Projects

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

Presented at Journal for Open Source Software, 2021

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. This technique prioritises data that offer high information gain, leading to improved performance using substantially less data. The system allows users to visualise and integrate data from different sources and deal with incorrect or missing labels and imbalanced class sizes. We illustrate using the system with an astronomical dataset due to the field’s immediate need; however, AstronomicAL has been designed for datasets from any discipline.
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P.I.E.S: Passive Information Extraction System

Published:

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. 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.
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Rave Cave

Published:

For a 3rd Year group project, we created Rave Cave, 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.
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