CV
Education
- Ph.D. in Machine Learning, University of Sussex, 2017 – 2022
- Thesis: Fair Representations in the Data Domain
- Supervisor: Prof. Novi Quadrianto
- First year part-time, alongside a graduate role at American Express
- B.Sc. (Hons) Computer Science, First Class, University of Sussex, 2013 – 2017
- Faculty prizes for Outstanding Computer Science Student and Best AI Final Year Project
Work experience
- Aug 2024 – present: AI Engineer
- Scoreline (Fantasy Football Hub)
- Own the technical direction of the AI function: the reference architecture for a multi-sport prediction platform, the organisation-wide backend testing standard, and model architecture across team strength, expected minutes and points prediction.
- Defined what a model has to satisfy to reach production — time-based evaluation splits, domain validation metrics, and checks for statistical degeneracy.
- Extended the platform from football to cricket.
- Jan – Sep 2022, Sep 2023 – Aug 2024: Postdoctoral Research Fellow
- Predictive Analytics Lab, University of Sussex
- The second appointment held through the Basque Center for Applied Mathematics (BCAM), Bilbao.
- Developing other researchers and maintaining the lab’s shared engineering practice, alongside contributing to projects as a technical generalist.
- Authored and maintained EthicML, the lab’s fair-ML benchmarking framework.
- Sep 2022 – Sep 2023: Career break
- Travel across Central and South America following completion of the PhD.
- Feb 2020 – Jan 2021: Consultancy Project Lead
- Predictive Analytics Lab, University of Sussex
- Managed a team of five delivering a standalone application for a charity client, built on research into Bayesian Network Structure Learning.
- Sep 2017 – Sep 2018: Technology Graduate
- American Express
- Teams worked:
- Data Architecture — data access APIs and database migrations for a move to microservices
- Enterprise Cloud Platform — advising development teams adopting cloud systems
- Summer 2016: Technology Intern
- American Express
- Duties included: Database Migration
Skills
- Python, PyTorch, scikit-learn, XGBoost, Pandas/NumPy
- Model evaluation and backtesting; experiment tooling (Optuna, Hydra)
- Systems architecture, Postgres, Pulumi, Cloud Run, Pub/Sub
- Constrained optimisation (MILP)
Publications
Talks
Introduction to Fair Machine Learning
Summer School at University of Sussex, Data Intensive Science Centre, Brighton, UK
Does Fairness Come with a Cost?
Conference presentation at Fields Institute, Toronto, Canada
Introduction to Fair Machine Learning
Summer School at Ukranian Catholic University, Faculty of Applied Sciences, Lviv, Ukraine
Tools and tenets for ML and Python
Informal at University of Sussex - Predictive Analytics Lab,