جستجوی استاد راهنمای دانشگاهی

• International Political Economy
• International Trade
• International Investments
• +۷ مورد دیگر

Prof. Dr. Oktay KIZILKAYA is a full-time Professor at Kirsehir Ahi Evran University, Faculty of Economics and Administrative Sciences, Department of Economics , Turkey. He has held academic positions since 2004, including Associate Professor (2019-2024) and Assistant Professor (2012-2018). Education: PhD and MA in Economics (2007-2012, 2004-2007), BA in Economics (1999-2004) from Selçuk University. Research Areas: International Political Economy, International Trade, International Investments, and International Economic Theories. His research focuses on the interplay between economic policies, foreign direct investment (FDI), energy consumption, environmental sustainability, and growth dynamics. Key themes include panel data analysis , co-integration , and policy implications for Turkey and emerging economies like BRICS-T. Recent publications analyze topics such as pandemic-induced uncertainty on tourism demand, eco-innovation in Germany, and the impact of political institutions on FDI. His work often employs time-series econometrics and panel causality methods . Scientific Awards: Publication Encouragement Award (2023) Publication Encouragement Award (2020) Best Researcher Award (2017, International Conference on Strategic Research in Social Science and Education) Award of 2017 (Strategic Researches Academy) Key Projects: Led 13 research projects on FDI, economic growth, environmental sustainability, and energy policy, all as principal investigator.

Konstantin (Kostia) M. Zuevمشاهده پروفایل

استاد آموزشی

• Network Science
• Applied Probability
• Computational Statistics
• +۴ مورد دیگر

Dr. Konstantin (Kostia) M. Zuev serves as Teaching Professor in the Computing + Mathematical Sciences Department at California Institute of Technology , where he has made significant contributions to network science and computational statistics since 2016. His dual PhDs in Mathematics (Moscow State University, 2008) and Civil Engineering (HKUST, 2009) underpin his interdisciplinary research spanning differential geometry, stochastic simulation, and network dynamics. Education PhD in Mathematics, Lomonosov Moscow State University (2008) PhD in Civil Engineering, Hong Kong University of Science & Technology (2009) His research focuses on network science , particularly course-prerequisite networks and complex financial systems , with recent work extending to network navigability in cosmological models and rare event simulation. Over his career, he has developed innovative Bayesian inference methods and geometric preferential attachment theories while maintaining active collaborations across mathematics, physics, and biomedical domains. Recent publications highlight network analysis in education ( 2023 ), hyperbolic graph theory ( 2024 ), and pandemic-informed cancer mortality studies ( 2023 ). His 15 most recent articles demonstrate methodological innovations across disciplines including statistics, physics, finance, and cosmology. Scientific recognition includes Humboldt Research Fellowship (2021) Carver Mead Seed Fund Grant (2023) ASCIT Teaching Award (2018, 2023) Northrop Grumman Teaching Excellence Prize (2019) As Graduate Option Representative for Information and Data Sciences at Caltech and faculty advisor for multiple student organizations including the Caltech Karate Club and Caltech Chess Club , he actively bridges academic rigor with community engagement through outreach initiatives like the virtual math education channel and university math circles for K-12 students.

Jiti Gaoمشاهده پروفایل

استاد

• Econometrics
• Non- and Semi-Parametric Econometrics
• Time-Series Analysis
• +۳ مورد دیگر

Professor Jiti Gao is a Donald Cochrane Chair in Econometrics & Business Statistics at Monash University's Faculty of Business and Economics. He leads the Department of Econometrics and Business Statistics, specializing in non- and semi-parametric econometrics, time-series analysis, and panel data methodologies. His research focuses on developing statistical models for climate change, energy demand, and financial forecasting. Affiliations: Monash University, Impact Labs Grants: Multiple ARC Discovery Projects (e.g., 2020–2025 on climate-energy time series, 2017–2020 on econometric model building) Collaborations: CSIRO, Yale University, and international partners from China, Norway, and Singapore Research interests include climate econometrics, financial time series, and policy evaluation. Over 136 publications span econometric theory and applications, with recent work on nonlinear trending models and quantile regression. His grants emphasize methodological advancements in time series and panel data analysis. Awards: Not explicitly mentioned, but recognition includes Australian Professorial Fellow status and international research leadership roles. Advising/Grants: Primary Investigator on multiple ARC-funded projects, focusing on climate modeling and financial econometrics Labs/Teams: Part of Monash's Impact Labs and collaborates with global institutions on climate and econometric initiatives

Martin Solbergerمشاهده پروفایل

دانشیار

• Time Series Econometrics
• Macroeconomic Forecasting
• Latent Time Series Estimation
• +۳ مورد دیگر

Martin Solberger is an Associate Professor in the Department of Statistics at Uppsala University, where he received his PhD in statistics in 2013 and was promoted to associate professor in 2022. His office is located at Ekonomikum (3rd floor), Kyrkogårdsgatan 10, with postal address Box 513, 751 20 UPPSALA. Dr. Solberger specializes in time series econometrics with particular expertise in macroeconomic forecasting and estimation of latent time series variables including potential GDP and the neutral interest rate. His research demonstrates sophisticated methodological approaches to dynamic factor models, unit root testing, and interest rate analysis, frequently employing Kalman filtering techniques and Bayesian VAR modeling. His publication record reveals a strong focus on Scandinavian economic analysis, particularly examining the natural rate of interest and neutral interest rate dynamics within Swedish and broader Nordic contexts. Recent work shows increasing attention to international spillover effects on domestic monetary policy variables and methodological refinements in panel data econometrics. Through extensive collaboration with researchers including Spånberg, Armelius, and Österholm, Solberger has established himself as a significant contributor to modern time series econometrics methodology and its application to central banking and fiscal policy questions.

Francisco Barillas Bedoyaمشاهده پروفایل

دانشیار

• Asset Pricing
• Portfolio Choice
• Macrofinance
• +۴ مورد دیگر

Francisco Barillas Bedoya is an Associate Professor at the School of Banking and Finance within the UNSW Business School, University of New South Wales. His research focuses on theoretical and empirical asset pricing, particularly portfolio choice, asset pricing tests, macrofinance, and term structure of interest rates. He has published extensively in top-tier journals like the Journal of Finance and Management Science. PhD from New York University MA from University of British Columbia BSc from Trent University His recent publications analyze Sharpe ratios for model comparison, speculative behavior in bond markets, and risk premia in fixed income markets. While no formal awards are listed, his work intersects financial economics, econometrics, and computational methods. Office: Level 3, Room 333C, Ref E12 Email: f.barillas@unsw.edu.au

Donald Robertsonمشاهده پروفایل

استاد

• Econometrics
• Applied Macroeconomics
• Financial Economics
• +۳ مورد دیگر

Professor Donald Robertson is a faculty member at the University of Cambridge , holding the position of Professor of Economics and Director of Graduate Studies and PhD Programme within the Faculty of Economics . He is affiliated with Pembroke College and contributes to econometric research and graduate education. Research Interests : His work focuses on Econometrics , Applied Macroeconomics , and Financial Economics , with methodological expertise in Time Series Analysis , Panel Data Analysis , and Predictive Modeling . His publications address topics like cross-sectional dependence, unit root testing, and instrumental variable estimation. Teaching : He instructs modules such as Introduction to Probability and Statistics , Time Series Methods , and MPhil Prep Course - Statistics . Publications : Recent contributions include work on R² bounds for predictive models, factor residuals in panel data, and fiscal fatigue in debt ratios, reflecting his focus on econometric theory and macroeconomic applications. Contact : Email dr10011@cam.ac.uk or phone +44(0)1223 335270. Office hours by email appointment in Room 70.

• Econometrics
• Applied Econometrics
• Financial Econometrics
• +۶ مورد دیگر

Professor Yongcheol Shin is a faculty member in the Department of Economics at the University of York. His academic background includes a BA (Hanyang University), MA (Hanyang University), and PhD (Michigan State University). He specializes in applied and theoretical econometrics, focusing on financial and macroeconomic modeling. Education: BA (Hanyang University), MA (Hanyang University), PhD (Michigan State University) His research spans econometric theory and applications in finance and macroeconomics. Key areas include nonlinear panel data modeling, cointegrating VAR models, regime-switching models, and statistical hypothesis testing for time series. Recent work addresses interactive effects in panel data and multilevel factor models. Recent publications (2023) focus on panel data analysis, canonical correlation, and unit root testing. These studies reflect his expertise in econometric methodology and its application to financial economics, macroeconomics, and trade dynamics. Scientific awards include: 2018 Maekyung-KAEA Economist Award He leads the ESRC-funded project 'New Cross-Sectionally Dependent Panel Data Methods for the Analysis of Macroeconomic and Financial Networks' (2020-2024), collaborating with researchers like J. Chen and W. Wang.

Derek G. Brewinمشاهده پروفایل

استاد

• Grain markets and trade
• Firm location choices and innovation
• Farm finance and production economics
• +۷ مورد دیگر

Dr. Derek G. Brewin is a Professor and Head of the Department of Agribusiness and Agricultural Economics at the University of Manitoba, within the Faculty of Agricultural and Food Sciences. He holds a PhD in Agricultural, Environmental and Regional Economics from Pennsylvania State University. Education: PhD, Agricultural, Environmental and Regional Economics, Pennsylvania State University, USA MSc, Agricultural Economics, University of Saskatchewan, Canada BSc, Agricultural Economics, University of Alberta, Canada Dr. Brewin's research focuses on spatial grain and oilseed markets, innovation in food processing and plant breeding, farm finance, and red meat supply chains. With 14 years of industry experience prior to his academic career, including roles as a lender and analyst in the agriculture sector, his work bridges practical industry knowledge with academic rigor. His current research projects examine the economics of crop rotations, grain transportation policy, plant location for oilseed processing, and the economics of perennial grains and forages with beef integration. His scholarly work shows a consistent focus on agricultural markets, transportation economics, and innovation policy, with a particular emphasis on Canadian agricultural systems. Recent publications analyze the impact of trade disruptions, pandemic effects on grain markets, and innovation policy in crop breeding. Scientific Awards and Recognition: Award-winning teacher of agricultural finance, marketing and risk management Past President of the Canadian Agricultural Economics Society Member and on Editorial Board of Northeast Agricultural and Resource Economics Association (NAREA) Member of the Structure and Performance of Agriculture and Agri-products Network Member of the Canadian Agricultural Innovation and Regulation Network Dr. Brewin has supervised numerous graduate students, with current students working on topics related to winter forage options, crop rotation profit impacts, and processing location impacts on farm prices. His professional service includes serving as a Senator at the University of Manitoba and as a director of Farm Management Canada and the Manitoba Rural Adaptation Council. Prior to his academic career, Dr. Brewin worked as a Corporate Advisor for the Canadian Wheat Board, a Policy Economist for Agriculture and Agri-Food Canada, and a farm lender. He was raised on a mixed irrigation farm in Purple Springs, Alberta, providing him with firsthand agricultural experience that informs his research and teaching.

• Econometrics
• Panel Data Econometrics
• Structural Breaks
• +۳ مورد دیگر

Joakim Westerlund is a Professor in the Department of Economics at Lund University's School of Economics and Management. With over 134 research outputs and 33 academic activities, his work focuses on econometrics, particularly panel data analysis, structural breaks, and estimation theory. He has contributed to the development of econometric methods for the New Keynesian Phillips Curve and common correlated effects models. Active Wallenberg Academy Fellowship (2019-2028) Supervised 11 doctoral theses and bachelor/master projects Peer-review panel member and journal editor His research aligns with UN Sustainable Development Goals in Economics and Econometrics, with significant contributions to panel unit root testing, interactive effects models, and Stata-based econometric methods. Westerlund received the prestigious Journal of Applied Econometrics Distinguished Author award in 2018. Current PhD supervisees include Christina Maschmann (2023-2028), Tilman Bretschneider (2023-2028), Pelle Almgren (2022-2027), and Shayan Meskinimood (2021-2026).

• Time Series Analysis
• Econometric Theory
• Functional Data Analysis
• +۳ مورد دیگر

Dr Won-Ki Seo is a Senior Lecturer in the School of Economics at the University of Sydney. His research focuses on time series analysis, econometric theory, and functional data analysis. He holds a Ph.D. in Economics from the University of California, San Diego. Research Interests: Dr Seo's work centers on cointegration analysis in functional spaces, Hilbertian processes, and the application of advanced mathematical frameworks to econometric problems. His recent studies explore tail behavior of Lévy processes, functional principal component analysis, and nonlinear time series modeling. Recent work includes analyzing stopped Lévy processes with Markov modulation and developing methodologies for functional time series inference Key contributions to cointegration theory in Banach spaces and functional data econometrics Dr Seo has published extensively in top journals like Econometric Theory and Journal of Time Series Analysis . His research bridges theoretical econometrics and practical applications in financial and environmental economics. Contact: won-ki.seo@sydney.edu.au | Office: A02 Social Sciences Building

• Finance
• Financial Economics
• Quantitative Finance
• +۳ مورد دیگر

Ke Xu is an Assistant Professor at the Department of Finance, Faculty of Business and Economics, University of Victoria. His research bridges finance, econometrics, and cryptocurrency, focusing on market microstructure, high-frequency trading, and price discovery mechanisms. He has extensively studied Bitcoin ETFs, fractional cointegration models, and machine learning applications in financial markets. Key Research Areas: Market Microstructure High-Frequency Trading Cryptocurrency Dynamics Price Discovery Machine Learning in Finance Financial Econometrics Article Trends: Xu’s work spans empirical analyses of Bitcoin ETFs, volatility modeling (e.g., affine GARCH), and algorithmic trading strategies. His recent papers explore mini flash crashes using machine learning, regulatory impacts on market quality, and sustainable crypto portfolios.

Melanie Schienleمشاهده پروفایل

استاد

• Econometrics
• Statistical Methods
• Financial Risk Analysis
• +۴ مورد دیگر

Prof. Melanie Schienle is a Professor and Chair of Statistical Methods and Econometrics at the Department of Economics and Management, Karlsruhe Institute of Technology (KIT). She also holds a professorship in the Department of Mathematics at KIT since 2021. Her expertise spans statistical methods, econometrics, financial risk analysis, and forecasting. She leads the HKMetrics Network and the RespiNow Hub for respiratory disease forecasting. She serves as a Senior Fellow at the Rimini Center for Economic Analysis (RCEA), a steering committee member of the German Economic Association, and a member of the University Research Council at KIT. Education: Ph.D. (Dr. rer. pol.) in Economics from Mannheim University (2008), summa cum laude; Diploma in Mathematics (University of Karlsruhe, 2003) with a minor in theoretical physics. She has held academic positions at Leibniz University Hannover (2012–2015) and Humboldt University of Berlin (2008–2012). Research interests focus on financial networks, systemic risk, time series analysis, and machine learning applications in economics. She co-leads projects on nowcasting and forecasting, including collaborative efforts during the pandemic to predict hospitalizations. Her work integrates advanced statistical techniques with real-world policy implications. Prof. Schienle is an Associate Editor for the International Journal of Forecasting and Journal of Time Series Analysis . She has authored over 50 peer-reviewed publications and contributed to high-impact journals like Nature Communications and Journal of Business & Economic Statistics . She leads the Institute of Statistics at KIT and chairs the MathSEE initiative for interdisciplinary mathematical applications.

• Financial Economics
• Macroeconomics
• International Finance
• +۶ مورد دیگر

Mehmed Ganić is a Full Professor of Economics at the International University of Sarajevo, specializing in Macro-Finance Theory, Applied Econometrics, and Financial Economics. With over 14 years of academic experience and 11 years in the finance industry, his research focuses on extending growth-finance models and analyzing financial markets in Eastern and Central Europe. He has authored four books and numerous articles on topics like FDI, financial stability, and EU integration. His research interests include the regulatory frameworks of securities markets, mutual funds enforcement, and digitalization impacts on economies. He has conducted extensive empirical analyses on cross-country comparisons in Southeast Europe, Balkan economies, and the effects of institutional quality on economic hypotheses. Ganić's publications explore critical themes such as the digitalization-growth nexus in Muslim-majority regions, the role of financial inclusion in reducing income inequality, and the implications of regional trade integration on capital mobility. His work frequently employs advanced econometric techniques like panel cointegration and ARDL bounds testing to analyze policy impacts. He has contributed to understanding post-transition economies' financial integration dynamics and authored studies on banking sector efficiency in Bosnia and Herzegovina. His research highlights challenges in implementing Basel principles and regulatory frameworks in emerging markets.

Mawuli Kouami Segnonمشاهده پروفایل

پژوهشگر

• Econometrics
• Time Series Analysis
• Financial Forecasting
• +۵ مورد دیگر

Dr. Mawuli Kouami Segnon is a researcher at the Chair of Empirical Economics, School of Business and Economics, University of Münster. His work focuses on econometric modeling, financial time series analysis, and volatility forecasting across various domains including cryptocurrencies, energy markets, and macroeconomic indicators. Research interests include: Development of advanced volatility models (GARCH, multifractal, regime-switching) Applications to financial markets, energy economics, and macroeconomic policy High-frequency data analysis and mixed-frequency forecasting Count data modeling with conditional heteroscedasticity Portfolio risk management using copula and multifractal approaches Recent publications demonstrate expertise in: Geopolitical risk impacts on stock volatility Comparative analysis of realized variance measures Inflation uncertainty modeling in G7 countries Electricity price volatility in Australian markets Bitcoin market forecasting Historical economic data analysis Current projects (since 2020) involve: Innovative economic/financial time series forecasting Financial market volatility modeling Applications of multifractal structures in econometrics

Qiwei Yaoمشاهده پروفایل

استاد

• Statistical Inference
• Time Series Analysis
• High-Dimensional Statistics
• +۶ مورد دیگر

Qiwei Yao is a Professor of Statistics at the Department of Statistics, London School of Economics (LSE), where he maintains an active research program in statistical methodology and applications. His office is located in Columbia House, Room 7.16 at LSE's Houghton Street campus in London. Professor Yao's research focuses on statistical inference for complex time series, with particular expertise in high-dimensional time series, dynamic networks, spatio-temporal processes, functional time series, nonlinear time series, and high-frequency data. His work bridges theoretical statistics with practical applications, especially in financial econometrics. He has developed innovative methodologies for dimension reduction, factor modeling, and network analysis that have become influential in the field. His recent publications reveal a strong trend toward developing statistical methods for increasingly complex data structures, particularly focusing on high-dimensional and network-based time series. His work integrates machine learning techniques with traditional statistical approaches, as evidenced by papers on deep learning for Markov property testing and tensor decompositions for matrix time series. There's also a clear emphasis on privacy-preserving methods and differential privacy in network analysis. Professor Yao has secured substantial research funding through multiple EPSRC Programme Grants and Research Projects, including the EPSRC Programme Grant for 'Statistical Foundations for Detecting Anomalous Structure in Stream Settings (DASS)' and 'Network Stochastic Processes and Time Series (NeST)'. He also leads the EPSRC Research Project on 'Statistical Network Analysis: Model Selection, Differential Privacy, and Dynamic Structures' and has collaborated with industry partners like Andurand Capital Management on projects such as 'Forecasting Oil Prices Based on Quantitative Methods'. His research has significant applications across various domains, particularly in energy forecasting (electricity load prediction), financial modeling (volatility modeling, oil price forecasting), and ecological modeling (spatio-temporal population dynamics). Professor Yao maintains strong collaborative relationships with researchers across multiple institutions and disciplines.