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Machine Learning Engineer

Carbon Re

Responsible for developing and maintaining ML models (PINNs, Kalman Filters) for improved control of cement plants. Lead a range of projects, such as a grant funded project for Department of Energy Security and Net Zero. Created and led the internal bi-monthly journal club within the ML team. A practice the team has kept to this day.

• Research
• Software Development
• Machine Learning

DPhil (PhD) Autonomous Intelligent Machines and Systems

University of Oxford

Machine Learning applied to Sciences

MSc Machine Learning

University College London

Theoretical Machine Learning

• Probababilisitc and Approximate Inference (Gatsby)
• Bayesian Deep Learning
• Applied Machine Learning
• AI for sustainable development
• Supervised Learning
• Reinforcement Learning (DeepMind)
• Proababilistic and Unsupervised Learning (Gatsby)
• Statistical NLP

BSc Natural Sciences

University College London

Astrophysics and Physical Chemistry

Can Reinforcement Learning support policy makers? A preliminary study with Integrated Assessment Models

NeurIPS 2023 Tackling Climate Change with AI Workshop

This paper explored the potential to use Reinforcement Learning to better explore complex climate models and exploit potential feedback loops.

Kolmogorov-Arnold Networks, simply explained

Wrote a Medium article explaining the latest advance in neural networks

• Explained the latest advance in neural networks
• Tested KANs for against symbolic regression

Gaussian Processes, from scratch

Implemented Gaussian processes from scratch using only NumPy

• Implemented from scratch using NumPy
• Explored the fundamentals of Gaussian processes

Physics Informed Neural Networks

A collection of derivations of physics informed neural networks

• Implemented PINNs with Pytorch
• Tested PINNs for parameter estimation