Rainer Winkelmann is a Professor of Economics at the University of Zurich, affiliated with the Department of Economics within the Faculty of Economics. He joined the university in 2001 as a Professor for Statistics and Empirical Economic Research. His research focuses on econometrics, particularly discrete and panel data models, with applications to social policy analysis, work, family dynamics, and well-being. Winkelmann holds a Ph.D. from the University of Munich (1993) and has taught at institutions such as Dartmouth College, University of Canterbury, and served as a visiting professor at Harvard University, Syracuse University, and UCLA. His work bridges theoretical econometrics and applied issues in health economics, labor markets, and happiness research. He has developed influential econometric methods, including models for zero-inflated count data and fixed-effects ordered logit models. His recent research explores healthcare demand, policy evaluation, and the impact of unemployment on well-being. Teaching responsibilities include advanced econometrics courses for Ph.D. students.
Malik Shukayev is an Associate Professor in the Department of Economics at the University of Alberta, Faculty of Arts. He holds a PhD from the University of Minnesota (2005), an MA from the University of Colorado at Boulder (1997), and an undergraduate degree in Engineering from the Kazakh National Technical University. Prior to joining the University of Alberta in 2016, he served as a researcher at the Bank of Canada. Education PhD in Economics, University of Minnesota at Twin Cities (2005) MA in Economics, University of Colorado at Boulder (1997) Bachelor of Engineering, Kazakh National Technical University (Kazakhstan) Research Interests Shukayev specializes in macroeconomics and monetary economics, focusing on general equilibrium models to analyze monetary, fiscal, and macroprudential policies. His work addresses challenges such as price-level targeting, inflation dynamics, and the interplay between financial stability and monetary policy. Recent research includes studies on risk-taking behavior at low interest rates and cross-border financial linkages. Teaching He teaches courses such as Intermediate Macroeconomics, Monetary Economics, and Central Banking: Models and Computation. His ECON 485 team won the national Governor’s Challenge competition in 2021 and 2023. Advising & Grants Shukayev has advised on projects related to central bank modeling and financial stability. His work frequently involves collaborations with institutions like the Bank of Canada, focusing on empirical macroeconomic models and policy simulations. Labs & Teams His research group emphasizes practical applications of dynamic stochastic general equilibrium (DSGE) models, with a focus on Canadian economic data and policy analysis.
Dan Cao is an Associate Professor in the Department of Economics at Georgetown University, located in Washington, DC. His research focuses on macroeconomic theory, international economics, and the intersection of political institutions with economic development. He holds a prominent position at Georgetown's economics department and contributes to academic discourse through numerous peer-reviewed publications. Dr. Cao’s research interests include dynamic stochastic general equilibrium (DSGE) modeling, property rights dynamics in autocratic regimes, nonlinear economic relationships, and the effects of financial frictions on macroeconomic stability. His work often bridges theoretical frameworks with policy-relevant analysis, addressing topics like wealth inequality, monetary policy limits, and technological impacts on economic cycles. Recent publications highlight his exploration of global DSGE models, asymmetric adjustment costs in Phillips curves, and the implications of zero lower bound constraints. His 2023 papers emphasize institutional dynamics in autocracies and global macroeconomic frameworks, while earlier works (2017–2020) delve into wealth distribution mechanisms and real exchange rate theories. No scientific awards or grants are explicitly listed in the provided materials. Dr. Cao’s advising activities and laboratory affiliations are not detailed here, though his extensive publication record indicates active involvement in graduate training and research collaborations.
Gauti B. Eggertsson is a Professor of Economics at Brown University and Director of the Orlando Bravo Center for Economic Research. His research focuses on macroeconomic policy, monetary policy at the zero lower bound (ZLB), fiscal policy effectiveness, and financial crises. He has held roles at the IMF and Federal Reserve Bank of New York, contributing to influential theories on liquidity traps and policy responses to economic downturns. Education and career highlights include collaborations with prominent economists like Michael Woodford and Paul Krugman, advancing frameworks for understanding policy at the ZLB. His work emphasizes level targeting, reflation strategies, and the implications of secular stagnation. Recent research explores inflation dynamics, fiscal-monetary policy coordination (e.g., 'Abenomics'), and the paradox of toil. His articles analyze the Great Depression, Great Recession, and modern policy challenges such as the 2020s inflation surge. Eggertsson advocates for aggressive policy interventions to counteract demand-side weaknesses and stabilize economies. Teaching includes advanced macroeconomics courses emphasizing empirical methods and policy analysis. His work is widely cited in academic and policy circles, influencing central bank strategies and economic thought.
Stefano Eusepi is a Professor of Economics at Brown University, specializing in macroeconomic theory, monetary policy design, and the role of expectations in economic dynamics. His research focuses on understanding inflation expectations, central bank communication strategies, and the effectiveness of monetary policy under imperfect knowledge conditions. He has contributed significantly to the development of large-scale macroeconomic models such as the FRBNY DSGE framework. His scholarly work examines topics including the Phillips curve in crisis contexts, learning mechanisms in economic models, and the implications of policy uncertainty for long-term debt pricing. Eusepi’s publications span journals and working papers addressing key issues in modern macroeconomics, including fiscal-monetary coordination, expectations-driven fluctuations, and unconventional monetary policies. Notably, his research emphasizes the importance of adaptive learning in explaining economic behavior and policy outcomes, challenging traditional rational expectations assumptions. While no specific awards are listed, his consistent output in top-tier economic forums underscores his scholarly impact. Advising and grants are not detailed in the provided texts. He is affiliated with Brown University’s Department of Economics and likely contributes to academic initiatives there. His work often intersects with policy-oriented research, reflecting collaboration with institutions like the Federal Reserve Bank of New York.
Professor Joe Nellis is a leading academic at Cranfield University, serving as Professor of Global Economy and Deputy Dean at the Cranfield School of Management. He is affiliated with the Department of Economics, Finance and Business Data Analytics and has been a central figure in establishing the school’s globally recognized economics teaching, ranked #1 in the world by the Financial Times in 2017. He holds visiting professorships in Germany, Belgium, Austria, the Netherlands, Hungary, the USA, and Ghana. BSc(Econ), University of Ulster MA, University of Warwick PhD, Cranfield University His research spans global macroeconomics, business environmental analysis, strategic thinking, and management development. He has published over 200 academic and practitioner articles and 19 books, focusing on fiscal and monetary policy, financial institutions, housing markets, and international economic developments. His collaborative work frequently examines policy impacts in both OECD and emerging economies. The 15 most recent publications reveal a strong trend in analyzing fiscal consolidation, monetary and macroprudential policies, institutional investors, and intellectual property enforcement. These works employ advanced econometric methods and panel data analysis, often with a focus on policy evaluation in Greece, Indonesia, and the UK. The breadth of journals reflects interdisciplinary engagement across economics, finance, innovation, and sustainability. CBE (Commander of the Order of the British Empire) Adam Smith Tassie Medallion (top Economics graduate, University of Ulster) Outstanding Professor Award (Hungary, TEMPUS Programme) Distinguished Graduate Award (University of Ulster) Multiple Best Professor Awards (Purdue University, Tilburg University) FT Rank: #1 globally for MBA economics teaching (2017) Professor Nellis has advised numerous private and public sector clients, including Cisco, Vodafone, Procter & Gamble, UCL, and UK government departments. He has held senior leadership roles such as Director of the Full-Time MBA, Academic Dean, and Pro-Vice Chancellor. He co-developed the UK’s leading house price indices (Halifax and Nationwide) and remains active in research, teaching, and consultancy. He is a frequent speaker at international conferences and contributes to policy debates on economic strategy and financial regulation. He is a key member of the Economics Group at Cranfield, which he founded, and continues to lead research initiatives in macroeconomic modeling, financial systems, and global economic trends. His work often involves collaboration with scholars across Europe, Africa, and Asia, reflecting his international academic network and influence.
Anish Mukherjee is a Research Fellow at the Faculty of Economics, University of Italian Switzerland (USI) in Lugano, Switzerland, working under Professor Antonietta Mira. His role focuses on developing statistical methodologies for complex biomedical data analysis within an economics faculty context. He earned his PhD in Biostatistics from the University of Louisville under Jeremy Gaskins' supervision. His research integrates advanced statistical techniques with biomedical applications, specializing in Bayesian approaches for high-dimensional dependent data. Key methodological contributions include zero-inflated count data models, heterogeneity detection frameworks for longitudinal outcomes, and nonparametric Bayesian methods using stochastic differential equations. Applied work spans microbiome analysis related to neurological treatments, infectious disease transmission modeling, maternal health disparities, wastewater-based SARS-CoV-2 surveillance, and air pollution-COVID-19 outcome relationships.
Oke Gerke is a Professor in Clinical Biostatistics in Diagnostic Research at the Department of Clinical Research, University of Southern Denmark, and a Biostatistician at the Department of Nuclear Medicine, Odense University Hospital. He is affiliated with the Research Unit of Clinical Physiology and Nuclear Medicine in Odense and holds a DMSc from the Faculty of Health Sciences at SDU. MSc in Mathematics and Economics, University of Hamburg (1998) PhD in Statistics and Econometrics, University of Hamburg (2001) DMSc, Faculty of Health Sciences, University of Southern Denmark (2024) Lecturer Training Programme, University of Southern Denmark (2010) His research centers on the methodological foundations of diagnostic and prognostic trials in molecular imaging. He specializes in adaptive and sequential trial designs, Bland-Altman agreement analysis, ROC curve methodology, and network meta-analysis of diagnostic accuracy studies. His work bridges biostatistics, clinical epidemiology, and nuclear medicine, with applications in oncology, cardiology, and public health. He has contributed extensively to improving reporting standards in diagnostic research and statistical methodology in clinical trials. The recent articles highlight a strong trend toward methodological innovation in diagnostic research, with a focus on adaptive and seamless trial designs, real-time evaluation frameworks during outbreaks, and advanced statistical techniques for agreement and cutpoint analysis. His clinical work integrates nuclear imaging modalities like PET/CT in cancer and cardiovascular disease, supported by rigorous meta-analytic and biostatistical approaches. He is a member of the following scientific societies: International Biometric Society (IBS) International Society for Clinical Biostatistics (ISCB) Danish Society for Theoretical Statistics (DSTS) Oke Gerke has supervised 1 PhD as main supervisor and 22 as co-supervisor, with 10 completed master’s theses under his main supervision and 4 ongoing PhD projects as co-supervisor. He has been involved in research projects such as the Neurobiological effects of work-related adjustment disorder, contributing to both statistical design and analysis. While no specific grants are listed, his extensive publication record and collaborative research indicate active grant-supported work. He frequently participates in workshops, seminars, and conferences, delivering guest lectures on topics such as network meta-analysis and diagnostic test evaluation. He is actively involved in academic and clinical research teams at SDU and OUH, particularly within the Research Unit of Clinical Physiology and Nuclear Medicine. His collaborative network spans multiple disciplines, including cardiology, oncology, and psychiatric research, reflecting a multidisciplinary approach to clinical biostatistics.
Jens Oluf Andersen is a Professor in the Department of Physics at the Norwegian University of Science and Technology (NTNU). His research focuses on quantum chromodynamics (QCD) at finite temperature/density, cold Bose/Fermi gases, renormalization group methods, and effective field theories. He has made significant contributions to understanding phase diagrams in dense quark matter and the interplay between magnetic fields and QCD dynamics. Education & Affiliations: Physics at NTNU, leading the theoretical high-energy physics group. His research interests span: - QCD phase transitions and critical phenomena - Chiral symmetry restoration in dense matter - Magnetic catalysis and inverse magnetic catalysis effects - Bose-Einstein condensation in QCD contexts - Effective field theory approaches for strongly interacting systems Recent work highlights the role of chiral perturbation theory in describing QCD at finite isospin density and the interplay between color superconductivity and thermodynamic properties. His 2025 papers explore chiral dynamics in QCD and its connection to Bose-Einstein condensation. Key collaborations include studies with Prabal Adhikari on isospin-dependent QCD and with Martin Kjøllesdal Johnsrud on magnetic field effects. His 2022 work analyzed the electroweak phase transition in two-Higgs models using nonperturbative methods.
Daniel Rodríguez García is an Associate Professor (tenured) at the Department of Computer Science, University of Alcalá, Madrid, Spain. He also serves as a visiting researcher at Oxford Brookes University, UK, and previously held roles as an online tutor at the Universitat Oberta de Catalunya (UOC) and lecturer at the University of Reading (2001–2010). His academic credentials include a Computer Science degree from the University of the Basque Country and a PhD from the University of Reading (2003), complemented by a Postgraduate Certificate in Academic Practice (2005). His research focuses on data mining and software engineering , particularly applying machine learning techniques to software engineering challenges like defect prediction, classifier optimization, and cybersecurity. He leads the PROGRESSUS (Programming & Sustainability) and TIFyC (Information Technologies for Training & Knowledge) research groups, emphasizing sustainable software practices and educational technology innovation. His work spans topics such as DevOps monitoring, inclusive e-learning platforms, and AI-driven threat analysis in manufacturing industries. Notable contributions include the POEMA personal cloud system for education and studies on ransomware patterns in the Dark Web. His articles reflect trends in multi-objective optimization, imbalanced data handling, and ethical AI integration. He actively participates in workshops like RAISE (Realizing AI Synergies in Software Engineering), fostering cross-disciplinary collaboration.
Huanfa Chen is an Associate Professor in Spatial Data Science at the Centre for Advanced Spatial Analysis (CASA), University College London (UCL). He joined CASA in 2019 as a Teaching Fellow, progressing to Lecturer and Deputy Departmental Tutor in 2020. His research focuses on spatial optimization, GeoAI, and computational methods for geospatial problems, including transportation planning, public health, and urban analytics. He holds a PhD in Geographical Information Science (UCL, 2019), MSc in Cartography and GIS (Peking University, 2014), and BSc in Chemistry (Peking University, 2011). He is an Associate Fellow of the Royal Institute of Navigation and contributes to open-source geospatial software development through projects like the spopt library. His work addresses urban challenges such as equitable healthcare access, traffic safety, and pandemic response through interdisciplinary approaches. Education background: PhD in Geographical Information Science (UCL, 2019) MSc in Cartography and GIS (Peking University, 2014) BSc in Chemistry (Peking University, 2011) Research interests span spatial optimization, GeoAI, and computational geospatial methods, with applications in transportation, public safety, and urban planning. He integrates techniques like deep neural networks, meta-heuristics, and agent-based simulation. Recent work includes optimizing vaccination service accessibility and predicting traffic incident risks using graph neural networks. Awards and recognition include contributions to open-source software (e.g., spopt ) and participation in international collaborations. He advises PhD students focusing on spatial data science and GeoAI.
Pascal Michaillat is an Associate Professor of Economics at the University of California, Santa Cruz. His research focuses on economic slack, particularly unemployment dynamics and macroeconomic policy responses. His work bridges macroeconomic theory with real-world policy applications, emphasizing the role of unemployment and vacancy rates in shaping economic outcomes. Key research themes include recession detection mechanisms, migration impacts on labor markets, and the development of robust statistical methodologies like the 'Michez rule' for real-time economic analysis. He has collaborated extensively on resolving theoretical anomalies in New Keynesian models and contributed to frameworks for optimal unemployment insurance design. Michaillat's recent work addresses methodological rigor in hypothesis testing, proposing critical values to mitigate p-hacking in scientific research. This work, co-authored with Adam McCloskey, was published in the Review of Economics and Statistics and includes open-source MATLAB code for reproducibility. His interdisciplinary approach integrates labor economics, business cycle analysis, and econometric modeling to inform policy decisions. Notable contributions include the Beveridgean Phillips curve framework and the geometric unemployment-vacancy relationship (u∗=√uv), which provide benchmarks for full employment. His research emphasizes cyclical unemployment's role in shaping fiscal and monetary policy effectiveness, particularly during economic downturns.
Hugh Miller serves as a Visiting Fellow at the Centre for Economic Transition Expertise within the Grantham Research Institute at the London School of Economics and Political Science, while concurrently working as a Policy Analyst at the Organisation for Economic Cooperation and Development (OECD) specializing in biodiversity-related financial risks and critical minerals. His academic credentials include: First-class Bachelor's degree in Politics, Philosophy, and Economics from the University of Exeter, with dissertation research on UK green bond market risk-return profiles MSc in Environmental Economics and Climate Change from the London School of Economics Miller's research critically examines financial system vulnerabilities in the climate transition, with particular emphasis: Sustainable Finance Mechanisms : Developing frameworks for green financial instruments and risk assessment Central Banking Adaptation : Integrating climate risks into monetary policy and prudential supervision Critical Minerals Security : Quantifying supply chain risks for energy transition technologies Analysis of his publication record reveals consistent focus on macro-financial implications of mineral scarcity, with methodological emphasis on NGFS climate scenarios to model material demand bottlenecks. His work demonstrates evolving policy relevance from foundational climate risk concepts (2022) toward strategic mineral stockpiling solutions (2025), maintaining strong connections between financial regulation and physical resource constraints. No scientific awards were documented in the source materials. Miller's collaborative research approach is evident through extensive co-authorship with OECD colleagues, Grantham Institute researchers, and international policy experts. His work demonstrates engagement with major climate finance initiatives including the Network for Greening the Financial System, though specific grant funding sources remain unreported in available materials. As a key contributor to the Centre for Economic Transition Expertise, Miller operates within LSE's Grantham Research Institute ecosystem while maintaining active OECD policy development roles. His research bridges academic analysis and practical policy formulation through regular contributions to international climate finance working groups.
Dr. Mulugeta Gebregziabher is a Professor and Vice Chair for Academic Programs at the Medical University of South Carolina (MUSC) , with dual appointments at the MUSC Global Health Institute and College of Graduate Studies . He is a Research Health Scientist and Methodology Core Leader at the Charleston VA Medical Center's HEROIC Innovation Center , focusing on health disparities, longitudinal data analysis, and health services research for conditions like diabetes, stroke, and HIV/AIDS. His methodological expertise includes: Longitudinal data analysis Zero-inflated data modeling Joint modeling of multiple outcomes Missing data techniques Large dataset analysis Clinical collaborations span diabetes, chronic kidney disease, cardiovascular disease, lung cancer, and global health. He has contributed to over 50 funded NIH/VA grants and 200+ peer-reviewed publications, developing novel statistical methods for health services research. Current teaching includes advanced biostatistics courses and summer institute workshops on Bayesian analysis and epidemiological statistics. Scientific leadership roles: Fellow, American Statistical Association President, American Statistical Association SC Chapter Editorial board member, British Medical Journal-Heart Founding member, Statistical Society of Ethiopians in North America Board member, Worldwide Fistula Fund
Professor Florin Bilbiie is a leading macroeconomist at the Faculty of Economics, University of Cambridge , specializing in business cycles and stabilization policies. His work bridges heterogeneous households, firm entry, and market power to analyze monetary-fiscal interactions. Research interests include: Aggregate Demand Analysis with Heterogeneity and Inequality Aggregate Supply Dynamics via Endogenous Entry and Product Variety Monetary and Fiscal Policy Design in Liquidity Traps Tractable Heterogeneous-Agent New Keynesian (THANK/HANK) Modeling Recent publications highlight his focus on sticky prices/wages, redistribution mechanisms, and profit-driven aggregate demand complementarities. He has received the 2021 Best Paper Award from the Journal of Monetary Economics. Collaborations include prominent economists like Melitz, Monacelli, and Perotti. Supervised PhD students work on topics ranging from asset bubbles to sovereign default modeling.
