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Personal profile

Biography

Rob J Hyndman FAA FASSA is a Professor of Statistics and Head of the Department of Econometrics and Business Statistics.

His academic qualifications include a Bachelor of Science (Honours) and a PhD from the University of Melbourne. He is an accredited statistician with the Statistical Society of Australia.

He is an elected Fellow of both the Australian Academy of Science, and the Academy of the Social Sciences in Australia.

Rob has researched and consulted with a wide range of business, industry and government clients. His work has included forecasting COVID-19 cases, demand forecasting for the electricity industry, estimating life expectancy for the Australian indigenous population, and forecasting Australian tourism demand.

He is an elected fellow of the International Institute of Forecasters, an elected member of the International Statistical Institute, and a member of the International Association for Statistical Computing, Institute of Mathematical Statistics, and the Statistical Society of Australia. He was editor-in-chief of International Journal of Forecasting from 2005-2018. 

Rob has received several prestigious awards for his research including the 2007 Moran Medal from the Australian Academy of Science, and the 2021 Pitman Medal from the Statistical Society of Australia. He has also been a recipient of the Dean’s Award for Innovation in Learning and Teaching (2020), the Dean's Award for Excellence in Innovation and External Collaboration (2010), the HP Innovation Research Award (2010), the Vice Chancellor's Award for Postgraduate Supervision (2008) and the Dean's award for Excellence in Research (2008).

Rob's research interests include forecasting, time series analysis, computational statistics, anomaly detection, and exploratory data analysis. He has also supervised more than 30 PhD and Masters students, with current projects including energy analytics, data visualization, hierarchical forecasting, anomaly detection and time series forecasting. 

Rob Hyndman's personal website

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

External positions

Director, International Institute of Forecasters

20052018

Research area keywords

  • Business Analytics
  • Machine Learning
  • Forecasting
  • Demography
  • Computational Statistics
  • Time Series
  • Anomaly Detection
  • Exploratory Data Analysis

Network

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