PhD Student, Senior Resident & Student Ambassador at the University of Bristol

News

2024-02-15

Published Euclid preparation. Measuring detailed galaxy morphologies for Euclid with Machine Learning on Arxiv!

2024-02-15

Published Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting on Arxiv!

2024-02-15

Presented a talk on 'Optimizing Data Efficiency: Using Active Learning Strategies and the QUEST Method for Efficient Classification and Labeling in Large Datasets' at the Galaxies & AGN with the First Euclid Data and Beyond in Bologna.

2023-03-28

Presented a pecha-kucha talk on my PhD research at the Interactive AI CDT Spring Research Conference.

2022-12-06

I recently finished my 6 month placement as an AI Research Engineer at Imagination Technologies where I was working on Sparsity, Lidar data and CUDA implementations of custom DL layers. A patent for my work has been submitted and is awaiting approval.

2022-04-27

Presented a talk on 'Using active learning to create reliable and robust classifiers for Euclid' at the 2022 Annual Euclid Consortium Meeting in Oslo.

2022-03-30

Presented a pecha-kucha talk on my PhD research at the Interactive AI CDT Research Showcase.

2022-02-23

From June, I will be starting a 6 month placement as an AI Research Engineer at Imagination Technologies!

2021-12-16

Presented a talk on 'Using active learning to create reliable and robust classifiers for Euclid' at the 2021 Euclid Consortium UK Meeting.

2021-10-18

Presented research poster of AstronomicAL at the 2021 IAP Colloquium which was dedicated to critical analysis of Machine Learning methods in Astronomy.

2021-09-03

Published AstronomicAL: an interactive dashboard for visualisation, integration and classification of data with Active Learning in the Journal for Open Source Software!

Talks and Presentations

The Hidden Difficulties of Machine Learning

November 10, 2021

Talk, Access To Bristol, Bristol, UK

On-campus presentation to 30 local sixth form students who intend to study Engineering at university. This presentation immediately followed the AI & ML:Cutting Through The Hype talk and was used to show how ML tasks are often not as straightforward as they may seem. This talk is very interactive with the aim that the students are able to discover the problems that appear themselves and see why certain solutions may not be sufficient for a problem.

AI & ML: Cutting Through The Hype

July 22, 2021

Talk, Sutton Trust Summer School, Bristol, UK

Webinar presented to 60 sixth form students who intend to study Engineering at university. The presentation starts with an introduction to what Computer Science is (and is not) like at university. Following this, the (very brief) foundations of what Machine Learning and AI really are. Unfortunately, the adoption of these tools has led to a large amount of over-exaggeration and overuse of certain buzzwords throughout the industry, making it seem like companies are doing super complicated and ground-breaking things when most of the time they’re doing nothing more than the Maths the students use in their A-Level studies. I also show the Dot-Com Boom and the AI Winter as examples for how overhyping can be damaging for research progress and the economy.

Computer Science, AI & Me

July 03, 2021

Talk, Insight into University - Engineering Development Trust, Bristol, UK

Webinar presented to over 100 sixth form students. The presentation began with telling the students about my academic life and how I went from a widening participation background to studying for a PhD at Bristol. This led to an introduction to what Computer Science is (and is not) like at university. The final part gave the students the (very brief) foundations of what Machine Learning and AI really are. Unfortunately, the adoption of these tools has led to a large amount of over-exaggeration and overuse of certain buzzwords throughout the industry, making it seem like companies are doing super complicated and ground-breaking things when most of the time they’re doing nothing more than the Maths the students use in their A-Level studies.

Presentation on MLOps and Kubeflow

December 03, 2020

Talk, University of Bristol, Bristol, UK

Lecture on MLOps and Kubeflow presented to 1st Year Interactive AI CDT students on Interactive AI Team Project unit. This talk aims to give a very accessible introduction to the need for MLOps by linking to the similarities of the development of DevOps systems. By looking into the effect of increasing scale (team size, customer base or project size), students will see potential problems with how their current development practices may not be sustainable when applied to ML projects at an industry-scale. Finally, there is a brief overview of Kubeflow and its main components, showing why they are useful and how they can potentially solve the previous issues.