جست‌وجوی استاد و پژوهشگر

Tatevik Sekhposyanمشاهده پروفایل

دانشیار

• Macroeconomics
• Econometrics
• Forecasting
• +۳ مورد دیگر

Tatevik Sekhposyan is an Associate Professor in the Department of Economics at Texas A&M University, specializing in applied macroeconomics, time series econometrics, and forecasting. Her research focuses on monetary policy shocks, uncertainty, and model evaluation. She holds roles as President of the Society for Nonlinear Dynamics and Econometrics, a Board Member of the Armenian Economic Association, and a Research Fellow of the CEPR. She earned her PhD from the University of North Carolina at Chapel Hill and has served on editorial boards of major journals. Her work explores macroeconomic uncertainty indices and the implications of shocks, with notable contributions to forecasting frameworks and policy communication. During 2024-2025, she is on sabbatical at Princeton University. Her educational background includes a focus on econometric methods and macroeconomic theory. Research interests include the identification of monetary policy effects, temporal aggregation impacts, and predictive density evaluations. Awards include the International Journal of Forecasting's Outstanding Paper Award (2014). She teaches courses on economic forecasting and time series analysis, and collaborates with Amazon's Supply Chain Optimization Technologies (SCOT) team on inventory prediction challenges. Key contributions include developing uncertainty indices for the Euro Area and analyzing electricity demand as an economic indicator. Her work bridges academic research with practical applications, emphasizing the role of uncertainty in economic decision-making.

Keon-Hyung Leeمشاهده پروفایل

استاد

• Health Services Administration
• Health Finance
• Health Policy Analysis
• +۳ مورد دیگر

Dr. Keon-Hyung Lee is a Professor and Arnold L. & Priscilla Moss Greenfield Endowed Professor at Florida State University's Askew School of Public Administration and Policy. His academic work spans public administration and health services administration, focusing on behavioral factors in healthcare systems and public sector dynamics. Ph.D. in Public Administration, Health Policy and Management, University of Southern California (2002) M.S. in Engineering-Economic Systems, Stanford University (1995) M.P.H. in Public Health, Yale University (1992) B.B.A. in Business Administration, Ohio University (1990) Dr. Lee's research examines Organizational behavior in healthcare systems Factors influencing public servants' attitudes State/local government program adoption Healthcare finance and policy analysis His recent publications show expanding focus on Health insurance enrollment dynamics Community benefit provisions Patient engagement in performance VA hospital efficiency Nonprofit sustainability Medicaid policy interactions Scientific awards include Korean Public Officials Overseas Training Program ($270,000) Strengthening Social Security Measurements ($10,000) U.S. DOD Hospital Efficiency Research ($8,000) NSF-funded VIFI Infrastructure Project ($100,000) Comparative OECD Healthcare Research ($180,000) Executive Agencies Assessment ($30,000) Dr. Lee teaches graduate courses in healthcare finance, policy analysis, and public administration while maintaining active research collaborations with institutions in South Korea and U.S. healthcare organizations.

• Financial Economics
• Systemic Risk
• Banking and Financial Regulation
• +۷ مورد دیگر

Viral V. Acharya is a Professor of Finance and the C.V. Starr Professor of Economics at New York University's Leonard N. Stern School of Business. He is affiliated with several leading research institutions, including the Centre for Economic Policy Research (CEPR), the European Corporate Governance Institute (ECGI), and the National Bureau of Economic Research (NBER). His research spans critical areas in financial economics, with a focus on systemic risk, financial regulation, banking stability, corporate governance, liquidity risk, sovereign debt, and the implications of unconventional monetary policy. His work frequently addresses real-world financial crises and regulatory challenges. The trends in his scholarly output reveal a consistent emphasis on understanding the interconnectedness between financial institutions and broader economic stability. His publications explore topics such as credit derivatives, shadow banking, securitization, market freezes, and climate-related financial risks, often combining theoretical models with empirical analysis to inform policy. Notable contributions include seminal papers on measuring systemic risk, the design of prudential regulation, the role of liquidity in asset pricing, and the real effects of sovereign debt crises. His recent work continues to address pressing issues such as banking stress in 2023 and the rise of shadow banking in China.

• Calculus of Variations
• Partial Differential Equations
• Nonlinear Elasticity
• +۴ مورد دیگر

Peter Hornung is a Professor at the Faculty of Mathematics , TU Dresden . His research lies at the intersection of Calculus of Variations , Partial Differential Equations , and Nonlinear Elasticity , with a focus on mathematical modeling of thin elastic structures, isometric immersions, and homogenization. Current Role : Professorship for Partial Differential Equations, TU Dresden Organized Workshops : Calculus of Variations and PDE Day (2019), Applied Analysis Day (2018) His work explores the geometric and analytical properties of elastic sheets and shells , including stability analysis, singularities in deformations, and stochastic homogenization. Publications span journals like J. Elasticity , SIAM J. Math. Anal. , and Calc. Var. Partial Differential Equations . Hornung collaborates with researchers such as L. Freddi , M. G. Mora , R. Paroni , and R. Moser . For inquiries, contact his secretary: Esther Parisius-Liebstein at esther.parisius-liebstein@tu-dresden.de .

Sima Siami-Naminiمشاهده پروفایل

مدرس

• macroeconomics
• monetary policy
• time series analysis
• +۵ مورد دیگر

Sima Siami-Namini serves as a Lecturer at Johns Hopkins University, teaching in the MS in Applied Economics program with extensive experience in undergraduate and graduate instruction across economics, statistics, and finance disciplines. Her academic credentials include advanced interdisciplinary training: PhD in Applied Economics (minor: Statistics), Texas Tech University, 2020 Master's in Statistics, Texas Tech University, 2022 Master's in Artificial Intelligence (Machine Learning focus), University of North Texas, 2023 Her research program integrates macroeconomic theory with cutting-edge computational methods, specializing in monetary policy analysis, time series econometrics, and AI-driven forecasting. She bridges traditional economic modeling with machine learning applications, particularly in anomaly detection, data visualization, and large language model implementations for economic forecasting. Analysis of her publication trajectory (2020-2024) reveals three dominant research streams: (1) deep learning architectures (LSTM, TCN) for time series forecasting and anomaly detection, (2) monetary policy impacts on income inequality using FAVAR/SVECM models, and (3) natural language processing applications for Federal Reserve communication analysis. Her recent work increasingly incorporates large language models for domain-specific economic analysis and code generation. No documented scientific awards or major honors appear in the available records. She mentors students in the Applied Economics program with emphasis on quantitative research methods, though specific grant funding details remain undisclosed. Her teaching methodology incorporates experiential learning techniques adapted from digital forensics education frameworks. No dedicated research laboratories or institutional teams are referenced in the source materials.

Rubayat Chowdhuryمشاهده پروفایل

مدرس

• Macroeconomics
• Applied Econometrics
• Monetary Policy
• +۵ مورد دیگر

Rubayat Chowdhury is a macroeconomist with affiliations at both the Centre for Applied Macroeconomic Analysis (CAMA) and the Development Policy Centre within the Crawford School of Public Policy at the Australian National University (ANU). Holding a PhD in Economics from ANU (2025-), he also earned a Master's (2014) and Graduate Diploma (2013) in Economics from ANU, along with a BSS in Economics from the University of Dhaka (2007). Education PhD in Economics (ANU) 2025- Master’s in Economics (ANU) 2014 Graduate Diploma in Economics (ANU) 2013 BSS in Economics (University of Dhaka) 2007 His research focuses on macroeconomic dynamics in emerging markets , particularly examining commodity shocks, business cycles, and exchange rate mechanisms in the Pacific region. Using advanced econometric techniques like SVAR and GVAR, his work addresses critical policy questions around resource dependence and economic resilience. Recent publications demonstrate expertise in structural econometric modeling and policy evaluation, with a geographic emphasis on Papua New Guinea and Bangladesh. Key themes include monetary policy effectiveness, financial market linkages, and economic development challenges in resource-dependent economies. Scientific Awards Helen Hughes Prize (2013, 2014) Australia Awards Scholarship (2013-2014) ODI Fellowship (2017-2019) Greg Taylor Scholarship (2020-2021) Australian Government Research Training Program (AGRTP) Scholarship (2020-2024) As a part-time lecturer at ANU, he has taught courses in Graduate Preparatory Macroeconomics (IDEC 7903), Open Economy Macroeconomics (IDEC 8008), Microeconomics (ECON 1101), Business Economics (ECON 8069), and Health Economics (ECON3004/6039). His career spans multiple central bank roles in Bangladesh and Papua New Guinea, complemented by World Bank consultancy experience.

Deniz Baglanمشاهده پروفایل

دانشیار

• Econometrics
• Nonparametric Econometrics
• Semiparametric Models
• +۴ مورد دیگر

Deniz Baglan is an Associate Professor of Economics and serves as the Director of Undergraduate Studies in the Department of Economics at Howard University, which is part of the College of Arts and Sciences. He holds a Ph.D. in Economics from the University of California, Riverside, and contributes significantly to econometric theory and its applications in macroeconomics and finance. Research Interests: His primary research lies in nonparametric and semiparametric econometric methods, particularly applied to panel data models. He investigates issues related to unobserved heterogeneity, dynamic modeling, and structural inference in economic and financial contexts. His work spans both theoretical developments and empirical applications, focusing on macroeconomic dynamics and empirical finance. Publication Trends: His recent scholarly output shows a consistent focus on advancing nonparametric techniques for panel data, including identification, estimation, and testing in models with fixed effects, time-varying parameters, and nonlinear structures. These contributions are published in notable journals such as Journal of Macroeconomics and Studies in Nonlinear Dynamics and Econometrics , reflecting a strong trajectory in methodological econometrics. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: While specific students and grant details are not listed, his role as Director of Undergraduate Studies suggests active involvement in academic mentoring and curriculum development. As a faculty member publishing in top-tier econometrics journals, he likely contributes to research supervision at graduate levels and may participate in externally funded research projects. Labs and Research Teams: There is no mention of specific labs, research centers, or collaborative teams in the provided information.

Abolfazl Safikhaniمشاهده پروفایل

استادیار

• Network Modeling
• High-Dimensional Statistics
• Spatiotemporal Models
• +۵ مورد دیگر

Abolfazl Safikhani is an Assistant Professor in the Department of Statistics at George Mason University. He holds a PhD in Statistics and Probability from Michigan State University and has held prior positions at Columbia University and the University of Florida. His research focuses on network modeling, high-dimensional statistics, spatiotemporal models, and applications in urban planning, neuroscience, and smart cities. He is an Associate Editor for Technometrics , Statistica Sinica , and Data Science in Science . He has contributed to advancements in statistical methodologies for time series analysis, including change point detection, transfer learning, and spatiotemporal modeling. His work bridges theoretical statistics with practical applications in urban growth prediction, healthcare (e.g., cancer drug response modeling), and transportation systems. Recent research trends include leveraging explainable AI for land use modeling, longitudinal omics data analysis, and structural break detection in high-dimensional systems. His publications span theoretical developments and real-world case studies, such as subway ridership during the pandemic and New York City’s taxi demand dynamics. Despite no listed awards, his editorial roles highlight his influence in statistical science. He actively mentors students and collaborates on interdisciplinary projects, emphasizing data-driven solutions for complex societal challenges.

Anindya Royمشاهده پروفایل

استاد

• Time Series Analysis
• Nonparametric Bayesian Analysis
• High-dimensional Estimation and Inference
• +۳ مورد دیگر

Anindya Roy is a Professor of Statistics in the Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC). His research focuses on time series analysis, Bayesian methods, high-dimensional statistics, and applications in biomedical and engineering domains. He serves as an Area Editor for Statistical Analysis and Data Mining , and on editorial boards for Sankhya, Ser. A and Statistics in Medicine . His research interests include nonparametric Bayesian approaches, geometric constraints in statistical models, and sequential experimental design. He has received research funding from the National Science Foundation (NSF DMS–2210282). Recent work addresses privacy-preserving data synthesis, causal inference in time series networks, and fetal growth modeling. Key contributions include methodologies for high-dimensional time series with directed acyclic graphs, Bayesian approaches for relational graph estimation, and statistical techniques for medical applications such as cyclotron ion source development and cervical cancer screening risk prediction. Notable collaborative efforts involve proteomic analysis of chemical mixtures, oncology trial design, and biomarker studies. His work bridges theoretical statistics with applied problems in health sciences and engineering, emphasizing interdisciplinary impact.

• Econometrics
• Macroeconomic Modeling
• Time Series Analysis
• +۳ مورد دیگر

Prof. Aleksander Welfe is a full professor and head of the Department of Econometric Models and Forecasts at the Faculty of Economic Sciences and Sociology, University of Łódź. He has held academic positions including Adjunct Professor at Warsaw School of Economics for over two decades. His primary role involves leading research in macroeconomic modeling and econometric time series analysis. Education & Affiliations : He holds a habilitation (doctorate) in econometrics and has collaborated internationally, notably with Nobel laureate Lawrence R. Klein. He is the founder and editor-in-chief of the Central European Journal of Economic Modelling and Econometrics . Research Focus : Specializes in macroeconomic modeling, time series analysis, non-stationary stochastic processes, and cointegration. His work emphasizes practical applications like Poland’s national economy models (WM-1), inflation dynamics, and energy price formation. He has pioneered structural break analysis in econometric models and developed methodologies for simulating economic policy scenarios. Awards : Elected Full Member of the Polish Academy of Sciences for contributions to macroeconometric modeling, particularly Poland’s macroeconomic models used in policy analysis. Grants & Labs : Leads research teams focused on economic forecasting and structural modeling. His department operates Poland’s primary macroeconomic modeling laboratory, producing influential policy reports and academic publications. Teaching : Teaches advanced econometrics and macroeconomic modeling at both University of Łódź and Warsaw School of Economics, mentoring multiple generations of economists.

Tatevik Sekhposyanمشاهده پروفایل

دانشیار

• Applied Macroeconomics
• Time Series Analysis
• Econometrics
• +۶ مورد دیگر

Tatevik Sekhposyan is an Associate Professor in the Department of Economics at Texas A&M University. She is also a Research Fellow at the Centre for Economic Policy Research and has held leadership roles, including former president of the Society for Nonlinear Dynamics and Econometrics and newly elected president of the Armenian Economic Association. Her research spans applied macroeconomics, time series analysis, and predictive density evaluations, with a focus on macroeconomic shocks and uncertainty. PhD in Economics, University of North Carolina at Chapel Hill Former economist at the Bank of Canada Her work combines classical and Bayesian econometric techniques to address model selection, forecast evaluation, and nonlinear dynamics. She has developed uncertainty indices and tools for real-time economic monitoring, notably through electricity demand analysis during the pandemic. Her methodological contributions include Markov switching rationality tests and fixed-horizon density forecasting. Key scientific awards include the International Journal of Forecasting's Outstanding Paper Award (2014) Tatevik applies her research to corporate settings as an Amazon Scholar, bridging academic insights with inventory management and supply chain optimization. She mentors junior economists and emphasizes the importance of role models in economics education.

Scott Joslinمشاهده پروفایل

دانشیار

• Asset Pricing
• Macro-Finance
• Fixed Income Markets
• +۳ مورد دیگر

Scott Joslin is an Associate Professor of Finance and Business Economics at the University of Southern California's Marshall School of Business, where he has held tenure since 2015. Previously, he was an Assistant Professor at MIT’s Sloan School of Management (2007–2011). His research focuses on capital markets, particularly bond and options markets, and their macroeconomic interactions. He employs advanced econometric techniques and computational methods, with publications in top journals like the American Economic Review and Review of Financial Studies. Education includes a PhD in Finance and MS in Statistics from Stanford University, a Doctoral program in Mathematics at Caltech, and an MS and BS in Applied Mathematics from Oklahoma State University. His expertise spans asset pricing, credit risk, macro-finance, and econometric methods. Research interests include fixed income markets, macro-finance linkages, and the role of accounting information in financial markets. His recent work addresses interest rate volatility, risk premia, and intermediary constraints. He has received multiple awards, including the Lusk Center Grant (2018) and USC Dean’s Research Excellence Award (2014). Teaching: Financial Derivatives, Risk Management, and Fixed Income Securities at USC. Professional Activities: Editorial roles at the Journal of Banking and Finance, Journal of Empirical Finance, and Management Science. Refereed for top journals including the American Economic Review and Econometrica. He has presented widely at conferences such as the American Finance Association (AFA) and Federal Reserve Bank events. His work bridges theoretical econometrics with practical financial market analysis.

• Machine Learning
• Cybersecurity
• Biometric Authentication
• +۳ مورد دیگر

Dr Wencheng Yang is a Senior Lecturer in Computing at the School of Mathematics, Physics and Computing , University of Southern Queensland. He holds a PhD in Computing from UNSW, an MSc from Korea, and a BMgmt from Wuhan University of Technology. His research spans multiple domains including machine learning security , biometric authentication , privacy-preserving systems , and IoT applications . Education : BMgmt (Wuhan University of Technology), MSc (Korea), PhD (UNSW) Yang’s work emphasizes privacy and security in AI systems, particularly in biometric authentication (e.g., fingerprint, face, ECG) and IoT security. His recent publications focus on model inversion attacks , homomorphic encryption , and federated learning for healthcare applications. Key trends include secure face-swapping , Alzheimer’s disease prediction , and anti-forensic detection . His research has been cited 3378 times, with 1458 total downloads and 31 monthly views. While no explicit scientific awards are listed, his interdisciplinary work bridges computer science , healthcare , and cryptography . Current projects include privacy-preserving frameworks for implantable medical devices and military health systems .

Terri Duhonمشاهده پروفایل

پژوهشگر ارشد

• Derivatives
• Credit Derivatives
• Financial Trading
• +۳ مورد دیگر

Terri Duhon serves as an Associate Fellow at Saïd Business School, University of Oxford, where she teaches on the MBA and MSc in Financial Economics programmes while maintaining high-level non-executive board positions including Non-Executive Chair of Morgan Stanley Investment Management Ltd., Non-Executive Director at Morgan Stanley International (Risk Committee Chair), Rathbones plc (Risk Committee Chair), and Wise plc. Her academic foundation includes a Mathematics degree from MIT, followed by a decade as a derivative trader at J.P. Morgan where she co-developed global credit derivatives markets (documented in Fool's Gold ), and later founded a consulting firm providing expert witness services during the credit crisis. Research and Industry Focus Ms. Duhon's expertise spans critical financial domains: Derivatives structuring and credit risk modeling Real-time portfolio management with equity, debt, and FX exposures Algorithmic trading strategies and execution systems Value-at-Risk (VaR) and scenario analysis under leverage Fintech innovation in global payment infrastructure Post-crisis unwinding of complex financial products She leads an experiential eight-week trading course where students build and stress-test portfolios, and contributes to Oxford's Algorithmic Trading Programme exploring technology-driven market strategies. Professional Leadership Author of How the Trading Floor Really Works , she previously served on CHAPS Co and Operation Smile boards, and co-founded the Prince’s Trust Women’s Leadership Group.

• Data Science
• Econometrics
• Economics
• +۵ مورد دیگر

Univ.-Prof. Martin Wagner is a Professor at the Department of Economics, Alpen-Adria-Universität Klagenfurt, where he serves as Vice-Dean of the Faculty of Management, Economics and Law and Head of the Quantitative Economics Division. His research bridges theoretical and applied econometrics with environmental and macroeconomic challenges. Affiliation: Department of Economics, Faculty of Management, Economics and Law, Alpen-Adria-Universität Klagenfurt Wagner’s work focuses on econometric theory and its applications, particularly in modeling nonlinear cointegrating relationships, environmental economics, and macroeconomic forecasting. His expertise includes: Cointegrating polynomial regressions Unit root processes and stationarity High-dimensional time series analysis Environmental Kuznets curves Panel data econometrics Macroeconomic modeling Recent publications highlight his contributions to robust estimation techniques and the intersection of climate science with economic growth dynamics. Contact: martin.wagner@aau.at