Dr Amirul Islam
- Faculty of Health, Arts & Design
- School of Health Sciences
- Department of Statistics Data Science and Epidemiology
- ATC 928 Hawthorn campus
- ORCID profile
- ORCID profile
Amirul received his PhD from the University of Queensland in 2001. He was a research-academic staff at National University of Singapore (2001-2002), University of Western Australia (2003-2004)and recently at the University of Melbourne (2005-2013) before joining Swinburne in 2014 in the in the Dept of Statistics, Data Sciences and Epidemiology. Amirul's research foci are in Epidemiology, Biostatistics and Genetic Statistics; large population-based cohort studies, cardiovascular disease, risk prediction, Patterns analysis, Multinomial and Spline Regression, Path analysis, and Rasch analysis for items response theory. His recent research projects include: (i) Bangladesh population-based Dieabetes and Eye Studies (BPDES), (ii) Psychological distress and quality of life in rural Bangladesh, (iii) Chronic diseases including diabetes and one of it's complications diabetic retinopathy in a rural district Narail in Bangladesh.
Amirul has published 113 peer-reviewed articles as a senior author or a co-author. He has more than 40 published abstracts or presentations in many prestigious conferences including the World Diabeted Conference. Amirul is an Academic Editor of one of the mostly cited Open Access Journals- Public Library of Science (PLOS) One. He is also a section editor (Epidemiology and Biostatistics) of Eye which the official Journal of the Royal College of Ophthalmology.
Public and Environmental Health; Biostatistics; Epidemiology; Health research design
PhD candidate and honours supervision
Higher degrees by research
Accredited to supervise Masters & Doctoral students as Principal Supervisor.
PhD topics and outlines
Chronic condition and quality of life in Riyadh in Saudi Arabia
Managing aggressive behaviour in adults with autism spectrum disorders for nurses in hospital environments. A pilot intervention in tertiary-care hospitals in Victoria, Australia.
Predictive Ability and Diagnostics for Categorical Response Models with the Application on Quantitative Modelling for diagnosis of Malaria disease in East Nusa Tenggara Indonesia
Statistical Methods for Risk Prediction Models with Multi-Categories Response Variables with Applications to Cost-Effective Diagnosis of Malaria in East Nusa Tenggara Province Indonesia.
Available to supervise honours students.
Honours topics and outlines
Sources of income, daily livings and dependency in older adults in a rural district in Bangladesh: Data from a prospective cohort study: The project has ethics approval. Data are from 2425 adults. Results can definitely be published
Fields of Research
- Biostatistics - 010402
- Epidemiology - 111706
- Ophthalmology And Optometry - 111300
Public and Environmental Health;Biostatistics;Epidemiology;Health research design
- 2016, Swinburne, VC 2016 Teaching Excellence Award in Higher Education, Swinburne University of Technology
- 2012, National, Teaching Award , University of Melbourne
Also published as: Islam, Amirul; Islam, A.; Islam, F.; Amirul Islam, F. M.; Amirul Islam, Fakir M.; Amirul Islam, Fakir Mohammad; Amirul, F. M. Islam; Amirul-Islam, F. M.; Amirul-Islam, Fakir M.; Islam, A. F. M.; Islam, Amirul F. M.; Islam, F. M.; Islam, F. M. A.; Islam, F. M. Amirul; Islam, Fakir Amirul; Islam, Fakir M. A.; Islam, Fakir M. A. Amirul; Islam, Fakir M. Amirul; Islam, Fakir Mohammad Amirul
This publication listing is provided by Swinburne Research Bank. If you are the owner of this profile, you can update your publications using our online form.
Recent research grants awarded
- 2017: Development of a diabetic retinopathy detection and managementprogram for a rural district Narail of Bangladesh through a telemedicine platform. *; Funding for research in Tropical Ophthalmology
- 2016: Optimising technology to measure functional vision, mobility and serviceoutcomes for people with low vision or blindness *; Melbourne-Sarawak Collaborative Research Development Scheme
* Chief Investigator
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