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Tomohiro Ando is a Professor of Management (Business Administration) at Melbourne Business School, and a Professorial Fellow at Faculty of Business Economics, University of Melbourne. Before joining Melbourne Business School in 2015, he held a number of continuing and visiting academic and professional appointments at leading institutions, including the University of California, Berkeley, the University of Chicago, the University of California, Los Angeles, the University of Tokyo, and Keio University.
Academic/Professional Services: At the University of Melbourne, he has contributed to academic leadership through service on working committees of the Deputy Vice-Chancellor and Pro Vice-Chancellor, and by supporting the Faculty of Business and Economics in research initiatives such as major grant applications and industry engagement. He served as the director of Centre of Excelence: Big data, AI and Analytics (2020-2025), Academic Convenor of the Melbourne Centre for Data Science (2020-2024), and as Co-Director of the Ph.D. Program at Melbourne Business School, where he also coordinated numerous analytics projects.His research and engagement extend beyond academia to both for-profit and not-for-profit organisations. He recently led a project supporting a not-for-profit organisation that helps women, non-binary, and gender-diverse jobseekers build career readiness and employment outcomes. He has also served on the Diversity and Inclusion Committee and lead the Women in Industry Award Committee. He regularly provides expert service to government, industry, and the academic community, including grant assessments, academic program reviews, award and scholarship selection, tenure and promotion evaluations, and Ph.D. thesis examinations. He served as Associate Editor of Econometrics (2012–2023) and is an active reviewer for leading journals such as Annals of Statistics, Biometrika, Journal of the American Statistical Association, Journal of Econometrics, and Journal of the Royal Statistical Society: Series B. Through consulting and collaboration, he has worked across diverse industries on strategy, marketing, HR, supply chain, and financial analytics, as well as artificial intelligence and machine learning applications.
Research and its Recognitions: His research has been published in leading journals, including Annals of Statistics, Biometrika, Journal of the American Statistical Association, Journal of Econometrics, Management Science, among other distinguished outlets. He has received more than ten competitive research grants from government and funding agencies, including the Australian Research Council and the Japan Society for the Promotion of Science. His paper with Bai (2018), “Selecting the Regularization Parameters in High-Dimensional Panel Data Models: Consistency and Efficiency,” received the Best Paper Award from Econometric Reviews. Another joint paper, Ando and Bai (2023), “Large-Scale Generalized Linear Models for Longitudinal Data with Grouped Patterns of Unobserved Heterogeneity,” published in the Journal of Business & Economic Statistics, was selected as one of twenty articles in the American Statistical Association’s Editor’s Choice Collection. He received the Dean’s Certificate for Research Excellence from the Faculty of Business and Economics in 2017 and 2018, was elected Fellow of the Spatial Econometrics Association in 2023, and is the recipient of the 2024 Academic Excellence Award in Research at Melbourne Business School.
Educational training: At Melbourne Business School, his teaching experience spans a range of subjects, including Analytics for Strategic Management, Case Studies, Consulting, Strategy, and Data Analytics across the Senior Executive MBA, Executive MBA, Full-time MBA, Part-time MBA, and Master of Business Analytics programs. He developed and introduced new MBA courses, Analytics for Strategic Management and Predictive Analytics, to strengthen the integration of data-driven decision-making within business strategy. He has also taught in the Advanced Management Program for senior executives and delivers professional training in Machine Learning for the Australian Government. Beyond university-based executive education, he occasionally conducts customized sessions such as Big Data Analytics for Sustainability. Earlier in his career, he also supervised Ph.D. students while serving in an academic role at the University of California, Los Angeles (UCLA).
Publications:
Research and its Recognitions: His research has been published in leading journals, including Annals of Statistics, Biometrika, Journal of the American Statistical Association, Journal of Econometrics, Management Science, among other distinguished outlets. He has received more than ten competitive research grants from government and funding agencies, including the Australian Research Council and the Japan Society for the Promotion of Science. His paper with Bai (2018), “Selecting the Regularization Parameters in High-Dimensional Panel Data Models: Consistency and Efficiency,” received the Best Paper Award from Econometric Reviews. Another joint paper, Ando and Bai (2023), “Large-Scale Generalized Linear Models for Longitudinal Data with Grouped Patterns of Unobserved Heterogeneity,” published in the Journal of Business & Economic Statistics, was selected as one of twenty articles in the American Statistical Association’s Editor’s Choice Collection. He received the Dean’s Certificate for Research Excellence from the Faculty of Business and Economics in 2017 and 2018, was elected Fellow of the Spatial Econometrics Association in 2023, and is the recipient of the 2024 Academic Excellence Award in Research at Melbourne Business School.
Educational training: At Melbourne Business School, his teaching experience spans a range of subjects, including Analytics for Strategic Management, Case Studies, Consulting, Strategy, and Data Analytics across the Senior Executive MBA, Executive MBA, Full-time MBA, Part-time MBA, and Master of Business Analytics programs. He developed and introduced new MBA courses, Analytics for Strategic Management and Predictive Analytics, to strengthen the integration of data-driven decision-making within business strategy. He has also taught in the Advanced Management Program for senior executives and delivers professional training in Machine Learning for the Australian Government. Beyond university-based executive education, he occasionally conducts customized sessions such as Big Data Analytics for Sustainability. Earlier in his career, he also supervised Ph.D. students while serving in an academic role at the University of California, Los Angeles (UCLA).
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