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!

Computer Science, AI & Me

Date:

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.

We allowed time for questions which ended up lasting for 30 minutes as the students were so engaged.

Relevant LinkedIn post and feedback of the event can be found here.