About Me
I am currently exploring some of South East Asia and plan to be back to my research some time in early 2026!
I recently finished my PhD at Imperial College London studying the use of machine learning methods for remote healthcare monitoring in dementia care. Before my doctoral research, I studied BSc Mathematics at UCL and MSc Applied Mathematics at Imperial.
My interests are in theoretical machine learning and building new techniques that are applicable to healthcare.
I am a part of the Translational Machine Intelligence Lab, supervised by Payam Barnaghi.
My Interests
I am interested in all things ML and Maths, but specifically:
- The use of machine learning for science or health
- The use of pretrained models and LLMs in healthcare
- Predicting clinical events from time-series data
- Representation learning of in-home monitoring data
I am also interested in photography, both film and digital.
Publications
Some of the publications I have worked on are listed below:
CV
Education
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Imperial College London, 2021 — 2025
PhD, Machine learning applied to healthcare
Developing machine learning techniques to improve Dementia care through the use of in-home sensors.
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University of Toronto, 2024
3-month Study Placement, Machine Learning and Computational Healthcare
Supervised by Rahul Krishnan: Studying the use of language models in building probabilistic predictive models.
This was funded through the Turing Global Fellows Fund.
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Imperial College London, 2019 — 2020
MSc, Applied Mathematics
Machine Learning, Data Science, Computational Mathematics, Dynamic Systems, Asymptotic Analysis, General Relativity, Vortex Dynamics, Applied Complex Analysis.
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University College London, 2016 — 2019
BSc, Mathematics
Numerical Methods, Probability, Statistics, Mathematical Methods, Financial Mathematics, Algebra, Partial Differential Equations General Relativity, Measure Theory, Complex Analysis, Real Analysis, Fluid Mechanics.
Experience
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Imperial College London, London, 2022 — Current
Teaching Assistant for Machine Learning for Neuroscience
Prepare and present materials, instruct in labs, give tutorials on Pytorch, and mark coursework for the Machine Learning for Neuroscience course.
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London, 2019 — Current
GCSE and A Level Mathematics Tutor
Prepare materials and tutor in GCSE and A Level Mathematics.
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Investec, London, 2019 — 2020
Data and Analytics Graduate
Part of the data and analytics graduate program, I gained experience in the data science, analytics, machine learning, and risk management teams.
Projects
The following are some public projects I am working on:
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AutoElicit
This is a python module that was developed based on the work "AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling".
The module provides a framework for using large language models (LLMs) to elicit expert knowledge in predictive modeling tasks. It includes tools for generating prior distributions.
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Machine Learning for Neuroscience Module
This is a module I am a assistant teacher for at Imperial College London for the MSc Computational Neuroscience.
This module introduces students to the application of machine learning techniques in neuroscience. It covers topics such as neural data analysis, predictive modeling, and the use of deep learning frameworks like PyTorch. The course website provides additional resources and materials for students.
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AVT Python Package
Some of my graphing code, inspired by seaborn's API.
Other projects can be found on my GitHub.