has secured significant grants including ARC Discovery Projects and DECRA fellowships, enabling cutting-edge research on market dynamics and economic interactions. Professor Panchenko's publications appear in top-tier journals like the Journal of Econometric Theory, AEJ: Micro, Journal of Economic Dynamics & Control, and Journal of Banking & Finance. His methodological contributions include novel approaches to copula-based forecasting, nonlinear causality testing, and evolutionary learning models in strategic economic environments. While specific student advising details aren't provided, his research leadership demonstrates sustained impact across econometric theory, financial markets, and experimental economics.

• Asset Management
• Hedge Funds
• Risk Management
• +۲ مورد دیگر

Robert Kosowski is Professor of Finance and Head of the Department of Finance at Imperial College Business School, Imperial College London. He holds a Ph.D. from London School of Economics, M.Sc. in Economics from London School of Economics, and B.A./M.A. in Economics from Trinity College, Cambridge University. His research examines asset management, risk management, machine learning applications in finance, hedge funds, and performance measurement. He has published in top finance journals including Journal of Finance, Journal of Financial Economics, and Review of Financial Studies. Awards include European Finance Association Best Paper Award (2007), four INQUIRE best paper awards, and British Academy Mid-Career Fellowship (2011-2012). Recent publications focus on machine learning in finance, regulatory impacts on funds, and innovative risk management approaches. Articles demonstrate consistent methodological rigor across quantitative finance topics with practical applications for investment management. Professor Kosowski is co-author of 'Principles of Financial Engineering' and directs executive education programs in Risk Management. He has industry experience as Head of Quantitative Research at Unigestion and previously worked at Goldman Sachs and Deutsche Bank.

Christoph Freiمشاهده پروفایل

استاد

• Quantitative Finance
• Risk Management
• Mathematical Economics
• +۴ مورد دیگر

Christoph Frei is a Professor and Chair of the Department of Mathematical and Statistical Sciences at the University of Alberta. He holds a PhD in mathematical finance from ETH Zurich and previously worked as a researcher at École Polytechnique in Paris. His research focuses on quantitative finance, risk management, and mathematical economics, with applications to algorithmic trading, credit risk, and digital currencies. Education: PhD in Mathematical Finance, ETH Zurich Postdoctoral Researcher, École Polytechnique (Paris) Bachelor/Master in Mathematics, ETH Zurich His work bridges academia and industry through collaborations with institutions like ATB Financial, Canadian Western Bank, and the Federal Reserve System. Key research interests include over-the-counter markets, financial regulation, and machine learning applications in risk prediction. Frei has received notable recognition, including the Best Paper in Asset Pricing Award (2019). Current industry partnerships include AI-driven customer risk prediction projects with ATB Financial and credit risk analysis with Canadian Western Bank. He actively contributes to professional organizations like PRMIA Edmonton and advises on financial technology innovation. Research grants come from NSERC, SSHRC, and Mitacs. His consulting roles have spanned risk modeling at UBS and Credit Suisse, emphasizing practical applications of theoretical frameworks.

Lars Augestad Lochstoerمشاهده پروفایل

استاد

• Asset Pricing
• Asset Management
• Quantitative Finance
• +۵ مورد دیگر

Lars Augestad Lochstoer is a Professor of Finance at the UCLA Anderson School of Management, where he teaches Empirical Methods in Finance and Data Analytics and Machine Learning in the Master of Financial Engineering program. He previously held faculty positions at Columbia University and London Business School, and served on the Asset Allocation Advisory Committee for the Norwegian Sovereign Wealth Fund from 2016 to 2022. Dr. Lochstoer earned his Ph.D. in Finance from the University of California, Berkeley's Haas School of Business in 2005, following his Sivilingeniør Business Economics degree from the Norwegian University of Science and Technology in 1999. His research focuses on understanding the economic mechanisms that drive asset prices, including stock market return dynamics, cross-sectional stock returns, exchange rates, and commodity markets. He has made significant contributions to asset pricing literature, particularly in volatility expectations, risk-return tradeoffs, and currency risk. His publication record reveals a strong focus on behavioral aspects of asset pricing, with recurring themes of investor expectations, volatility dynamics, and market anomalies. His work often combines theoretical models with empirical evidence, frequently incorporating quantitative methods and data science approaches. Recent publications show increasing attention to currency risk and multi-horizon risk-return relationships, reflecting evolving market conditions and research interests. EFA Viz Risk Management Prize for best paper in Energy Markets, Securities and Prices (2009) Michigan Ross School of Business Mitsui Finance Symposium Best Discussant Award (2012) UCLA Anderson Excellence in Teaching Award (2017, 2020, 2021) RFS Distinguished Referee Award (2021) As an active member of the academic finance community, Lochstoer serves as an associate editor for the Review of Finance and the Critical Finance Review, having previously served in the same capacity for the Review of Financial Studies. His professional service includes committee roles in major finance associations and extensive reviewing for top finance and economics journals. He has also contributed to practical finance through his service on the Asset Allocation Advisory Committee for the Norwegian Sovereign Wealth Fund.

Paolo Collaمشاهده پروفایل

دانشیار

• Asymmetric Information in Financial Markets
• Corporate Finance
• Market Fragmentation
• +۳ مورد دیگر

Paolo Colla is an Associate Professor of Finance at Bocconi University and serves as Director of the International Economics and Finance B.Sc. Program. His research focuses on asymmetric information in financial markets, corporate financing strategies, and market fragmentation. He has published extensively in leading journals such as the Journal of Finance and Review of Financial Studies. Key topics include price manipulation in FX markets, debt structure dynamics, and the impact of legal frameworks on financial instruments. His work bridges theoretical finance with practical applications, addressing issues like sovereign debt pricing and regulatory policy implications. Teaching responsibilities include courses on financial modeling, derivatives, and institutional finance. His research has explored diverse themes, including the dissemination of short-sellers' information and strategic trading behaviors in fragmented markets. Despite no explicit mention of awards or grants, his prolific publication record underscores his scholarly contributions to corporate finance and financial markets.

Vikram Nandaمشاهده پروفایل

استاد

• Corporate Finance
• Financial Institutions
• Behavioral Finance
• +۵ مورد دیگر

Dr. Vikram Nanda is the O.P. Jindal Distinguished Chair Professor of Finance at the Naveen Jindal School of Management, University of Texas at Dallas. He holds a PhD in Finance from the University of Chicago, MBA from Yale University, and a Bachelor of Technology from Indian Institute of Technology Kanpur. His research focuses on corporate finance, financial institutions, and behavioral finance, with emphasis on topics like hedge fund strategies, managerial overconfidence, and corruption's economic impacts. Key research highlights include studies on multi-market trading (best paper award), litigation risk effects on contracting, and cryptocurrency bubble detection. He has served on editorial boards for Journal of Financial Research and Financial Letters , and contributed to non-academic publications like Barron’s . His work spans 30+ years across top-tier institutions including USC, University of Michigan, and Georgia Tech. Current research explores AI's role in investment management, gender diversity in executive roles, and legal frameworks affecting corporate behavior. Awards include Smith Breeden Prize nominations and Q-Group research grants. Educations: PhD (Chicago), MBA (Yale), B.Tech (IIT Kanpur) Affiliations: Financial Intermediation Research Society, European Finance Association Labs/Teams: Behavioral Finance Research Group, Corporate Governance Initiative He advises on strategic financial decisions and has authored/coauthored over 50 publications. Recent work examines environmental, social, and governance (ESG) investment strategies and the impact of trade secret laws on financial opacity.

Tse-Chun Linمشاهده پروفایل

استاد

• Behavioral Finance
• Empirical Asset Pricing
• Financial Market

Professor Tse-Chun Lin serves as Professor and Head of the Finance Area at HKU Business School, The University of Hong Kong. He joined HKU in 2009 as Assistant Professor, achieving tenure and promotion to Associate Professor in 2015 and full Professor in 2018. His research appears in premier journals including American Economic Review, Journal of Financial Economics, and Review of Financial Studies, with coverage in The Economist, WSJ, and Bloomberg. His academic credentials include: Ph.D. in Economics, University of Amsterdam M.Phil. in Economics, Tinbergen Institute M.B.A., National Chengchi University B.A. in Economics, National Taiwan University Professor Lin's research centers on Behavioral Finance, Empirical Asset Pricing, and Financial Markets. He investigates how cognitive limitations, psychological biases, and information asymmetry influence investor decisions and market dynamics. His work frequently employs large-scale datasets and natural experiments to document phenomena like social media's impact on local information advantages, psychological barriers in cross-firm return predictability, and behavioral drivers of trading anomalies. His methodologies often bridge experimental design with real-world market data to isolate causal relationships. Analysis of his recent publications reveals consistent focus on behavioral mechanisms in financial markets, with increasing emphasis on societal implications (e.g., stock market losses linked to domestic violence) and novel data sources (e.g., social media). His work demonstrates methodological rigor through repeated natural experiments and large-sample analyses, contributing significantly to understanding market inefficiencies and investor psychology. Professor Lin has advised doctoral students including Vesa Pursiainen (co-author on crowdfunding research). As Finance Area Head, he leads academic strategy and curriculum development. His research program reflects sustained funding through HKU appointments and collaborative projects with international scholars.