Hi there! 👋🏻

I am a specialist in mathematical optimisation, machine learning, and software engineering with over 15 years of professional experience. I completed my PhD in 2016, investigating efficient approaches to solving scheduling, timetabling, rostering, and assignment problems arising in industry: Optimisation Algorithms for Planning and Scheduling Workplace Training. I was part of the Optimisation Group while at the University of Technology Sydney (UTS).

My professional experience in the energy industry includes electricity and gas price forecasting; mains frequency monitoring, visualisation, and anomaly detection; and optimal control of residential rooftop solar+battery and grid-scale solar+battery+gas setups.

I have experience working in and leading a Data Science team at a multinational software/technology company servicing the global logistics industry. The areas of application primarily involve data analysis and interactive reporting; anomaly detection; recommender systems; revenue forecasting; natural language processing methods for content classification and suggestion; predictive analytics; and vehicle routing. The team works in a fully end-to-end manner: from ideation, to requirements gathering, to research and prototyping, to engineering data pipelines/models/APIs for incremental delivery, to handover.

I have had the pleasure to do some volunteer work over the years. In 2017 I was a Business/Communications panelist at UTS "Your Future in Science and Maths" event, designed to provide students with ideas about where their Science and Maths degrees can take them. In 2020 I developed and presented workshops on Machine Learning at the National Computer Science School. I served as an industry mentor to PhD students in 2022 and again in 2023 as part of the UTS Women in STEM Research (WiSR) Mentoring Program.

When I'm not working, I enjoy spending time with my family, rock climbing, cycling, bush walking, weight lifting, cooking, 3D printing, and playing board games.