Academic Background

I am a PhD candidate in Health Data Science at the University of Cambridge, on the Health Data Research UK-Turing Wellcome PhD Programme in Inouye Lab, supervised by Angela Wood, Mike Inouye, and Sam Lambert. My thesis focuses on assessing and improving fairness in clinical prediction algorithms, including in polygenic risk scores and machine learning for fair medical risk prediction.

Before my PhD, I was a DeepMind Scholar in MPhil Advanced Computer Science at the Cambridge Computer Laboratory, supervised by Neil Lawrence. My research focused on the fairness of bias and variance errors in machine learning models. I am a member of Clare Hall College.

I completed my first-class BSc in Computer Science at the University of Birmingham, with visiting student placements at the University of British Columbia and the University of Waterloo.

After my undergraduate degree, I worked as an AI research consultant, where I joined a start-up company building artificial intelligence software for autonomous vehicles. Here, my research was on the implementation and optimisation of multi-objective route planning algorithms. For this work, I have two patents: Vehicle Route Guidance and Target Speed Optimisation.

Publications

• Axes of prognosis: Identifying subtypes of COVID-19 Outcomes: Working with COVID-19 data from Wuhan, China, I collaborated with Emma Whitfield on this project supervised by Honghan Wu to identify and predict nuanced subtypes of COVID-19 prognosis. It was published at the American Medical Informatics Association Annual Symposium 2021 and can be found here and my presentation can be found here.
• Achieving Net Zero within the NHS: System-wide transition to greener, sustainable care: As part of the University of Cambridge ThinkLab, I worked on a project with the NHS to improve the delivery of the NHS Green Plan, by specifying actionable solutions and shaping future policies. Our report can be read here.

Projects

• Statistical Methods for Health Equity Organiser: As a statistical methods co-lead at Data Science for Health Equity, we organise seminars, run a reading group, and conduct research on statistical methods for health equity. We run a yearly symposium on Statistical Methods for Health Equity.
• Reinforcement learning for healthcare: I worked on a project wherein I explored various reinforcement learning paradigms with a particular focus on offline RL and how this can be applied to the problem of multimorbidity trajectory modelling. Chris Yau supervised me on this project.
• Fairness and the bias-variance trade-off: For my MPhil thesis, I explored bias and variance errors in ML automated decision making in the context of fairness, using data on criminal recidivism.
• Multi objective journey optimisation: As part of my R&D job, in conjunction with the University of Birmingham, I worked on a project to create an AI journey optimisation system for autonomous vechicles for for my final-year BSc project, supervised by Dave Parker.

Invited Talks

• Cambridge Festival (2024): I gave a talk for the public on Artificial Intelligence: With great power comes great responsibility as part of the Cambridge Festival.
• HDR UK Cambridge Community Meeting (2023): Here I spoke on Understanding and Improving Fairness in Medical Risk Prediction.
• Cambridge Festival (2023): Public talk on Fairness in medical risk prediction algorithms. Recording here.
• HDR UK Doctoral Immersion Week (2023): Guest seminar on Algorithmic fairness in cardiovascular disease risk prediction at the HDR UK Doctoral Immersion Week on Fairness in healthcare data modelling.
• HDR UK Bimonthly Webinar (2021) : I joined Peter Diggle in conversation on running and completing a PhD in the time of COVID in the HDR UK bimonthly webinar.
• UCL MedTech (2021): I spoke at the UCL MedTech conference, to share my experiences and research in the hope to inspire undergraduate students at UCL.

Teaching

• Artificial Intelligence: Theory, Responsibility, and Sustainability (2023): I co-designed and delivered this course for high school students. My sections focused on on AI for sustainable development, climate change, and AI in the Global South.
• MPhil Population Health Sciences (2023): Teaching assistant on the Advanced Statistics for Epidemiology module.
• High school Computer Science (2017-2022): Personalised tutoring for GCSE and A-Level; teaching computer science in schools years 7-13.

Personal Interests

I am a member of Clare Hall Choir. Elsewhere, I have been a soloist, lead vocalist, backing vocalist, and chorister in genres ranging from rock to classical!

I co-founded the University of Cambridge Allotment Society, where we built a community to grow fruit and vegetables sustainably, as well as donating to local charities. This included writing grant applications for funding, managing the day-to-day running of the allotment, and social media management.

I adore travelling, especially exploring nature. My other hobbies include hiking, dancing (ex-UK freestyle display team), yoga, digital art (freelance digital artist), and photography. I also train in Kung Fu and row in Clare Hall Boat Club, where I am social secretary.