Research grants

  • 2020-2024: ARC Industrial Transformation Training Centre. "Optimisation Technologies, Integrated Methodologies, and Applications (OPTIMA)". Chief Investigators: Smith-Miles, Stuckey, Taylor, Ernst, Aickelin, Garcia de la Banda, Pearce, Wallace, Bondell, Hyndman, Alpcan, Thomas, Anjomshoa, Kirley, Tack, Costa, Fackrell, Zhang, Glazebrook, Branke, O’Sullivan, O’Shea, Cheah, Meehan, Wetenhall, Bowly, Bridge, Faka, Mareels, Coleman, Crook.
  • 2017–2021 “ARC Centre of Excellence for Mathematical and Statistical Frontiers”. Chief Investigators: N Bean, K Burrage, J de Gier, A Delaigle, P Forrester, T Garoni, RJ Hyndman, R Kohn, D Kroese, K Mengersen, A Pettit, P Pollet, M Roughan, L Ryan, S Sisson, K Smith-Miles, P Taylor, I Turner, M Wand, Y-G Wang.
Project ID Chief Investigators Project Title Partner Org
LP180101151K Mengersen, RJ Hyndman, E Peterson, J McGree, R Turner, P Maxwell, B Liquet, J Jones.Revolutionising water-quality monitoring in the information age.Queensland Dept of Environment & Science; Healthy Land and Water.
LP160101885 Kate Smith-Miles, Rob Hyndman Intruder alert! detecting and classifying events in noisy time series Future fibre technologies limited
LP160101038 Bonsoo Koo,
Zili Zhu, David Cox, Douglas McBirnie
Towards a superannuation system
fit for the future 
Challenger Ltd
Accurium Pty Ltd

Project ID

Chief Investigators Project Title Funding Years


Tatsushi Oka

Estimating and Testing Heterogeneous Structural Changes

2021 – 2023


Bin Peng; Wenying Yao

New Insights on Modelling Time Trends with Panel Data: Theory and Practice

2021 – 2023


Seojeong Lee; Bonsoo Koo

Statistical Analysis of State-Dependent Government Spending Multipliers

2021 – 2023


Donald Poskitt; Xueyan Zhao; Firmin Sabro Doko Tchatoka

Identification Power and Instrument Strength in Discrete Outcome Models

2021 - 2023

DP200102769 Heather Anderson; Jiti Gao; Farshid Vahid; Wei Wei; Peter Phillips, Oliver Linton, Asger Lunde New methods for modelling complex trends in climate and energy time series. 2020-2022
DP200101414 Gael Martin; David Frazier; Rob Hyndman; Worapree Maneesoonthorn Loss-based Bayesian Prediction. 2020-2022
DE200101070 David Frazier Consequences of Model Misspecification in Approximate Bayesian Computation 2020-2022
DE200100693 Benjamin Wong Financial Cycles and the Macroeconomy 2020-2022
DP190101152 Tatsushi Oka, Tong Li Econometric methods for distributional policy effect 2019-2021
DP190100202 James Morley, Yunjong Eo; Benjamin Wong Understanding the sources of secular stagnation 2019-2021
DP180102538 Liana Jacobi, Dan Zhu Prior sensitivity analysis for Bayesian Markov chain Monte Carlo output 2018-2020
DE170100713 Bonsoo Koo Nonparametric estimation and forecasting of yield curve dynamics 2017-2019
DP170104421 Jiti Gao

Econometric model building and estimation

DP170100729 Gael Martin, David Frazier, Christian Robert, Eric Renault The validation of approximate Bayesian computation. 2017-2019

Vasilis Sarafidis, Takashi Yamagata

Micro-panel data with non-linear error components

DP170103884 German Valencia, Dianne Cook, Csaba Balazs, Andreas Buja, Marzia Rosati Visualisation of multidimensional physics data. 2017-2019
DP150104292 Heather Anderson, Bonsoo Koo, Myung Seo Forecasting when model stability is uncertain 2015-2017
DP150101012 Jiti Gao, Peter Phillips Non- and Semi-Parametric Panel Data Models: Theory and Applications 2015-2019
DP150101728 Gael Martin, Catherine Forbes, Brendan McCabe, Christian Robert Approximate Bayesian Computation in State Space Models 2015-2017
DP150100210 Mervyn Silvapulle, Davide La Vecchia, Marc Hallin

Robust Methods for Heteroscedastic Regression Models for Time Series

DP140100743 Mark Harris, David Harris, Brenda Gannon Threshold Models in Micro-Econometrics with Applications to Health 2014-2016
DP140103220 Anastasios Panagiotelis, George Athanasopoulos, Rob Hyndman, Farshid Vahid Macroeconomic Forecasting in a Big Data World 2014-2016
DP140102345 Xueyan Zhao, Don Poskitt, Frank Windmejer Partial Identification of Treatment Effect in Binary Response Models with Applications in Health 2014-2016
DP140100673 Bill Griffiths, Duangkamon Chotikapanich, Prasada Rao Modelling Income Distributions over Space and Time: 1985-2010 2014-2016
  • 2020-2021. K Ackermann, P Raschky, S Angus. ‘The Expansion of the Internet and Economic Growth Worldwide’. Funding from Facebook Research

  • 2019-2020: C Bergmeir, F Vahid, RJ Hyndman. “Application of advanced short term power generation forecasting technology for wind and solar farms”. Funding from Advisian.
  • 2020 RJ Hyndman, G Athanasopoulos. "Review of Australian tourism forecasting models". Funding from Australian Trade and Investment Commission.

  • 2019-2020: RJ Hyndman, M O'Hara-Wild "Modelling of bore water levels in NSW". Funding from the Office of the NSW Chief Scientist and Engineer.

  • 2017–2018 RJ Hyndman, S Ben Taieb, C Bergmeir. “Demand forecasting for large-scale dynamic hierarchies in a big data environment”. Funding from Huawei Innovation Research Program.
  • 2017–2021 B Inder, "Research on Key Issues for Economic Development in Timor-Leste" partnered with Cardno Emerging Markets / DFAT

  • 2018–2019 P Silvapulle, N Bailey, "Big data analytic approach to assessing impacts of harmful temperatures on wheat crops in northern Victoria: regional economic impacts and opportunities for adaptation" funded by Department of Environment, Land,Water and Planning (DELWP)
  • 2017–2019 B Koo, A Pantelous, "RiskLab Projects - Actuarial Sciences" funded by Data61- CSIRO

  • 2017–2019 RJ Hyndman, D Cook, "RiskLab Projects - Econometrics" funded by Data61- CSIRO

  • 2018 RJ Hyndman, "Identifying anomalies in water quality data from Queensland rivers", partnered with QUT and Queensland Department of Environment and Science

  • 2019–2019 RJ Hyndman, Christoph Bergmeir. “DeepForecast: Leveraging forecasts on large scales of related time series”. Funding from Facebook Research

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