John Shawe-Taylor

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John Stewart Shawe-Taylor is the Director of the University College Center for Computational Statistics and Machine Learning. His main field of research is the theory of statistical learning. He has contributed to a variety of areas from graphic theory, cryptography, statistical theory of learning and its applications. His main contributions were, however, in developing the analysis and subsequent algorithm definition of principle algorithms based on the theory of statistical learning. This work has contributed to a major rebirth in machine learning by introducing kernel methods and supporting vector machines, including mapping these approaches to new domains, including computer vision, document graduation and brain scan analysis. He has worked more recently on interactive learning and strengthening learning. He has also played a key role in bringing together a number of important European Networks of Excellence. The scientific coordination of these programs has influenced a generation of researchers and promoted the widespread use of machine learning in science and industry. More than 300 papers with more than 42,000 citations have been published. Two co-authored books with Nello Cristianini have become standard monographs for studying kernel processes and vector supporting machines, attracting 21,000 quotations. He’s head of the department of computer science at University College London, where he has monitored a significant expansion and has been seen emerging from the United Kingdom Research Evaluation Framework as the top computer science department in 2014.