Biography
I am an early-career clinical machine learning researcher, currently working as a Lecturer of Health Data Science at the Centre for Big Data Research in Health, UNSW. My academic background is diverse, spanning applied Artificial Intelligence (AI), Electrical and Electronic Engineering, and Materials Science. I completed my PhD at the Anglia Ruskin University, UK, in 2019 with the support of an EU scholarship. My doctoral research focused on...view more
I am an early-career clinical machine learning researcher, currently working as a Lecturer of Health Data Science at the Centre for Big Data Research in Health, UNSW. My academic background is diverse, spanning applied Artificial Intelligence (AI), Electrical and Electronic Engineering, and Materials Science. I completed my PhD at the Anglia Ruskin University, UK, in 2019 with the support of an EU scholarship. My doctoral research focused on developing intelligent systems for pathological tests, utilising computer vision and machine learning on point-of-care platforms.
With over a decade of experience in the digital healthcare sector, I served as a postdoctoral researcher at the University of Oxford, UK, primarily focusing on machine learning with electronic health records in the Computational Health Informatics (CHI) lab. Before my time at the CHI Lab, I worked as a research fellow at the Medical Technology Research Centre (MTRC), Anglia Ruskin University, contributing to projects involving AI for unmet healthcare and social needs. Additionally, I advocate for healthcare accessibility through philanthropy and serve as a guest lecturer at Nottingham Trent University, UK, addressing ethical, legal, and social dimensions of Big Data Analytics. I also hold the position of Health and Technology Fellow at the Youth Policy Forum in Bangladesh.
My Grants
Current project(s):
Trajectories for chronic disease management plans use in primary care in adults with cardiovascular disease. Funded by the 45 and Up Study Cardiovascular Research Grant from the National Heart Foundation of Australia (AUD 65,000, CIC), 2024-2025.
Previous grants:
- SBRI- Healthy Ageing Social Ventures feasibility studies, Innovate UK, 2022-23.
- SBRI: Improving Multimorbidity Acute Care Using Data Analytics, phase 1, Innovate UK, 2021.
- Research Grant of Capacity Utilization Programme under Special Allocation for Science and Information & Communication Technology, Ministry of Science and Technology, Bangladesh, 2011-2012
Education grant(s):
2024: EF Grant, UNSW (AUD 3,000)
2024: CDI Grant, UNSW (AUD 2,500)
My Qualifications
- PhD in Applied AI, Anglia Ruskin University (ARU), United Kingdom (2019).
- MPhil in Materials Science, Bangladesh University of Engineering and Technology (BUET), Bangladesh (2014).
- BSc in Electrical and Electronic Engineering, Ahsanullah University of Science and Technology (AUST), Bangladesh (2011).
My Awards
Notable Awards:
- Norman Tanner Prize and the Glaxo Travelling Fellowship, The Royal Society of Medicine, London, UK, September 2023.
- Best International Research Paper, Association of Researchers in Construction Management (ARCOM) Thirty-third Annual Conference, Cambridge, UK, September 2017.
- Prof Muhammad Harunur Rashid Paper Award (Runner-up), 3rd International Conference on the Developments in Renewable Energy Technology, IEEE, Dhaka, Bangladesh, May 2014.
Scholastic Grants and Achievements:
- PhD Scholarship: Erasmus Mundus Action 2 FUSION project.
- Undergraduate Merit Scholarship: Three-time recipient of Tuition Fee Awards at AUST.
My Research Activities
I am fascinated by diverse domains of machine learning that specifically target real-world applications. Currently, my research pursuits are centred around the following areas:
- Survival-aware machine learning
- Intersection between survival analysis and treatment effect estimation
- Ethical AI
My Research Supervision
Supervision keywords
Currently supervising
PhD student from ARU
My Teaching
As part of the MSc Health Data Science team, I am currently convening and teaching the course(s):
Computing for Health Data Science - HDAT9300.