Angus R Williams

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Angus R Williams

Position

Senior Data Scientist, Online Safety Team

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Research areas

Social media Visualisation (Programming languages) Non-parametric & semi-parametric methods Neural networks Unsupervised learning Supervised learning Deep learning Computer vision Applications (Machine learning)

Bio

Angus is a data scientist on the online safety team within the public policy programme, working on the Online Harms Observatory and researching data-centric AI for online safety. He has a MEng (distinction) from the University of Bristol in computer science with innovation, where he completed his dissertation on misinformation and AI.

His work centres around the use of machine learning, deep learning & natural language processing methods to deliver innovative solutions to human-centred problems.

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Research publications

Large language models can consistently generate high-quality content for election disinformation operations

Advances in large language models have raised concerns about their potential use in generating...

Williams, A.R., Burke-Moore, L., Chan, R.S.-Y., Enock, F.E., Nanni, F., Sippy, T., Chung, Y.-L., Gabasova, E., Hackenburg, K. and Bright, J. (2024). Large language models can consistently generate high-quality content for election disinformation operations. [online] arXiv.org.

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