جستجوی استاد راهنمای دانشگاهی

François-Éric Racicotمشاهده پروفایل

استاد

• Applied Economics
• Econometrics
• Financial Engineering
• +۵ مورد دیگر

François-Éric Racicot is a Full Professor at the Telfer School of Management of the University of Ottawa. He holds a B.Sc. and M.Sc. in Economics from the University of Montreal, and a Ph.D. in Applied Economics/Finance from ESG UQAM. He has over 15 years of teaching experience, specializing in quantitative finance, financial engineering, and econometrics at both undergraduate and graduate levels. His research focuses on hedge fund risk dynamics, macroeconomic shocks, systemic risk, and financial crises. Education: B.Sc. (UdeM), M.Sc. (UdeM), Ph.D. (UQAM) Teaching Roles: Courses in quantitative finance, financial engineering, and applied econometrics at Telfer School of Management Past Experience: Head of MBA in Financial Services and DESS in Finance (2007-2012) at UQO; founder of UQO's M.Sc. in Financial Economics Research Interests: Applied econometrics, derivatives pricing, systemic risk analysis, liquidity risk, and the impact of macroeconomic factors on financial markets. His work integrates advanced statistical methods like nonlinear VAR models and dynamic panel data techniques. Recent Research Trends: Focus on hedge fund risk responses to macroeconomic shocks, illiquidity pricing in asset models, and taxation effects on portfolio diversification. His 2024 studies explore procyclical hedge fund strategies and tax policy implications. Funded Research (2018–2025): Over $90k in grants including SSHRC projects on macroeconomic risk in hedge funds and IPAG Business School fellowships. Affiliations: Member of the GREFA research group at Université de Sherbrooke. Authored five textbooks on computational finance, financial econometrics, and derivatives.

Yongli Wangمشاهده پروفایل

استادیار

• Time-series econometrics
• Forecasting under uncertainty
• Structural breaks
• +۴ مورد دیگر

Yongli Wang is an Assistant Professor (Lecturer) in Economics at the Department of Economics, Birmingham Business School, University of Birmingham, where he also serves as the Admissions Tutor for the Year Abroad Programme. He joined the University of Birmingham in March 2022 after previously holding a lectureship at the University of Essex from October 2019. PhD in Economics, University of Leicester, 2020 MSc Financial Economics, University of Leicester BSc Finance, Wuhan University, China His research is centered on time-series econometrics, with a strong focus on forecasting under uncertainty , structural breaks , and inflation modeling . His work applies advanced econometric techniques to analyze macroeconomic dynamics, particularly in the context of central bank forecasting and global inflation spillovers. Yongli Wang’s recent publications, from 2023 to 2024, prominently feature collaborations with leading econometricians and are published in top journals such as the Journal of International Money and Finance and the Journal of Forecasting . These works examine inflation forecasting performance across major central banks, the use of dynamic factor models, and regional spillover effects, reflecting a cohesive and high-impact research agenda in macroeconomic forecasting. He has no listed scientific awards in the provided text. Yongli Wang has held administrative roles including Deputy Director of Undergraduate Final Projects and Deputy Director of PGT Dissertations at the University of Essex. There is no mention of research grants or advising of students in the text. He does not appear to lead or be part of a named research lab or team based on the available information.

Łukasz Siemieniukمشاهده پروفایل

استادیار

• Chaos Theory in Economics
• Fractal Analysis in Finance
• Academic Entrepreneurship
• +۵ مورد دیگر

Łukasz Siemieniuk is an Assistant Professor at the University of Białystok's Faculty of Economics and Finance, Department of Finance. His research focuses on applying advanced mathematical models to economic and financial systems, particularly chaos theory, fractal analysis, and innovation ecosystems. He investigates how academic business incubators (AIP) drive entrepreneurship, startup financing mechanisms like crowdfunding, and the integration of business intelligence systems with organizational needs. Key areas include financial market analysis using fractal dimensions, IT infrastructure in corporate finance, and policy frameworks supporting innovation. His work bridges theoretical models (e.g., R/S analysis, genetic algorithms) with practical applications in Polish and European economic contexts. Research Interests: Dr. Siemieniuk explores intersections between economic complexity and modern technologies. He examines how chaotic systems theory can improve financial decision-making, evaluates the role of fractal geometry in assessing corporate health, and analyzes the structural properties of academic incubators as catalysts for regional economic growth. His work also addresses cybersecurity in financial systems and the interoperability of advanced technologies with business processes. Recent trends show increasing focus on sustainable innovation ecosystems and digital transformation in enterprise management. Publications reflect a 20-year trajectory from early studies on knowledge management systems to current interdisciplinary analyses of startup ecosystems. He consistently publishes in areas linking quantitative methods (e.g., neural networks, genetic algorithms) with entrepreneurial development and policy analysis. Notable themes include infrastructure determinants of enterprise growth, human capital dynamics in innovation systems, and the ethical dimensions of financial technologies. Lab/Team: His research is conducted through collaboration with the Department of Finance's innovation research group, focusing on applied quantitative methods and policy evaluation. He contributes to academic-business partnerships through Białystok University's innovation initiatives.

Monika Mrázováمشاهده پروفایل

استاد

• International Trade
• Political Economy
• Industrial Organization
• +۴ مورد دیگر

Monika Mrázová is a Professor of Economics at the Institute of Economics and Econometrics, Geneva School of Economics and Management (GSEM), University of Geneva. She is also a Research Affiliate at CEPR and a Research Network Fellow at CESifo. Her academic career includes prior roles as Assistant Professor at the University of Surrey and Postdoctoral Research Fellow at the London School of Economics. She served as a visiting professor (Peter B. Kenen Fellow) at Princeton University from September 2022 to June 2023. Her research centers on International Trade, Political Economy, and Industrial Organization . She investigates topics such as trade agreements, regulatory harmonization, firm heterogeneity, markup dispersion, and the political economy of trade barriers. Her work integrates theoretical modeling with empirical analysis, often using structural methods to estimate trade elasticities and welfare effects. She frequently collaborates with leading economists including J. Peter Neary, Giovanni Maggi, and Céline Carrère. The most recent articles demonstrate a strong trend toward analyzing institutional aspects of trade, such as regulatory cooperation and bureaucratic inefficiencies, while maintaining a rigorous foundation in microeconomic theory and empirical econometrics. Her publications appear in the top journals in economics, including Econometrica , American Economic Review , and Journal of International Economics . Scientific Awards: Kateřina Šmídková Prize (2022) Peter B. Kenen Fellow, Princeton University (2022–2023) Monika Mrázová advises graduate students and contributes to academic mentoring, though specific advisees are not listed. She has secured research funding through affiliations with CEPR and CESifo, and her work is supported by ongoing institutional collaborations. She teaches undergraduate and graduate courses in International Trade at the University of Geneva. She is affiliated with leading research networks and participates in high-level academic conferences and policy discussions. Her lab or research team is not explicitly named, but her collaborative work suggests active involvement in international research groups focused on trade and industrial organization.

Ege Yazganمشاهده پروفایل

استاد

• Applied Econometrics
• Monetary Policy
• International Finance
• +۷ مورد دیگر

Prof. Ege Yazgan is a full Professor of Economics at Istanbul Bilgi University , where he serves in multiple leadership roles including Interim Rector and Director of the Center for Financial Studies (CEFIS). He is affiliated with the Faculty of Business Administration and the Department of Economics. His academic work spans econometrics, macroeconomics, and financial economics, with a strong focus on Turkish economic policy. PhD, University of Sussex (2000) MA, Istanbul University and Boğaziçi University BA, Faculty of Economics, Istanbul University (1991) His research interests include Applied Econometrics , Monetary Policy , International Finance , GDP Nowcasting , and Financial Cycles . He is the founder of simditahmin.com , a real-time Turkish GDP forecasting platform, and frequently uses high-frequency and big data in his models. He has published extensively in journals such as International Journal of Forecasting , Empirical Economics , and Journal of Business Cycle Research . The recent trends in his publications show a growing emphasis on nowcasting using alternative data sources (e.g., online prices, financial transactions), machine learning applications in macroeconomic forecasting, and nonlinear modeling of financial and business cycles in emerging markets, particularly Turkey. Scientific contributions and outreach: Regular commentator on macroeconomic issues in Turkish media (CNBC-e, Bloomberg, NTV, TRT) Organizer of major conferences in macro-finance and econometrics Active participant in policy debates on inflation, external deficits, and financial stability Advising and grants: He has advised multiple researchers and co-authored numerous papers with junior colleagues such as B. Soybilgen and H. Kaya. He has led research projects on forecasting and financial studies, supported through institutional and academic grants, though specific grant names are not listed. He is a member of several research centers including CEFIS, Murat Sertel Center, Rimini Center, and Economic Research Forum. Labs and teams: He leads the Center for Information Finance Research (CEFIS) at Istanbul Bilgi University, which focuses on financial data analysis, econometric modeling, and macroeconomic forecasting. The center organizes workshops and collaborates with international scholars in nonlinear dynamics and econometrics.

David Ruppertمشاهده پروفایل

استاد

• Functional data analysis
• Nonparametric regression
• Statistical machine learning
• +۷ مورد دیگر

David Ruppert is the Andrew Schultz Jr. Professor of Engineering at Cornell University's School of Operations Research and Information Engineering, and Professor of Statistics and Data Science. He holds dual appointments and has been a faculty member since 1987. His education includes a B.A. in Mathematics from Cornell University (1970), M.A. in Mathematics from the University of Vermont (1973), and Ph.D. in Statistics and Probability from Michigan State University (1977). Research Interests: His work spans functional data analysis, astrostatistics, neuroimaging (fMRI/ICA), environmental statistics, and semiparametric regression. He has pioneered methods in measurement error models, splines, and Bayesian statistics. His research has been continuously funded by NSF, NIH, and EPA since 1978. Publications: Over 130 refereed articles and 5 books, including foundational texts like Measurement Error in Nonlinear Models and Statistics and Data Analysis for Financial Engineering . Recent work includes astrostatistical modeling of galaxy spectral energy distributions and neuroimaging analysis. Awards/Honors: Wilcoxon Prize (1986), ASA/IMS Fellowships, Highly Cited Researcher (ISI), and Distinguished Alumni Award (2014). Teaching: Courses include Financial Engineering, Bayesian Statistics, and Functional Data Analysis. He co-developed four graduate/undergraduate courses at Cornell. Service: Editor of Journal of the American Statistical Association , Director of the MPS Program in Data Science and Statistics (DSS). Impact: 29 PhD students trained, many now leading researchers in academia and industry.

Dirk Bergemannمشاهده پروفایل

استاد

• Game theory
• Industrial organization
• Learning and information acquisition in markets
• +۴ مورد دیگر

Dirk Bergemann is the Douglass and Marion Campbell Professor of Economics at Yale University, holding a PhD from the University of Pennsylvania (1994). He serves as Department Chair since 2013 and co-editor of Econometrica . His research focuses on game theory, mechanism design, and information economics. At TUM, he is a Hans Fischer Senior Fellow (since 2014), hosted by the Chair of Decision Science and Systems. Education Vordiplom, Economics, Goethe University Frankfurt (1989) PhD, Economics, University of Pennsylvania (1994) Research Interests Dynamic contracts and learning in markets Auction design and information structures Bayesian persuasion and robust mechanisms Industrial organization and digital markets Key Contributions Bergemann’s work on robust mechanism design ( Econometrica , 2005) and information structures in auctions ( Journal of Economic Theory , 2007) have shaped modern game theory. His recent focus includes algorithmic economics, cloud pricing, and platform regulation. Awards Fellow, Econometric Society (2007) Fellow, European Economic Association (2012) Google Faculty Fellowship (2014–2015) NSF Research Grants (multiple periods) Advising & Grants Supervised numerous PhD students in mechanism design and market economics. Active in NSF-funded research on information economics and digital platforms. Labs/Teams Collaborates with TUM’s Decision Science team on algorithmic decision-making and co-leads Yale’s mechanism design research group.

David S. Leeمشاهده پروفایل

استاد

• Econometrics
• Labor Economics
• Public Policy Analysis
• +۴ مورد دیگر

David S. Lee is a Professor of Economics and Public Affairs at Princeton University, serving as Director of IDEAS for Higher Education. His research focuses on econometric methodologies, labor economics, and public policy analysis, with notable contributions to causal inference techniques like regression discontinuity and kink designs. He has published extensively on topics including minimum wage policy, union impacts on firms, and income inequality. Lee has held affiliations with institutions like UC Berkeley and NBER, and his work has earned prestigious awards such as the Emerald Literati Award and the Journal of Econometrics Aigner Award. Key research areas include developing robust statistical methods for instrumental variable analysis, evaluating policy effects through quasi-experimental designs, and analyzing labor market dynamics. His recent work addresses healthcare resource allocation and machine learning applications in healthcare prediction. Lee's articles frequently bridge theoretical econometric advancements with applied policy questions, emphasizing practical relevance for economic decision-making. Education : Implied academic background based on career trajectory (not explicitly stated in text). Awards : Emerald Literati Award (2018), Aigner Award (2007-2008). Grants/Advising : Active in directing research initiatives like IDEAS for Higher Education, with grant support from NBER and other institutions. He advises on policy-relevant research and collaborates widely, evidenced by co-authored works with economists like David Card and Justin McCrary. His lab focuses on methodological innovations and their application to real-world economic challenges.

• International Monetary Economics
• Foreign Exchange Rate Determination
• Financial Markets Risk
• +۳ مورد دیگر

Casper G. de Vries is a Professor holding the Witteveen Chair of Monetary Economics at the Erasmus School of Economics , Erasmus University Rotterdam. He is affiliated with the Tinbergen Institute and serves on the Scientific Council for the Dutch Government (WRR), advising two Dutch pension funds. His career includes positions at Purdue University, Texas A&M University, and KU Leuven, with visiting roles at institutions like Chapman University. Education: PhD in Economics, Purdue University Postdoctoral positions at Texas A&M University and KU Leuven Research Interests: International monetary policy and exchange rate dynamics Financial risk analysis using extreme value theory Applied game theory in lobbying and auction design Systemic risk in financial systems His work bridges theoretical frameworks with empirical analysis, emphasizing extreme event modeling and policy implications. Articles: Over 50 peer-reviewed publications in top journals (e.g., Journal of Economic Theory , Journal of Econometrics , American Economic Review ). Recent work focuses on systemic risk diversification, internet auction dynamics, and policy-relevant financial stability issues. Scientific Awards: Fellow of the Tinbergen Institute Teaching and Roles: PhD courses on monetary economics at the Tinbergen Institute Former Vice Dean of Research and Education at Erasmus School of Economics Advisor to Dutch socio-economic councils (SER) Labs/Teams: Active in the Erasmus School of Economics' research groups on financial markets and monetary policy.

Elias Tzavalisمشاهده پروفایل

استاد

• Econometrics
• Panel Data Analysis
• Unit Root Testing
• +۵ مورد دیگر

Elias Tzavalis is a Professor of Economics at the Athens University of Economics and Business (AUEB), Department of Economics. He serves as Director of the MSc program in Banking & Finance for Executives. His research focuses on econometric methodology, panel data analysis, structural breaks, and monetary policy. Notable contributions include work on unit root testing in dynamic panels, Bayesian methods for detecting structural breaks, and applications in financial risk management. Education & Roles: Professor at AUEB since 20XX Director of MSc Banking & Finance Executives Program Research Interests: Advanced econometric techniques, nonlinear modeling of economic relationships, macroeconomic policy analysis, and financial market dynamics. He has extensively published in top journals like Journal of Econometrics , Journal of Empirical Finance , and Econometric Reviews . Publications Trends: Recent work emphasizes structural breaks in macroeconomic data, threshold models for policy analysis, and applications of panel unit root tests. Key themes include fiscal sustainability, risk premium effects, and the impact of inflation regimes on monetary policy. Grants & Awards: No specific awards listed, but extensive citation impact in econometrics and finance literature. Advising & Labs: No student advising records provided, but collaborates frequently with researchers on computational econometrics and financial modeling projects.

Ivan Markovskyمشاهده پروفایل

دانشیار

• Structured Low-Rank Approximation
• System Identification
• Data-Driven Control
• +۷ مورد دیگر

Ivan Markovsky is an Associate Professor at the Department of Fundamental Electricity and Instrumentation (ELEC) of the Vrije Universiteit Brussel. He previously held positions at the School of Electronics and Computer Science (ECS) at the University of Southampton. His research focuses on structured low-rank approximation, system identification, and data-driven control, with applications in signal processing and control systems. Education: PhD in Electrical Engineering from Katholieke Universiteit Leuven (2005). Research Interests: Specializes in low-rank approximation methods, system identification, and their applications in control theory and signal processing. Develops numerical optimization algorithms for structured matrices and tensors, with emphasis on practical engineering problems. His work bridges theoretical mathematics and applied control systems engineering. Awards: Received an ERC Starting Grant (2011) for research on structured low-rank approximation. Grants & Projects: ERC Starting Grant (2011-2016) - Structured Low-Rank Approximation FWOAL827 (2017-2020) - Block-oriented nonlinear identification using Volterra series FWOAL758 (2015-2018) - Decoupling multivariate polynomials in nonlinear system identification Labs/Teams: Leads research groups focused on system identification, matrix approximation, and data-driven control methodologies. Collaborates internationally on projects involving tensor approximation and nonlinear system modeling.

• International Economics
• Financial Markets
• Macroeconomics
• +۱۲ مورد دیگر

Bernardina ALGIERI is an Associate Professor in Political Economy at the Department of Economics, Statistics and Finance (DESF), University of Calabria, Italy. She is actively engaged in research and teaching, with a strong focus on international economics, financial markets, environmental and energy economics, and tourism. She teaches International Economics and Financial Markets in graduate programs and contributes to academic outreach through seminar coordination. Her research interests include international competitiveness, commodity price volatility, systemic risk in financial markets, environmental sustainability, and the economic impacts of tourism and renewable energy. She applies advanced econometric techniques to analyze macroeconomic and financial data, particularly in the context of energy and agricultural commodities. The recent publications reflect a consistent trend in analyzing interdependencies between financial markets and real economic activity, with particular emphasis on climate change, carbon emissions, and digital transformation in tourism. Her work spans both theoretical and empirical domains, often employing novel statistical methods such as the Gerber correlation and INGARCH models to assess co-movements and extreme events in markets. Among her scientific contributions, she has published in leading journals such as Energy Economics , Food Policy , Tourism Economics , and Journal of Cleaner Production . Her collaborative research network includes scholars from Italy, Germany, and the UK, reflecting an international approach to economic inquiry. She advises students and participates in institutional activities, including serving as Scientific Coordinator for internal and external seminar series at DESF. She has also been involved in training and career services, acting as an academic tutor for internships. Her research is conducted within the 'Crescita, risorse ed ambiente' research group, which focuses on sustainable growth, environmental policies, and renewable energy systems.

Roberto Duncanمشاهده پروفایل

دانشیار

• International Finance
• Macroeconomics
• Development Economics
• +۷ مورد دیگر

Roberto Duncan is an Associate Professor in the Department of Economics at Ohio University's College of Arts and Sciences. He also serves as the Director of the Master of Arts in Economics program. His research focuses on international finance, macroeconomics, development economics, and applied econometrics, with a strong emphasis on inflation dynamics, monetary policy, and health-economic convergence across countries. Ph.D. in Economics, University of Wisconsin-Madison, 2010 Master of Arts in Economics, University of Chile, 2003 Licentiate in Economics, Pontifical Catholic University of Peru, 2000 His research interests span inflation targeting , fiscal and monetary policy cyclicality , global imbalances , and cross-national convergence in obesity and BMI . He employs advanced econometric techniques to analyze macroeconomic stability and policy effectiveness, particularly in emerging economies. His work often explores how institutional quality influences macroeconomic outcomes and how central banks can improve forecasting accuracy in open economies. The 15 most recent publications reflect a dual focus: one stream on monetary policy frameworks —especially Flexible Average Inflation Targeting and inflation forecasting using NOEM models—and another on long-term health and economic convergence , analyzing BMI and obesity trends across countries. These works combine theoretical modeling with robust empirical analysis, frequently published in journals such as the Journal of Forecasting , Oxford Bulletin of Economics and Statistics , and Economics & Human Biology . Roberto Duncan has not been publicly associated with any scientific awards or honors in the provided texts. He actively teaches both undergraduate and graduate courses in macroeconomics and Latin American economics. As the M.A. Graduate Chair, he plays a key role in program leadership and student mentorship, although specific advisees are not listed. He has contributed to pedagogical research, including the design of teaching models for business cycle theory in developing economies. There is no mention of external grants, but his collaborative research suggests active engagement in academic networks. There is no information about specific labs or research teams led by Roberto Duncan. However, his extensive co-authorship indicates strong collaborative research ties, particularly with economists such as Enrique Martínez-García and Patricia Toledo.

Jochen Jungeilgesمشاهده پروفایل

استاد

• Economic Dynamics
• Applied Econometrics
• Nonlinear Deterministic and Stochastic Dynamic Systems
• +۳ مورد دیگر

Jochen A. Jungeilges is a Professor of Economics at the Department of Economics and Finance, School of Business and Law, University of Agder. He holds academic qualifications including Master's degrees in Economics (University of Bielefeld) and Applied Statistics (Louisiana State University), a PhD in Economics (University of Bielefeld), and a Habilitation from the University of Osnabrück. His research focuses on economic dynamics and applied econometrics, with particular emphasis on nonlinear deterministic and stochastic dynamic systems in micro- and macroeconomics, statistical methodology, and empirical social choice. Recent work explores network analysis applications to financial time series. Publications appear in journals like the Journal of the European Economic Association, Communications in Non-linear Science & Numerical Simulation, and Structural Change and Economic Dynamics. Teaching responsibilities include Financial Econometrics (SE-419), Empirical Finance (SE-510), and Machine Learning with Applications in Finance (SE-507). He has served on appointment boards, participated in international dissertation procedures, and reviewed for journals like the Journal of Economic Behavior & Organization.

Taiji Suzukiمشاهده پروفایل

دانشیار

• Machine Learning
• Statistical Learning Theory
• Deep Learning
• +۶ مورد دیگر

Prof. Taiji Suzuki is an Associate Professor at the University of Tokyo in the Department of Mathematical Informatics . He also serves as Team Leader of the "Deep Learning Theory" team at AIP-RIKEN , Japan. With a PhD in Information Science and Technology from the University of Tokyo (2009), he has held academic positions at the University of Tokyo (2009-2013) and Tokyo Institute of Technology (2013-2017) before returning to the University of Tokyo in 2017. University of Tokyo (2004: BEng in Mathematical Engineering) University of Tokyo (2006: MSc in Information Science and Technology) University of Tokyo (2009: PhD in Information Science and Technology) His research interests span statistical learning theory , deep learning , kernel methods , sparse estimation , and stochastic optimization . He investigates how neural networks adapt to function smoothness, avoid the curse of dimensionality, and achieve global optimization through mean-field dynamics. His work bridges theoretical guarantees (minimax optimality, convergence analysis) with practical implementations (transformers, graph neural networks, diffusion models). The 15 most recent articles focus on transformers' representation power, graph neural networks' limitations, diffusion models' convergence, and optimization theories for deep learning. Key themes include information-theoretic bounds , feature learning dynamics , and mean-field analysis . He explores applications in AI for medicine, federated learning, and biomedical modeling. Awards & Recognition: Outstanding Paper Award, ICLR 2021 MEXT Young Scientists’ Prize Outstanding Achievement Award, Japan Statistical Society 2017 Outstanding Achievement Award, Japan Society for Industrial and Applied Mathematics 2016 Best Paper Award, IBISML 2012 Best Paper Candidate, ICDM 2019 He has served as Area Chair for NeurIPS, ICML, ICLR, AISTATS, and as Program Chair for ACML. His scientific contributions include convergence theories for stochastic gradient methods, minimax analysis of deep learning vs kernel methods, and novel frameworks for distributional optimization in diffusion models.