About Me
I am a student at Imperial College London pursuing a PhD focused on developing machine learning techniques for the extraction of clinical insights from in-home monitoring data, mostly focused on people living with Dementia.
My interests are in theoretical machine learning as well as building new techniques that are applicable to healthcare.
I am a small part of the Translational Machine Intelligence Lab, supervised by Payam Barnaghi.
My Interests
I am curious about all things ML and Maths, but specifically:
I have worked in the following areas:
- The use of pretrained models in healthcare monitoring
- Learning from noisy data
- Predicting clinical events from in-home time-series data
- Generative modeling
- Meta-learning
- Continual learning
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.
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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.
Publications
Some of my key works are listed below:
Projects
The following are some projects I am working on:
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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. I also put the course website together, which is a work in progress!
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AVT Python Package
Some of my graphing code, inspired by seaborn's API.
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AML Python Package
Some of my Machine Learning code.
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SKU Python Package
Sci-kit Learn Utils add extra functionality to pipelines, and allow for more complex machine learning training and testing. It also includes some extra functionality for hyper-parameter optimisation.
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Dcarte-Transform Python Package
Dcarte-Transform package adds extra functionality to dcarte, an in-house python package designed for loading the UK DRI Minder data. Specifically Dcarte-Transform adds extra abilities for machine learning research. It also includes a feature engineering recipe for easy access to engineered features.
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PDUtils Python Package
Pandas Utils adds extra functionality to DataFrames.