Computer Laboratory

Artificial Intelligence Group

The work of the Artificial Intelligence Group is multi-disciplinary, spanning genomics and bio-informatics, computational learning theory, computer vision, and informal reasoning. A unifying theme is understanding multi-scale pattern recognition problems, seeking powerful (often statistical) algorithms for modeling and solving them, and for learning from data. The AI Group seeks to find synergies amongst ideas based in statistics, mechanised reasoning, cognitive science, biology, and engineering, and to develop practical applications from them.

AI Group

Members of the AI Group engaging with the final position of the famous chess match between IBM Deep Blue and world champion Gary Kasparov. In that chess game the world changed: Artificial Intelligence finally delivered on a long-awaited promise and earned its name.

John Daugman

John Daugman John Daugman is Professor of Computer Vision and Pattern Recognition in the Computer Laboratory. He obtained his AB and PhD degrees from Harvard University in the USA, where he also then taught on the Faculty. Before coming to Cambridge he held the Toshiba Chair at the Tokyo Institute of Technology, Japan, and during 2002–2004 he was the Johann Bernoulli Professor of Mathematics and Informatics at the University of Groningen, The Netherlands. He is a Fellow of the Institute of Mathematics and its Applications, and a Fellow of the International Association for Pattern Recognition. In 2013, Daugman was inducted into the US National Inventors Hall of Fame.

At Cambridge he currently teaches Computer Vision, Information Theory, and Mathematical Methods for Computer Science.

Research interests: computer vision, statistical pattern recognition, information theory and wavelets.

One outgrowth of his work has been iris recognition, an automatic and fast method for determining personal identity with very high confidence, by mathematical analysis of the random patterns that are visible in the iris of a person's eye from some distance. Professor Daugman's algorithms are the basis of all currently deployed iris recognition systems and have been licensed internationally, particularly for use in airports where governments (including the UK) allow the process to substitute for a passport. Currently the Government of India is using these algorithms to enroll and cross-compare the iris patterns of all 1.2 billion citizens of India in a national entitlements and benefits ID system. With 600 million persons enrolled so far and a further 1 million each day, some 600 trillion iris comparisons for ID de-duplication in India are performed every day with these algorithms.

(Professor Daugman is currently unavailable to supervise PhD students.)


Sean Holden

Holden Sean Holden is University Senior Lecturer in Machine Learning and Fellow and Director of Studies in Computer Science at Trinity College Cambridge. He obtained his BSc in Electronic Systems Engineering from the University of East Anglia and his PhD in Information Engineering from Cambridge University. He was postdoctoral researcher at King's College London and Cambridge University Engineering Department before taking up a Lectureship in Computer Science at University College London, where he set up and ran the MSc programme in Intelligent Systems. He was appointed Lecturer in Machine Learning in Cambridge in 2002.

He currently teaches the courses Artificial Intelligence I and Artificial Intelligence II to second and third year students respectively.

Research interests: machine learning algorithms, computational learning theory, Bayesian inference and Bayes networks, planning algorithms, functional languages for machine learning, probabilistic programming languages, application of machine learning in theorem proving, drug design, retinal opthalmology and organelle proteomics.


Mateja Jamnik

Mateja Jamnik Mateja Jamnik is University Lecturer and an EPSRC Advanced Research Fellow. Prior to this she was guest researcher in Prof. Joerg Siekmann's OMEGA Group, affiliated with the Collaborative Research Center "Resource-adaptive Cognitive Processes" at the University of Saarland, Sarbruecken, Germany, and Research Fellow in the School of Computer Science at the University of Birmingham. She completed her PhD in Prof. Alan Bundy's Mathematical Reasoning Group at the Department of Artificial Intelligence of the University of Edinburgh.

Research interests: computational modeling of human reasoning, in particular in mathematics. Artificial intelligence, automated reasoning, diagrammatic reasoning, theorem proving, proof planning, cognitive science, machine learning, human-computer interaction, knowledge representation, agent technology.

Dr Jamnik co-organises the UK network for women in computing research Women@Cl network grant funded by EPSRC:


Pietro Liò

Pietro Liò Pietro Liò is a Lecturer in Computational Biology and Director of Studies and Fellow in Computing at Fitzwilliam College. He currently teaches Bioinformatics (Algorithms in Bioinformatics), Genome Informatics II (Phylogenetic methods + Comparative Genomics) for the MPhil in Computational Biology (Department of Mathematics), and 4M8 Tripos (Cambridge-MIT initiative) Department of Engineering.

Research interests: computational and statistical modelling of molecular systems, analysis of molecular biology data (DNA and protein sequences, gene expression data, evolutionary information, proteomics), computational approaches to multiscale problems in molecular biology systems, computational molecular evolution.


See also: Natural Language Processing Group