About
Sinan Koparan
PhD Researcher specialising in Sports Data Science & Artificial Intelligence, building ML solutions that drive real-world impact in sport participation and performance.
At a Glance
| Current Role | PhD Candidate, Sports Data Science & AI |
| Programme | Next Generation Graduates Program (NGGP) |
| Partners | CSIRO Data61 | Rugby Australia | NSW Institute of Sport |
| Focus Areas | Machine Learning, LLMs, Sports Analytics, Data Science |
What I Do
I develop data-driven solutions that help sporting organisations make better decisions. My work sits at the intersection of machine learning, sports science, and real-world application—transforming complex datasets into actionable insights.
PhD Research — Community Sport Analytics
CSIRO Data61 & Rugby Australia
Building predictive models to understand what makes community sports clubs thrive. My research directly informs how national sporting organisations allocate resources to improve retention, grow participation, and ensure long-term sustainability across thousands of clubs.
- Developing ML pipelines to analyse participation patterns across large-scale datasets
- Creating interpretable models that translate to practical resource allocation strategies
- Collaborating with industry partners to ensure research delivers measurable outcomes
Applied AI Research — Elite Sport Performance
NSW Institute of Sport (NSWIS)
Leading the technical development of LLM-powered tools for coaches and athletes. Designing systems that automate content analysis and accelerate insight generation in high-performance sport environments.
- Architecting RAG systems for domain-specific knowledge retrieval
- Building automated analysis pipelines that reduce manual review time
- Deploying practical AI tools in real coaching workflows
Technical Skills
Languages & Frameworks Python, JavaScript, TypeScript, R, SQL
Machine Learning & AI Scikit-learn, PyTorch, LangChain, OpenAI API, Google Gemini API, RAG Systems
Data & Analytics Pandas, NumPy, Statistical Modelling, Data Visualisation, ETL Pipelines
Development React, Node.js, Express, Git, REST APIs, Full-Stack Development
What Drives Me
I’m motivated by problems that demand both technical depth and practical impact. Over the past 18 months, I’ve developed a deep focus on Large Language Models—not just understanding how they work, but building applications that solve real problems.
My projects page showcases tools I’ve built: from automated research paper aggregation to AI-powered document extraction to RAG-based knowledge systems. Each project reflects my approach: identify a genuine need, build a working solution, and iterate based on real usage.
I thrive in environments where rigorous research meets practical implementation—where the goal isn’t just to publish, but to build things that work.
Let’s Connect
I’m always open to discussing research collaborations, technical challenges, or opportunities where data science and AI can make a meaningful difference.