Overview

Working at the intersection of research, software, and decision-making

My background cuts across health, analytics, and AI engineering. That mix has shaped how I work: I like research that can survive contact with real constraints, and systems that do more than demo well.

I completed a Master of Analytics in Health at Massey University, am concurrently undertaking a Master of Computer Science in AI at Monash University, and will begin a fully funded PhD at The University of Queensland in April 2026. Both universities have approved concurrent enrolment in the Monash masters and the UQ PhD.

The throughline is consistent: take messy domains, structure them well, and build models, pipelines, and tools that lead to better decisions.

At a glance

  • Research Digital twins, AMR risk, forecasting
  • Builds ML pipelines, internal tools, analytics systems
  • Strength Turning ambiguous problems into shipped systems
  • Based across New Zealand and Australia
15.9% reduction in MAE for 24-hour building energy forecasts See proof 90%+ faster nutrition formulation iteration in industry workflows See proof 150+ health claims supported through structured data substantiation See proof

Focus Areas

Three areas where I do my best work

01

Applied machine learning

From forecasting and transfer learning to production workflows, I enjoy building models that are judged by practical usefulness, not novelty alone.

02

Digital twins for complex systems

I am especially interested in digital twins as a way to integrate multiple sectors, uncertain signals, and high-impact decisions into one workable modelling frame.

03

Data products that actually get used

My industry work has centred on dashboards, internal tooling, pipelines, and decision-support systems that teams adopt because they remove real friction.

Selected Proof

Work that shows how I think and what I ship

Industry

AI systems for nutrition formulation and substantiation

At Radix Nutrition, I led data science work spanning optimisation, claims substantiation, and internal product tooling. The result was faster iteration, lower formulation costs, and decision support adopted across R&D and operations.

  • Optimisation
  • Internal tools
  • Decision support

Build

Open technical presence

I use this site, GitHub, and YouTube to document projects, share technical lessons, and make my thinking legible. I care about being able to show the work, not just list it.

Journey

A non-linear path that sharpened the work

I did not begin in computer science. Coming from health, sport, and human performance gave me a bias toward problems with real-world consequences, messy variables, and multidisciplinary stakeholders.

That perspective still shapes my work today. I am most energised when a project needs both technical depth and translation across disciplines.

The University of Queensland
SAAFE CRC — Solving Antimicrobial Resistance in Agribusiness, Food & Environments
PhD — The University of Queensland & SAAFE CRC
2026-2029

PhD in Artificial Intelligence, The University of Queensland

Fully funded RTP scholarship and SAAFE CRC top-up focused on cross-sectoral digital twins for AMR risk assessment.

Robert Spencer at Radix Nutrition
Radix Nutrition — Data Analyst, then Lead Data Scientist (Apr 2024–Oct 2025)
2024-2025

Radix Nutrition — Data Analyst, then Lead Data Scientist

Joined as the first technical hire (Data Analyst, Apr 2024–Jan 2025), building data infrastructure and internal tools; promoted to Lead Data Scientist (Jan–Oct 2025), owning end-to-end AI and analytics for formulation, substantiation, and decision support.

Monash University
Monash University — Master of Computer Science in Artificial Intelligence
2024-2027

Master of Computer Science in Artificial Intelligence, Monash University

Part-time, online; deepens formal AI training alongside research and industry work. Completed nine of twelve units with remaining coursework planned around doctoral milestones.

Group photo: Dr Mikael Boulic, Dr Hennie van Heerden, Robert Spencer, Dr Surangika Ranathunga, and A/Prof Teo Susnjak outside the School of Built Environment Laboratories at Massey University
With supervisors — Dr Mikael Boulic, Dr Hennie van Heerden, Robert Spencer, Dr Surangika Ranathunga, A/Prof Teo Susnjak (left to right) — Master of Analytics in Health, School of Built Environment Laboratories, Massey University, February 2025
2023-2024

Research Assistant in AI, Massey University

Transformer-based forecasting and transfer learning for building energy prediction; first-author Q1 publication in Energy and Buildings.

Robert Spencer at Massey University graduation
Master of Analytics in Health — Massey University, 2024
2023-2024

Master of Analytics in Health, Massey University

Completed with Distinction; health analytics and methods training concurrent with the RA appointment.

Robert Spencer at Waikato University graduation
Bachelor of Health, Sport & Human Performance — double majors in Human Performance Science and Community Health — The University of Waikato, 2022
2020-2022

Bachelor of Health, Sport & Human Performance, The University of Waikato

Double majors in Human Performance Science and Community Health — the grounding in health, messy real-world data, and stakeholder context that still informs how I frame technical work.

Online Presence

I share the process as well as the outcomes

On YouTube and online, I talk about career transitions into AI, the tools and models I use day to day, and the practical side of building technical capability over time.

The throughline is the same as my research and engineering work: curiosity, usefulness, and a bias toward making complex ideas easier to work with.

Where to follow my work

Connect

Interested in research, collaboration, or applied AI work?

I'm always happy to connect with people working in artificial intelligence, health, complex systems, sustainability, and thoughtful technical communication.

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