machine learning

Making Machines Better Learners

Helen Yannakoudakis from KCL Informatics is working on the next generation of machine learning models for natural language processing that can learn more effectively and with less training data. Along the way, she is also making existing approaches better from detecting hateful memes to supporting health diagnostics, the impact of her work is considerable.

King’s investigates the use of quantitative modelling to predict innovation programme success.

This work was motivated by Professor Elena Simperl’s experience of leading and supporting competitive EU-funded projects that offer business incubation and acceleration services to data-centric startups and SMEs (namely ODINE, DataPitch and DMS Accelerator projects). One of the key strengths of such programmes lies in their ability to attract, select and effectively allocate resources towards the most promising companies.

SAIS

SAIS (Secure AI assistantS) is a cross-disciplinary collaboration between the Departments of Informatics, Digital Humanities and The Policy Institute at King's College London, and the Department of Computing at Imperial College London, working with non-academic partners: Microsoft, Humley, Hospify, Mycroft, policy and regulation experts, and the general public, including non-technical users.

King's success in hateful memes challenge

King’s Lecturer in Computer Science, Dr Helen Yannakoudakis, was part of a team that enjoyed success in Facebook AI’s ‘Hateful Memes Challenge’ competition.