Anastasia Semykina is a Professor of Economics and Deputy Dean (Research and Innovation) at RMIT University's School of Economics, Finance & Marketing. She holds a PhD from Michigan State University (2006) and previously served as Charles and Joan Haworth Professor of Economics at Florida State University. Her expertise spans theoretical and applied econometrics, with a focus on panel data models, missing data estimation, and their application in labor economics, education economics, transition economies, and economic psychology. She teaches advanced econometrics and microeconomics courses at both undergraduate and graduate levels. Research Interests: Theoretical and Applied Econometrics Labor Economics Economics of Education Transition Economies Economics and Psychology Health Economics Her recent publications address topics such as panel data methodologies, healthcare cost-effectiveness analysis, and educational policy evaluation. She is actively involved in supervising PhD and Master's research students in econometrics and applied economics.
Dr. Edward Wei is a Research Fellow at the University of Sydney Business School's Institute of Transport and Logistics Studies (ITLS), where he has been since 2018. His work focuses on transport modeling, urban mobility, and policy analysis, with an emphasis on post-pandemic commuting patterns and sustainable transport initiatives. He holds a PhD from the University of Technology Sydney (UTS), an MBus from Queensland University of Technology (QUT), and a BEc from UIBE in China. Dr. Wei's research explores the intersection of work arrangements (e.g., hybrid work, flexi-time) and their impacts on transportation demand, urban planning, and environmental sustainability. His recent projects include developing state-wide transport models, analyzing micro-mobility adoption, and assessing the role of non-traditional mobility service providers in MaaS frameworks. Key areas of expertise include discrete choice modeling, transport demand forecasting, and policy evaluation. His publications span over 30 peer-reviewed articles, with recent contributions emphasizing post-pandemic commuting behavior, zero-emission truck transitions, and sustainable university travel strategies. His academic contributions bridge theoretical transport economics with practical policy applications, addressing challenges such as car tolling regimes, public transport patronage optimization, and the integration of remote work patterns into urban planning frameworks.
Scientia Professor Robert Kohn is a distinguished academic at the University of New South Wales, holding a position in the School of Economics within the UNSW Business School. With a career spanning several decades, Professor Kohn has established himself as a leading expert in statistical methodology and econometric modeling. His research has significantly contributed to Bayesian statistics and computational methods for complex data analysis. Professor Kohn's research focuses on advanced statistical methodologies including Bayesian methodology, variable selection and model averaging, nonparametric regression models, time series modeling, multivariate Gaussian and non-Gaussian regression, and Markov chain Monte Carlo simulation algorithms. His work bridges theoretical statistics with practical applications across economics, finance, and cognitive science. His research demonstrates a consistent trajectory toward developing more efficient computational methods for complex statistical models, with recent work emphasizing variational Bayesian methods, particle filtering techniques, and applications to time series analysis. Analysis of his recent publications (2022-2025) reveals a strong focus on advancing computational statistical methods, particularly in Bayesian inference for complex models. His work shows increasing integration of machine learning techniques with traditional statistical methods, especially in handling high-dimensional data and complex time series structures. Professor Kohn has made significant contributions to variational inference methods, particle-based computational techniques, and applications to financial time series and cognitive modeling. Professor Kohn has maintained an exceptionally productive research career with continuous publication output since the 1970s, demonstrating remarkable longevity and adaptability in his research focus as statistical methodologies have evolved. His work shows strong international collaboration, particularly with researchers in Australia, the United States, and Europe, reflecting his standing in the global statistical community.
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
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
George Athanasopoulos is Professor and Head of the Department of Econometrics and Business Statistics at Monash University, a position he has held since 2022. He was appointed Professor in 2019 and has established himself as an internationally recognized expert in forecasting, time series analysis, and applied econometrics. He serves as Past President (since 2024) and former Director (2014-2024) of the International Institute of Forecasters, and is Associate Editor of the International Journal of Forecasting since 2014. His research focuses on hierarchical and grouped time series forecasting, where he has pioneered methods for forecast reconciliation and cross-temporal coherence. His work has significantly influenced forecasting practices across diverse fields including national statistics offices, energy markets, and public health. He is particularly renowned for his contributions to tourism forecasting and macroeconomic modeling in big data environments. Awarded the Australian Awards for University Teaching in 2022 for outstanding contributions to student learning, Professor Athanasopoulos has also received multiple Dean's Awards from Monash Business School for research excellence, teaching innovation, and publication quality. His research output includes over 49 publications and leadership of six major research projects, including the ARC-funded 'Macroeconomic forecasting in a Big Data world' and the RACE for 2030 CRC project on clean energy forecasting. His work contributes to UN Sustainable Development Goals through applications in economic forecasting, energy modeling, and sustainable tourism development. He has supervised numerous research students and collaborated extensively with institutions including Australian National University, Griffith University, and international partners across multiple continents.
Glen Searle is an Associate Professor at the Faculty of Architecture, Design and Planning at The University of Sydney, specializing in urban planning and metropolitan governance. His academic career demonstrates a strong focus on strategic planning, infrastructure governance, and urban policy development, particularly within the Australian context. Professor Searle's research interests span urban planning, strategic planning, metropolitan governance, infrastructure governance, land use planning, urban sustainability, and city development. His work critically examines planning systems, governance structures, and policy implementation challenges in metropolitan areas, with particular attention to Sydney's urban development strategies and infrastructure projects. He has made significant contributions to understanding the complexities of metropolitan governance, the public interest in mega infrastructure planning, and the challenges of population growth management. Analysis of Professor Searle's recent publications reveals a consistent focus on governance frameworks for urban infrastructure, metropolitan strategic planning, and the intersection of planning policy with population dynamics. His work demonstrates a methodological diversity, employing systematic literature reviews, case studies, and network analysis to examine urban phenomena. A notable trend is his increasing focus on infrastructure governance, particularly how governance structures respond to crises and changing urban conditions. His research bridges theoretical planning concepts with practical policy applications, often drawing on Australian case studies while connecting to international planning discourse. Professor Searle has secured significant research funding, including the 2020 Infrastructure Governance Incubator grant from The Henry Halloran Trust and the 2019 Population Growth and Regional Connectivity research grant from the Australian Housing and Urban Research Institute. His collaborative approach is evident in his extensive co-authorship patterns across multiple institutions and disciplines. His scholarly contributions include numerous journal articles in leading planning and urban studies publications, book chapters, and edited volumes such as Global Planning Innovations for Urban Sustainability (2019). Professor Searle's work has appeared in high-impact journals including Urban Studies , Journal of Planning Literature , Urban Policy and Research , and Planning Theory and Practice .
Christopher John O'Donnell is a distinguished Professor at the School of Economics, University of Queensland, Australia, where he holds a dual affiliation (50% each) with both the main School of Economics and the Centre for Efficiency and Productivity Analysis (CEPA). His research primarily focuses on efficiency and productivity analysis across various sectors including agriculture, fisheries, public services, and healthcare. As a leading scholar in his field, he has published extensively in top-tier economics and operations research journals and is recognized as being among the top 5% of authors globally according to multiple citation metrics. O'Donnell's research interests span several interconnected domains: efficiency analysis, productivity measurement, agricultural economics, econometrics, state-contingent production frontiers, and metafrontier analysis. His work often bridges theoretical methodology with practical applications, particularly in estimating efficiency and productivity changes under various constraints and uncertainties. He has developed innovative approaches for measuring productivity in public service providers, agricultural sectors, and healthcare institutions, with particular attention to how weather, climate change, and demand uncertainty affect performance metrics. His research output demonstrates consistent productivity, with publications spanning from the 1990s to the present, including significant contributions in the last five years. O'Donnell frequently collaborates with researchers internationally, particularly with scholars from Australia, Europe, and Asia, reflecting the global relevance of his work. His publications appear in leading journals such as the American Journal of Agricultural Economics, Journal of Productivity Analysis, European Journal of Operational Research, and Agricultural and Applied Economics journals. Ranked among top 5% authors by citation metrics (Number of Citations) Ranked among top 5% authors by citation metrics (Number of Citations, Discounted by Citation Age) Ranked among top 5% authors by citation metrics (Number of Citations, Weighted by Number of Authors) Ranked among top 5% authors by citation metrics (Number of Citations, Weighted by Number of Authors, Discounted by Citation Age) Ranked among top 5% authors by citation metrics (Euclidian citation score) O'Donnell has supervised numerous graduate students, as evidenced by his 'Record of graduates' noted in his RePEc profile. His research has been supported by various institutions, particularly focusing on agricultural productivity, public sector efficiency, and resource economics. He has contributed significantly to methodological developments in productivity measurement, including nonparametric approaches and metafrontier frameworks that allow for cross-technology comparisons. As a core member of the Centre for Efficiency and Productivity Analysis (CEPA) at the University of Queensland, O'Donnell contributes to one of the world's leading research centers in efficiency and productivity analysis. His work has practical applications for policymakers in agriculture, fisheries management, healthcare, and public service delivery, helping organizations measure and improve their performance in increasingly complex economic environments.
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
Professor Valentyn Panchenko is a leading academic in Economics at the UNSW Business School, specializing in advanced econometric methodologies and financial modeling. Holding a PhD from the University of Amsterdam and an MPhil from the Tinbergen Institute, his research bridges theoretical econometrics with real-world financial applications, emphasizing big data analysis, network structures, and dependence modeling in economic systems. His expertise spans financial econometrics, time series analysis, non-parametric statistics, and agent-based economic simulations. He focuses on Granger causality, model evaluation, structural economic modeling, and bounded rationality with heterogeneous agents. His work has secured significant grants including ARC Discovery Projects and DECRA fellowships, enabling cutting-edge research on market dynamics and economic interactions. Professor Panchenko's publications appear in top-tier journals like the Journal of Econometric Theory, AEJ: Micro, Journal of Economic Dynamics & Control, and Journal of Banking & Finance. His methodological contributions include novel approaches to copula-based forecasting, nonlinear causality testing, and evolutionary learning models in strategic economic environments. While specific student advising details aren't provided, his research leadership demonstrates sustained impact across econometric theory, financial markets, and experimental economics.
Dr. Mohamad Khaled is a Senior Lecturer in the School of Economics at The University of Queensland (UQ), affiliated with the Centre for Efficiency and Productivity Analysis within the Faculty of Business, Economics and Law. His research focuses on Applied Health Economics , Health Econometrics , and broader Econometrics methodologies. He specializes in analyzing health inequality, socioeconomic determinants of health, and statistical modeling techniques for economic data. His work addresses critical issues such as child malnutrition, health concentration curves, and income-related health disparities. Dr. Khaled has contributed to peer-reviewed journals including European Journal of Health Economics , Journal of Business and Economic Statistics , and Health Economics . His methodologies often involve advanced econometric frameworks and Bayesian approaches. He holds an academic position in a leading economics department and collaborates with institutions like Edward Elgar Publishing. His research emphasizes bridging theoretical econometric models with real-world health policy applications.
Harald Van Heerde is a Research Professor of Marketing at the University of New South Wales, Sydney, within the UNSW Business School's Department of Marketing. He holds roles as Editor of the Journal of Marketing and Executive Vice-Chairman/Program Director of the Marketing Science Hub at AiMark. His academic career includes positions at Maastricht University, the University of Waikato, Tilburg University, and Massey University. Education: Ph.D. in Economics (Cum Laude), University of Groningen, the Netherlands (1999) M.Sc. in Econometrics (Cum Laude), University of Groningen, the Netherlands (1995) Research Interests: Harald focuses on applying econometric models and large datasets to address critical marketing challenges. His work explores marketing mix effectiveness , brand equity , digital marketing strategies , consumer behavior in crises , and cross-industry applications such as retailing, healthcare, and entertainment. Methodologically, he emphasizes dynamic models, endogeneity correction, optimization techniques, and text mining. Articles Trends: Recent publications highlight analysis of inflation's impact on consumer spending , mobile app engagement , brand recovery post-crisis , and econometric frameworks in marketing decision-making. His work bridges theoretical advancements with practical business implications, particularly in stochastic cost industries and global market dynamics. Awards & Fellowships: 2024: AMA Fellow & Shelby/Hunt Best Paper Award 2021: Churchill Award (Lifetime Contributions) 2004–2023: 10+ paper awards including MSI/Root, Paul Green, and multiple long-term impact recognitions Advising & Grants: Currently supervising doctoral candidates Ayesha Hossain (Human Branding) and Ada Choi (consumer financial decision-making). Supervised 12 completed theses across branding, retailing, and digital marketing. Secured over AU$2 million in grants including ARC Discovery, MSI, and the Marsden Fund. His grants examine topics like brand crisis management, price war dynamics, and mobile marketing ROI. Labs & Teams: Leads the Marketing Science Hub at AiMark, a nonprofit connecting academics with household panel data. Consults for global firms including Unilever, Edeka, and AZTEC. His work emphasizes collaborative data-driven research with industry partners.
Ruben Loaiza-Maya is an Associate Professor (Research) in the Department of Econometrics and Business Statistics at Monash University. He holds a PhD in Econometrics from the University of Melbourne and an undergraduate degree in Economics from Universidad Nacional de Colombia (Medellin). His research focuses on Copula Modelling, Bayesian Estimation Methods, Time Series Analysis, and Macroeconomic/Financial Forecasting. Key contributions include advancements in variational inference, state space models, and robust forecasting techniques under model misspecification. He leads the active project 'Variational Inference for Intractable and Misspecified State Space Models' (2023–2026), funded as a Primary Chief Investigator. His work contributes to UN Sustainable Development Goals through methodological advancements in economic and financial analysis. Recent research emphasizes scalable Bayesian methods, hybrid variational approaches, and efficient computational techniques for high-dimensional models. Publications span prestigious journals like the International Journal of Forecasting, Journal of Econometrics, and Journal of Business and Economic Statistics. Notable collaborations include studies on copula-based time series forecasting and robust approximate Bayesian computation. His work bridges theoretical econometrics with practical applications in risk management and macroeconomic policy.
Professor Alicia Rambaldi is Director of Research at the School of Economics, Faculty of Business, Economics and Law at the University of Queensland. She is also an Affiliate of the Centre for Efficiency and Productivity Analysis. Her academic career spans decades of research in econometric methodologies with applications to real-world economic problems. Professor Rambaldi's research interests focus on applied econometrics, time series econometrics, state-space models, and spatial time series models. She has made significant contributions to economic measurement, particularly in developing methodologies for computation of price indices for land and property, estimation with linked administrative data, and smoothing methodologies combining spatial and temporal information. Her work bridges theoretical econometrics with practical applications in housing markets, climate adaptation, and international economic comparisons. Her recent publications demonstrate a consistent focus on housing economics, with numerous papers on hedonic pricing models, property valuation, and the impact of environmental factors on real estate markets. She has also maintained a strong research program in international comparisons, purchasing power parity, and productivity analysis, often collaborating with leading researchers in these fields. Professor Rambaldi is actively involved in research supervision, currently advising on topics including language barriers faced by immigrants, distributive politics, and copula models. Her completed supervision includes significant work on purchasing power parities, development indexes, trade studies, and spatial analysis of tourism employment. Her current research projects include spatial time series models with applications to housing and land prices, transport demand modeling, and international comparisons. She has secured substantial funding from diverse sources including the Australian Research Council, Natural Hazards Research Australia, and government departments, demonstrating the applied relevance of her work. Professor Rambaldi leads an active research group within the Centre for Efficiency and Productivity Analysis, focusing on developing and applying advanced econometric techniques to address pressing economic measurement challenges. Her work often involves interdisciplinary collaboration with researchers in environmental science, urban planning, and transportation studies.
Associate Professor Seojeong Lee is a faculty member at the University of New South Wales (UNSW) Business School, School of Economics, specializing in advanced econometric theory. She joined UNSW in 2012 after completing her PhD at the University of Wisconsin-Madison and has established herself as a leading researcher in robust inference methods under complex data conditions. Her educational background includes: Ph.D. in Economics, University of Wisconsin-Madison (2008-2012) M.A. in Economics, Seoul National University (2006-2008) B.A. in Economics and Political Science (dual major), Seoul National University, summa cum laude (2000-2006, with military service 2002-2004) Professor Lee's research centers on developing theoretically rigorous methods for econometric inference, with primary focus on generalized method of moments (GMM), instrumental variables (IV), and two-stage least squares (2SLS) under model misspecification. Her work addresses critical challenges including invalid/many/weak instruments, heterogeneous treatment effects, and clustered sampling, contributing foundational advances to statistical inference in economics. Analysis of her recent publications reveals a strong trajectory in refining methods for many-instrument settings and misspecified models, with increasing emphasis on computational implementations (e.g., Stata packages) and applications to causal inference. Her work bridges theoretical econometrics with practical policy-relevant analysis. Her scientific achievements include: Australian Research Council DECRA Fellowship (2017-2019) UNSW Dean's Research Fellowship (2020-2022) Zellner Thesis Award Honorable Mention from American Statistical Association (2014) Multiple competitive UNSW research awards Professor Lee actively supervises PhD candidates Wei Tian and Fangzhou Yu, and has secured over AUD 700,000 in research funding including ARC Discovery Projects. She teaches undergraduate and postgraduate econometrics courses, integrating her research into pedagogy. Her ongoing work continues to push boundaries in robust econometric methodology for modern data challenges.
