# Meet the Team

LocoLLM is an open-source project out of Curtin University, Perth. It started as one person's side project and is designed to grow through student contributions semester by semester.

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## Active Members

### Michael Borck -- Project Lead

Michael is a Lecturer and AI Facilitator in the School of Marketing and Management at Curtin University. He teaches AI-related units at both undergraduate and postgraduate level, and spends a lot of his time helping colleagues across the university figure out how to actually use AI tools effectively.

Before academia, he spent over a decade in the Royal Australian Navy in technical and leadership roles: software developer, analyst programmer, systems administrator, project manager, IT manager. That background in defence and government means he's spent a career working in environments where things have to work reliably, securely, and under constraints. That mindset carries through to LocoLLM's design philosophy.

His research background is in machine learning and computer vision, with a PhD from Curtin focused on feature extraction from multi-modal mobile mapping data. He also holds degrees in computing (ANU), mathematics (QUT), and business (Curtin). The mix of maths, computer science, and business is part of why LocoLLM sits at the intersection of technical AI work and practical accessibility.

Michael is a Certified Professional of the Australian Computer Society, a member of the IEEE Computer Society, and co-founder of the Business AI Research Group at Curtin. He has published six open-source books on AI integration under MIT license, all freely available on GitHub.

He runs the lab hardware, sets the project direction, designs the training curriculum, and writes most of the documentation. He also built the 3D-printed fan shroud cooling the P100 in Burro, because that's the kind of project this is.

**Contact:** [GitHub](https://github.com/michael-borck) | Curtin University

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*This section will grow. LocoLLM is designed so that each semester's student cohort contributes adapters, benchmarks, router improvements, and documentation. Active members are listed here while they're contributing to the project.*

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## Past Members

*No past members yet. As contributors move on from Curtin or shift their focus, they'll be recognised here for their contributions to the project.*

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## Contributing

You don't need to be at Curtin to contribute. LocoLLM is open source under the MIT license. If you want to train an adapter, improve the router, run benchmarks, or write documentation, see [Getting Started](why-locollm.md) or open an issue on [GitHub](https://github.com/michael-borck/loco-llm).
