His work spans from analysing national dietary data to developing frameworks for the ethical implementation of Large Language Models (LLMs) in healthcare settings.

His research centres on the intersection of public health and environmental sustainability. As lead author, he has published two complementary studies in the past year examining relationships between demographic factors and dietary greenhouse gas emissions. The first analysed nearly two million New Zealand household food purchases to assess these relationships in a national context. Building on this, he led a narrative review synthesising findings from studies across affluent Western nations, examining how demographic characteristics influence dietary emissions patterns. This body of work combines both large-scale data analysis and comprehensive literature synthesis to better understand the social determinants of dietary environmental impact.

Since joining Synergia in 2022, Eli has led data analytics initiatives for major health initiatives across Auckland, including Tū Whakaruruhau (the Auckland Wellbeing Collaborative) and the Palliative Outcomes Initiative (POI). He applies statistical methods to answer critical questions about health service delivery and outcomes—for example, examining how primary mental health initiatives influence self-reported wellbeing measures and secondary service referrals, with particular attention to equity between Māori and non-Māori populations.

Eli is currently leading Synergia’s internal work on Large Language Models (LLMs), developing ethical frameworks for their use while implementing them to automate workflows and build sophisticated web applications that surface insights from data. On behalf of Synergia, he has also created resources to support New Zealand health service providers in responsibly adopting generative AI tools through the “AI Deep Dive” learning series, and has presented to a dozen different organisations on this topic in the past year.
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