EPSRC Doctoral Prize Fellow at the University of Bristol

News

2024-10-03

I have successfully defended my thesis and have been awarded my PhD in Interactive AI!

2024-09-19

Published Euclid preparation - XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning in Astronomy & Astrophysics!

2024-06-03

I have started my 2-year Fellowship at the University of Bristol working on Diffusion Models and Digital Twins!

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 Journal for Open Source Software!

CV

Education

Interactive AI PhD

University of Bristol, 2019-2024

Areas of Research:

Computer Science MEng

University of Bristol, 2015-2019

Units Include:

Skills

Programming

Most Proficient:

Python

Experience with:

C++ • CUDA • BASH • Jekyll

Libraries

Most Proficient:

PyTorch • SKLearn

Experience with:

PyBind • Tensorflow • WandB • Astropy

Software

Most Proficient:

Adobe Maya

Experience with:

Blender

Research

Projects & Achievements

AstronomicAL: an interactive dashboard for visualisation, integration and classification of data with Active Learning

Developed as part of my PhD thesis

AstronomicAL is a human-in-the-loop interactive labelling and training dashboard that allows users to create reliable datasets and robust classifiers using active learning. The system enables users to visualise and integrate data from different sources and deal with incorrect or missing labels and imbalanced class sizes by using active learning to help the user focus on correcting the labels of a few key examples. Combining the use of the Panel, Bokeh, modAL and SciKit Learn packages, AstronomicAL enables researchers to take full advantage of the benefits of active learning: high accuracy models using just a fraction of the total data, without the requirement of being well versed in underlying libraries.

AstronomicAL resulted in a publication in the Journal for Open Source Software. More info can be found here.

Passive Information Extraction System (P.I.E.S)

Interactive AI Group Project - Developed for L.V Insurance

Based on the requirements of L.V, our group developed a backend question-answering system which assists the service desk staff in extracting relevant information from customer phone calls. The Passive Information Extraction System (P.I.E.S) analyses a live transcript of the conversation to improve customer experience by allowing service desk operators to concentrate on the human interaction rather than data collection. The system processes all information from the conversation in real time and enters it on the system while the call operator concentrates on the customer’s welfare. All information extracted can be verified by the call handler ensuring vital information is never missed or incorrectly identified. The system uses a BERT model trained on the Stanford Question Answering Dataset (SQuAD). One of the main advantages of the implemented system is the ability to produce more training data with every call the company handles. With thousands of calls per week, it is possible to generate a sufficiently large labelled dataset of transcripts specific to the company’s requirements. This allows for routine updating of the Question and Answer model to ensure it is performing to a high standard.

Multiplayer Rhythm-Based Dungeon Crawler

Games Project - Awarded Best 3rd Year Group Project

For a 3rd Year group project, we created a game called Rave Cave. It is a multiplayer rhythm-based dungeon crawler where large amounts of players rock out simultaneously in time to the music. Players must cooperate with their team to solve puzzles and complete complex button sequences - all in time to the beat of the music. We created our own game engine in C++ by integrating our custom code with external libraries.

Gold Crest Award & Engineering Education Scheme

The Royal Navy

The Engineering Education Scheme is a scheme run by the Engineering Development Trust, which links teams of 4 sixth form students with companies to work on an engineering problem. Our company was The Royal Navy and, over a year, we developed a replacement for a leaking Mantlet Bag. Our solution has been taken on board by the Ministry of Defence, and they have assigned their lead contractor to put our solution to further testing.

Work experience

Imagination Technologies | AI Research Engineer

June 2022 - December 2022

During this 6-month internship, I worked on creating custom CUDA implementations for Deep Learning Inference on high sparsity data. My novel implementation of sparse convolutions can compete with SOTA latency on Lidar classification networks. The code has been developed to be able to run on any general-purpose hardware. The project has since been submitted for five patents.

University of Bristol | Student Ambassador

December 2016 - Present

I am also currently a student ambassador for my university. I participate in outreach programmes for school students such as Access to Bristol and University Summer Schools, as well as open days and campus tours. My role often requires me to solely lead a large group of students, requiring me to be independent and have strong communication and presentation skills.

University of Bristol | Senior Resident

September 2018 - September 2021

I was a live-in peer mentor within halls of residence. I provide advice to individual students and contribute to inclusive community-building events and activities in partnership with the student-led JCRs. It is also my responsibility to identify at an early stage those students who may be vulnerable and need referring to the Residential Life Team.

University of Bristol | International Office Intern

July 2017 - September 2017

During the summer break of my 2nd year, I was an intern for the University’s International Office. I was in charge of all correspondence, booking and leading of all tours for prospective international students around the university. I thoroughly enjoyed interacting with the visitors, answering questions about my experiences at Bristol and university life in general. With up to 3 tours a day, each with up to 5 family groups, it was critical to manage the bookings so that each group could receive the key information they required given that many had travelled long distanced and were on tight schedules.

Conferences

Teaching

Non-Research Talks