#Chair
Chair on Artificial Intelligence at University College London
University College London – Professor John Shawe-Taylor
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Artificial intelligence (AI) is affecting the daily lives of millions of people across the world.
This term is a collective name for digital technologies that enable computers and machines to perform tasks that were previously only accomplishable by human beings. The University College London’s Chair researches contemporary AI techniques that allow computers to discover patterns in data and to learn new skills; either “by example” or by reinforcement of envisaged behaviour.
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QUOTE
“My blue sky project is education, where I believe AI can enhance the educational provision and experience of countless people across the globe, through its potential for personalized delivery of high quality educational materials.”
Professor John Shawe-Taylor
UNESCO Chairs are based within Institutes for Higher Education and specialise in specific research fields. They provide policy advice to the UK National Commission for UNESCO and HM government, as well as reviewing UNESCO applications.
ABOUT THE CHAIR
Led by Professor John Shawe-Taylor, the Chair’s team is developing a series of research projects delivering AI that can improve health and education, reduce inequality, and spur economic growth – all while tackling climate change and working to preserve our oceans and forests.
The aim of the team is to work with AI researchers, policymakers and start-ups in order to highlight the power and benefits of AI in solving the UN Grand Challenges. As such, the Chair helped to establish the first Category Two institute directly focussed on Artificial Intelligence under the auspices of UNESCO at the Jožef Stefan Institute in Slovenia. The International Research Centre on Artificial Intelligence (IRCAI) aims to provide a coordination point, funding route and exploitation accelerator for approaches to the United Nations Sustainable Development Goals (SDGs) that make use of AI.
By running workshops, events and networks for experts and students alike, the Chair is raising the profile of the important role AI has in our day to day lives, and equipping people from around the world to use this technology to positively shape their futures. One such workshop brought together machine learning and artificial intelligence practitioners from research communities across Africa and the world to design activities that will strengthen the work of African AI4D researchers, policy-makers and practitioners.
ABOUT THE CHAIR’S RESEARCH
John’s main research area is Statistical Learning Theory, but his interests range from Neural Networks, to Machine Learning, to Graph Theory. Machine learning is the practice of applying artificial intelligence to computer systems in order to minimise the need for programming – the machines are able to learn and improve from experiences for themselves. Developments in machine learning can raise educational standards through improved educational apps, digital engagement, and personalised learning. John has made positive contributions to a vast number of industries with his work, most recently with his paper identifying a more accurate prediction-method for ambulance call-outs.
John is a pioneer within the field of Machine Learning and his work has helped to drive a fundamental rebirth in the field with the introduction new analysis and mapping methods. Amongst the technological areas that have benefited highly are computer vision, document classification and brain scan analysis. More recently, he has also worked on interactive learning and reinforcement learning.
Professor John Shawe-Taylor
John Shawe-Taylor is Professor of Computer Science at University College London (UCL), as well as Director of the Centre for Computational Statistics and Machine Learning (CSML). He has coordinated a number of European wide projects investigating the theory and practice of Machine Learning, including the NeuroCOLT projects looking at Neural Computational Learning.
John has a far reach with his work, and is currently the scientific coordinator of a Framework VI Network of Excellence in Pattern Analysis, Statistical Modelling and Computational Learning (PASCAL) involving 57 partners.
The scientific coordination of these projects has influenced a generation of researchers and promoted the widespread uptake of machine learning in both science and industry that we are currently witnessing.
#Institution
University College London
Professor, Director at the Centre for Computational Statistics and Machine Learning
SINCE 2006
#Alma-Mater
Royal Holloway, University of London
PhD.
#Role at UNESCO
Chair in Artificial Intelligence
SINCE 2018
#Research&Events
LATEST EVENTS AND RESEARCH PROJECTS
Read about some of the many projects that Professor Shawe-Taylor has been a part of during his career.
Open Education Resources and AI Hackathon
#AICollaboration
The Chair organised a hackathon that allowed students at several international universities to take part in an early requirement capture process, helping to design, build and develop a working prototype that supports Open Education with AI.
Publications
SELECTED PUBLISHED WORK
In role as chair, John has carried out extensive AI research alongside colleagues from across the globe.
Predicting Engagement in Video Lectures
2020
#OpenEducation
Here, John explores how best to measure the success of Open Education Resources and evaluates the quantifiable aspects of learner engagement.
Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression
2018
#Mathematics
By accurately predicting when and where ambulance call-outs occur, it follows that there could be a reduced response time and better care. Here, John presents a novel method for ambulance demand prediction.
LATEST
QUOTE
“Humane AI is a European initiative that is rethinking the AI agenda by placing people at the centre of research and development. This is the approach that characterises my ambition for what AI can deliver for humanity. UNESCO provides a platform that can help to synthesise and promote this agenda.”
Professor John Shawe-Taylor
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