Research Fellow, Monash Centre for Occupational and Environmental Health, School of Public Health and Preventive Medicine, Monash University.
Research focus: improving public health and patient outcomes using advanced statistical models and epidemiological methods on large-scale clinical data. This includes understanding patterns and impacts of acute and chronic health conditions using hospital data, clinical registries and occupational cohort registries datasets.
Dr Win Wah is a recipient of a 2024 Early and Mid-Career Researcher Award for novel use of data. This award recognises early and mid-career researchers for excellence in their field. Monash Partners spoke to Win upon accepting this award.
Can you tell us about yourself, your research and career journey to date?
I am a Research Fellow at Monash University, based at the Monash Centre for Occupational and Environmental Health. I have a background as a medical doctor (MBBS) and double masters’ in public health in the UK and Denmark. My PhD thesis focused on developing innovative statistical models for Bayesian spatial and spatial-temporal modelling in cancer incidence and outcomes in Australia. Since completing my master’s degree, I have developed and applied different statistical models and epidemiological methods to large-scale, longitudinal clinical, epidemiological, and spatial-temporal datasets. I have also provided statistical advice to clinicians, medical students, and master’s and PhD students by assisting with the research study design and analysis, supporting research paper writing, and contributing to teaching evidence-based medicine lectures and biostatistics courses. I have delivered evidence-informed research outputs by authoring several peer-reviewed publications in international clinical or public health research journals. My post-doctoral research has focused on integrating and utilising diverse datasets to inform innovative methodologies and applications in occupational and environmental health.
Why is support of early and mid-career researchers so important?
Support for early and mid-career researchers is crucial because these stages are pivotal for developing innovative ideas, establishing independent research agendas, and building the skills needed to address complex public health challenges. Providing resources, mentorship, and opportunities to early and mid-career researchers helps them grow into influential contributors in their fields and navigate the challenges of building sustainable research careers while making meaningful contributions to science, health, and society.
What kind of support was the most beneficial to you/or you felt you needed as an early and mid-career researcher and what did it mean to you?
As an early-career researcher, the most beneficial support for me was a combination of mentorship, funding opportunities, and access to collaborative networks. This support has been invaluable to me. It allowed me to develop confidence in my contributions and provided me with the tools to translate research ideas into impactful outcomes, which have contributed to evidence-informed public health policies and clinical practices.
Why do you think awards like this are important for Early and Mid-Career Researchers?
Awards like this are vital for early and mid-career researchers as they provide recognition, motivation, and validation during crucial stages of their careers. They acknowledge their contributions, showcase impactful research, and open doors to funding, collaborations, and leadership opportunities. By amplifying visibility and reaching key stakeholders, such awards drive real-world applications of research. They also inspire confidence in recipients and the next generation, fostering a sense of community and encouraging ambitious goals. Ultimately, these awards highlight the importance of early and mid-career researchers to innovation and knowledge growth, motivating them to achieve even greater impact.
What are your future aspirations for your research/career?
My future aspirations focus on advancing the epidemiology, prevention, and management of health conditions while improving population health. I aim to achieve this through the innovative use of health data by developing and applying standard and advanced statistical models, epidemiological methods, Bayesian methods, and machine-learning approaches that will inform evidence-based clinical practices and public health policies on both national and global levels. My goal is also to bridge methodological innovation with practical applications, ultimately contributing to improved clinical practices and public health policies worldwide.
