Leadership

Research Director

Professor Andrew Blake

Professor Andrew Blake is Research Director at The Alan Turing Institute. Prior to joining the Institute in 2015, Professor Blake held the position of Microsoft Distinguished Scientist and Laboratory Director of Microsoft Research Cambridge, England. He joined Microsoft in 1999 as a Senior Researcher to found the Computer Vision group. In 2008 he became a Deputy Managing Director at the lab, before assuming the directorship in 2010. Before joining Microsoft Andrew trained in mathematics and electrical engineering in Cambridge England, and studied for a doctorate in artificial intelligence in Edinburgh. He was an academic for 18 years, latterly at the faculty at Oxford University, where he was a pioneer in the development of the theory and algorithms that can make it possible for computers to behave as seeing machines.

Professor Blake has published several books including “Visual Reconstruction” with A.Zisserman (MIT press), “Active Vision” with A. Yuille (MIT Press) and “Active Contours” with M. Isard(Springer-Verlag). He has twice won the prize of the European Conference on Computer Vision, with R. Cipolla in 1992 and with M. Isard in 1996, and was awarded the IEEE David Marr Prize (jointly with K. Toyama) in 2001.

In 2006 the Royal Academy of Engineering awarded him its Silver Medal and in 2007 the Institution of Engineering and Technology presented him with the Mountbatten Medal(previously awarded to computer pioneers Maurice Wilkes and Tim Berners-Lee, amongst others.) He was elected Fellow of the Royal Academy of Engineering in 1998, Fellow of the IEEE in 2008, and Fellow of the Royal Society in 2005. In 2010, Andrew was elected to the council of the Royal Society. In 2011, he and colleagues at Microsoft Research received the Royal Academy of EngineeringMacRobert Award for their machine learning contribution to Microsoft Kinect human motion-capture. In 2012 Andrew was elected to the board of the EPSRC and also received an honorary degree of Doctor of Science from the University of Edinburgh. In 2013 Andrew was awarded an honorary degree of Doctor of Engineering from the University of Sheffield. In 2014, Andrew gave the prestigious Gibbs lecture at the Joint Mathematics Meetings (transcript available here). Professor Andrew Blake has been named as the recipient of the 2016 BCS Lovelace Medal, the top award in computing in the UK, awarded by BCS, The Chartered Institute for IT. The award is presented annually to individuals who, in the opinion of BCS, have made a significant contribution to the advancement of Information Systems.

Professor Blake recorded a Short Talk discussing his research, you can view the full video here: http://bit.ly/2meBAGL

In 2016, Professor Blake was awarded the Lovelace medal – the top award in computing in the UK, awarded by BCS, The Chartered Institute for IT. In May 2017, Andrew gave the Lovelace lecture “Machines that learn to see” which you can view in full here: http://academy.bcs.org/content/lovelace-lecture

  • Publications

    • J. Shotton, R. Girshick, A. Fitzgibbon, T. Sharp, M. Cook, M. Finocchio, R. Moore, P. Kohli, A. Criminisi, A. Kipman, A. Blake (2013). Efficient Human Pose Estimation from Single Depth Images. Decision Forests for Computer Vision and Medical Image Analysis. PDF
    • D.J. Holland, J. Mitchell, A. Blake, and L. F. Gladden (2013). Grain Sizing in Porous Media using Bayesian Magnetic Resonance. Physical Review Letters. PDF
    • A.A. Muryy, A.E. Welchman, A. Blake, R.W. Fleming (2013). Specular Reflections and the Estimation of Shape from Binocular Disparity. Proceedings of the National Academy of Sciences of the United States. PNAS
    • D.J. Holland, A. Blake, A.B. Tayler, A.J. Sederman, L.F. Gladden (2012). Bubble Size Measurement Using Bayesian Magnetic Resonance. Chemical Engineering Science. PDF
    • J.G. Rossa, D.J. Holland, A. Blake, A.J. Sederman, L.F. Gladden (2012). Extending the use of Earth’s Field NMR using Bayesian methodology: Application to Particle Sizing. Journal of Magnetic Resonance. PDF
    • D.J. Holland, A. Blake, A.B. Tayler, A.J. Sederman, L.F. Gladden (2011). A Bayesian Approach to Characterising Multi-phase Flows Using Magnetic Resonance: Application to Bubble Flows. Journal of Magnetic Resonance. PDF Science Direct
    • J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake (2011), Real-Time Human Pose Recognition in Parts from a Single Depth Image, in CVPR (Best Paper), IEEE. PDF
    • D.J. Holland, A. Blake, A.B. Tayler, A.J. Sederman, L.F. Gladden. (2011). A Bayesian Approach to Characterising Multi-phase Flows Using Magnetic Resonance: Application to Bubble Flows. Journal of Magnetic Resonance. 209(1), 83-7.Download
    • V. Gulshan, C. Rother, A. Criminisi, A. Blake, and A. Zisserman (2010). Geodesic Star Convexity for Interactive Image Segmentation, Proc. IEEE Conf. Computer Vision and Pattern Recognition. PDF
    • D.J. Holland, D.M. Malioutov, A. Blake, A.J. Sederman and L.F. Gladden (2010). Reducing Data Acquisition Times in Phase-encoded Velocity Imaging Using Compressed Sensing. Journal of Magnetic Resonance. 203, 2, 236-246. In press.
    • D. Cremers, Y. Boykov, A. Blake, F. R. Schmidt:, eds (2009). Energy Minimization Methods in Computer Vision and Pattern Recognition, in EMMCVPR. PDF
    • P. Parasoglou, D. Malioutov, A.J. Sederman, J. Rasburn, H. Powell, L.F. Gladden, A. Blake and M.L. Johns (2009). Quantitative Single Point Imaging with Compressed Sensing. Journal of Magnetic Resonance. 201, 1, 72-80. PDF
    • B. Amberg, A. Blake, T. Vetter (2009). On Compositional Image Alignment with an Application to Active Appearance Models. IEEE Conf. Computer Vision and Pattern Recognition. PDF
    • V. S. Lempitsky, M.Verhoek, J. A. Noble, A. Blake (2009). Random Forest Classification for Automatic Delineation of Myocardium in Real-Time 3D Echocardiography. Functional Imaging and Modeling of the Heart. 447-456. PDF
    • Z. Yi, A. Criminisi, J. Shotton, and A. Blake (2009). Discriminative, Semantic Segmentation of Brain Tissue in MR Images. Medical Image Computing and Computer Assisted Intervention. PDF
    • V. Lempitsky, C. Rother, S. Roth, and A. Blake (2009). Fusion Moves for Markov Random Field Optimization. Microsoft Research Technical Report no. MSR-TR-2009-60, May 2009. Also IEEE Trans. PAMI, in press. PDF
    • P. V. Gehler, C. Rother, A. Blake, T. P. Minka, T. Sharp (2008). Bayesian Color Constancy Revisited. Proc. IEEE Conf. Computer Vision and Pattern Recognition. PDF
    • A. Criminisi, T. Sharp, A. Blake (2008). GeoS: Geodesic Image Segmentation. Proc. Eur. Conf. on Computer Vision, 99-112. PDF
    • V. S. Lempitsky, A. Blake, C. Rother(2008). Image Segmentation by Branch-and-Mincut. Proc. Eur. Conf. on Computer Vision, 15-29. PDF
    • J. Shotton, A. Blake, R. Cipolla (2008). Multiscale Categorical Object Recognition Using Contour Fragments. IEEE Trans. Pattern Anal. Mach. Intell. 30(7), 1270-1281. PDF
    • J. Shotton, A. Blake, R. Cipolla (2008). Efficiently Combining Contour and Texture Cues for Object Recognition.Proc. British Machine Vision Conf. PDF
    • A. W. Fitzgibbon, D.P. Robertson, A. Criminisi, S. Ramalingam, A. Blake (2007). Learning priors for calibrating families of stereo cameras. Proc. Int. Conf. Computer Vision, 1-8. PDF
    • V. S. Lempitsky, C. Rother, A. Blake (2007). LogCut – Efficient Graph Cut Optimization for Markov Random Fields. Proc. Int. Conf. Computer Vision, 1-8. PDF
    • B. Amberg, A. Blake, A.W. Fitzgibbon, S. Romdhani, T. Vetter (2007). Reconstructing High Quality Face-Surfaces using Model Based Stereo. Proc. Int. Conf. Computer Vision, 1-8. PDF
    • A. Agarwal, S. Izadi, M. Chandraker, A. Blake (2007). High Precision Multi-touch Sensing on Surfaces using Overhead Cameras. Tabletop, 197-200.
    • S. Izadi, A. Agarwal, A. Criminisi, J.M. Winn, A. Blake, A.W. Fitzgibbon (2007). C-Slate: A Multi-Touch and Object Recognition System for Remote Collaboration using Horizontal Surfaces. Tabletop, 3-10. PDF
    • A. Criminisi, A. Blake, C. Rother, J. Shotton, P.H.S. Torr (2007). Efficient Dense Stereo with Occlusions for New View-Synthesis by Four-State Dynamic Programming. International Journal of Computer Vision 71(1), 89-110. PDF
    • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross, C. Rother (2006). Probabilistic Fusion of Stereo with Color and Contrast for Bi-Layer Segmentation. Int. Journal of Computer Vision 76(2), 107. PDF
    • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross and C. Rother (2006). Probabilistic Fusion of Stereo with Colour and Contrast for Bi-layer Segmentation. IEEE Trans. Pattern Analysis and Machine Intelligence, 480-1492. PDF
    • C. Rother, L. Bordeaux, Y. Hamadi and A. Blake (2006). AutoCollage. ACM Trans. Graphics (SIGGRAPH), 847-852. PDF
    • A. Criminisi, J. Shotton, A. Blake, C Rother and PHS Torr (2006). Efficient Dense Stereo with Occlusions for New View-synthesis by Four-state Dynamic Programming. Int. J. Computer Vision, 0920-5691. PDF
    • A. Agarwal and A. Blake (2006). The Panum Proxy Algorithm for Dense Stereo Matching Over a Volume of Interest. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2339-2346. PDF
    • A. Criminisi, G. Cross and A. Blake (2006). Bilayer Segmentation of Live Video. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 53-60. PDF
    • O. Williams, A. Blake and R Cipolla (2006). Sparse and Semi-supervised Visual Mapping with S3GP. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 230-237. PDF
    • C. Rother, V. Kolmogorov, T. Minka and A. Blake (2006). Cosegmentation of Image Pairs by Histogram Matching Incorporating a Global Constraint into MRFs. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 993-1000. PDF
    • O. Williams, A. Blake, and R. Cipolla (2005). Sparse Bayesian regression for efficient visual tracking. IEEE Trans Pattern Analysis and Machine Intelligence, 27, 8, 12921304. PDF
    • A. Blake (2005). Visual tracking: a short research roadmap. In Mathematical Models of Computer Vision: The Handbook, eds. O. Faugeras, Y. Chen and N. Paragios, Springer, in press. PDF
    • J. Shotton, A. Blake and R. Cipolla (2005). Contour-based learning for object recognition. Proc. Int. Conf. Computer Vision, 1, 503510. PDF
    • C. Rother, S. Kumar, V. Kolmogorov and A. Blake (2005). Digital Tapestry. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2, 589596. PDF
    • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross and C. Rother (2005). Bi-layer segmentation of binocular stereo. Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2,407414. PDF
    • O. Williams, A. Blake, and R. Cipolla (2004). The Variational Ising Classifier (VIC) algorithm for coherently contaminated data. Proc Neural Information Processing Systems, 17. PDF
    • J. Winn and A. Blake (2004). Generative affine localisation and tracking. Proc Neural Information Processing Systems, 17. PDF
    • S.Romdhani, P. Torr, B. Schoelkopf and A. Blake (2004). Efficient face detection by a cascaded support-vector machine expansion. Proc. Roy. Soc. A, 460, 2501, 32833297. PDF
    • C. Rother, V. Kolmogorov and A. Blake (2004). GrabCut interactive foreground extraction using iterated graph cuts. ACM Trans. Graphics (SIGGRAPH), 309314. PDF
    • A. Blake, C. Rother, M. Brown, P. Perez, and P. Torr (2004). Interactive image segmentation using an adaptive GMMRF model. Proc. Eur. Conf. on Computer Vision (ECCV), Springer-Verlag, 428441. PDF
    • P. Perez, J. Vermaak and A. Blake (2004). Data fusion for visual tracking with particles. Proc. IEEE, 92, 3, 495513. PDF
    • P. Perez, M. Gangnet and A. Blake (2003). Poisson image editing. ACM Trans. Graphics (SIGGRAPH), 2(3):313-318. PDF
    • A. Criminisi, J. Shotton, A. Blake and P.H.S. Torr (2003). Gaze manipulation for one to one teleconferencing. Proc. Int. Conf. on Computer Vision (ICCV), 191198. PDF
    • O. Williams, A. Blake and R. Cipolla (2003). A sparse probabilistic learning algorithm for realtime tracking. Proc. Int. Conf. on Computer Vision (ICCV), 353360. PDF
    • K. Toyama and A. Blake (2002). Probabilistic tracking with exemplars in a metric space. Int. J. Computer Vision, 48, 919. PDF
    • J. Rittscher, T. Watanabe, J. Kato, S. Joga and A. Blake (2002). An HMM-based segmentation method for traffic monitoring. IEEE Trans. Pattern Analysis and Machine Intelligence, 24, 9. PDF
    • P. Prez, A. Blake, and M. Gangnet (2001). JetStream: Probabilistic contour extraction with particles. Proc. Int. Conf. on Computer Vision (ICCV), II:524-531. PDF
    • J. Vermaak, A. Blake, M. Gangnet, and P. Perez (2001). Sequential Monte Carlo fusion of sound and vision for speaker tracking. Proc. Int. Conf. on Computer Vision (ICCV), I:741-746. PDF
    • J. Sullivan, A. Blake, M. Isard and J. MacCormick (2001). Bayesian Object Localisation in Images. Int. J. Computer Vision, 44, 2, 111-136. PDF
    • J. Deutscher, A. Blake and I. Reid (2000). Articulated Body Motion Capture by Annealed Particle Filtering Proc. Conf. Computer Vision and Pattern Recognition, 2, 126 133. Abstract and .ps.gz and movies
    • B. North, A. Blake, M. Isard and J. Rittscher. (2000). Learning and Classification of Complex Dynamics. IEEE Trans. Pattern Analysis and Machine Intelligence, 22, 9, 10161034. PDF
    • J. MacCormick and A. Blake (2000). Probabilistic exclusion and partitioned sampling for multiple object tracking. Int. J. Computer Vision, 39(1), 57-71, 2000. PDF
    • R. A. Eagle, M.A. Hogervorst and A. Blake. (1999). Does the visual system exploit projective geometry to help solve the motion correspondence problem? Vision Research, 39, 373-385.
    • E. Rimon and A. Blake (1999). Caging planar bodies by 1-parameter, two-fingered gripping systems. Int. J. Robotics Research, 18, 3, 299-318.
    • A. Blake and M. Isard (1998). Active Contours. Springer-Verlag.
    • A. Blake, B. Bascle, M. Isard and J. McCormick (1998). Statistical models of visual shape and motion. Phil. Trans. Roy. Soc. B, 356, 1283-1302. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). CONDENSATION – Conditional density propagation for visual tracking. Int. J. Computer Vision, 29, 1, 5-28. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). A mixed-state Condensation tracker with automatic model switching. Proc 6th Int. Conf. Computer Vision, 107-112. Abstract and .ps.gz
    • B. Bascle and A. Blake (1998). Separability of pose and expression in facial tracking and animation. Proc 6th Int. Conf. Computer Vision, 323-328. Abstract and .ps.gz
    • J. MacCormick and A. Blake (1998). A probabilistic contour discriminant for object localisation. Proc 6th Int. Conf. Computer Vision, 390-395. Abstract and .ps.gz
    • R. Kaucic and A. Blake (1998). Accurate, Real-Time, Unadorned Lip Tracking. Proc 6th Int. Conf. Computer Vision, 370-375. Abstract and .ps.gz
    • C. Davidson and A. Blake (1998). Caging planar objects with a three-finger, one-parameter gripper Proc IEEE Int. Conf. Robotics and Automation, 2722-2727. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). A smoothing filter for Condensation model switching. Proc European Conf. Computer Vision, 768-781. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). ICondensation: Unifying low-level and high-level tracking in a stochastic framework Proc European Conf. Computer Vision, 893-908. Abstract and .ps.gz
    • R. Cipolla and A. Blake (1997). Image divergence and deformation from closed curves. Int. J. Robotics Research, 16, 1, 77-96. Abstract and .ps.gz
    • D. Buckley, J.P. Frisby and A. Blake (1996). Does the human visual system implement an ideal observer theory of slant from texture? Vision Research, 36, 8, 1163-1176.
    • D. Sinclair and A. Blake. (1996) Quantitative planar region detection. International Journal of Computer Vision, 18, 1, 77-91.
    • S. Rowe and A. Blake (1996). Statistical mosaics for tracking. J. Image and Vision Computing, 14, 8, 549-564. Abstract, .ps.gz
    • M. Isard and A. Blake (1996). Contour tracking by stochastic propagation of conditional density. Proc European Conf. Computer Vision, Cambridge, UK, 343-356. Abstract and .ps.gz
    • B. Bascle, A. Blake and A. Zisserman (1996). Motion deblurring and super-resolution from an image sequence. Proc European Conf. Computer Vision, Cambridge, UK, 573-582. Abstract and .ps.gz
    • D. Reynard, A. Wildenberg, A. Blake and J. Marchant (1996). Learning Dynamics of Complex Motions from Image Sequences. Proc European Conf. Computer Vision, Cambridge, UK, 357-368. Abstract and .ps.gz
    • E. Rimon and A. Blake (1996). Caging 2D bodies by one-parameter, two-fingered gripping systems. Proc Int. Conf. Robotics and Automation, 1458-1464, IEEE Press. PDF
    • A. Blake (1995). A symmetry theory of planar grasp. Int. J. Robotics Research, 14, 5, 425-444. Abstract and .ps.gz
    • A. Blake, M. Isard and D. Reynard (1995). Learning to track the visual motion of contours. Artificial Intelligence, 78, 101-134. Abstract and .ps.gz
    • R. A. Eagle and A. Blake. (1995). Two-dimensional constraints on three-dimensional structure from motion tasks. Vision Research, 35, 20, 2927-2941. PDF
    • A. Blake- (1994). Uncertain views. Nature, 368, 498-499.
    • D. Sinclair, A. Blake and D. Murray. (1994). Robust estimation of ego-motion from normal flow. Int. J. Computer Vision, 13, 1, 57-69.
    • A. Blake and M. Isard (1994). 3D position, attitude and shape input using video tracking of hands and lips. Proc. ACM SIGGRAPH Conference, Orlando, USA, 185-192. Abstract and .ps.gz
    • R. Brockett and A. Blake (1994). Estimating the shape of a moving planar curve. Proc. IEEE Int. Conf. Decision Theory and Control, 3247-3252. PDF
    • A. Blake, D. McCowen, H.R. Lo, P.J. Lindsey (1993). Trinocular active range sensing. IEEE Trans. Pattern Analysis and Machine Intelligence, 15, 5, 477-483. PDF
    • A. Blake, H.H. B-ulthoff and D. Sheinberg (1993). Shape from Texture: Ideal Observers and Human Psychophysics Vision Research, 33, 12, 1723-1737. PDF
    • A. Blake, R. Curwen and A. Zisserman (1993). A framework for spatio-temporal control in the tracking of visual contours. Int. J. Computer Vision, 11, 2, 127-145. Abstract and .ps.gz
    • A. Blake, M. Taylor and A. Cox (1993). Grasping visual symmetry. Proc 4th Int. Conf. Computer Vision, Berlin, 724-733. PDF
    • -A. Blake (1992). Computational modelling of hand-eye coordination. Phil. Trans. Roy. Soc. B, 337, 351-360.
    • R. Cipolla and A. Blake (1992). Surface shape from the deformation of apparent contours. Int. J. Computer Vision, 9, 2, 83-112. PDF
    • R. Cipolla and A. Blake (1992). Surface orientation and time to contact from image divergence and deformation. Proc. 2nd European Conf. Computer Vision, Springer-Verlag, 465 474
    • A. Blake and A. Yuille, editors, (1992). Active Vision. MIT Press.
    • A. Blake and H.H. B-ulthoff (1991). Shape from specularities: computation and psychophysics. Phil. Trans. Roy. Soc. B, 331, 237-252. PDF
    • L. Tarassenko and A. Blake (1991). Analogue computation of collision-free paths. Proc. IEEE Int. Conf. Robotics and Automation, 540-545. PDF
    • A. Blake and C. Marinos (1990). Shape from texture: estimation, isotropy and moments. J. Artificial Intelligence, 45(3), 323-380. PDF
    • A. Blake and H. B-ulthoff (1990). Does the brain know the physics of specular reflection? Nature, 343(6254):165-168. PDF
    • A. Blake and R. Cipolla (1990). Robust estimation of surface curvature from deformation of apparent contours. Proc. 1st European Conf. on Computer Vision, Springer-Verlag, 465-474.
    • R. Cipolla and A. Blake. (1990). The Dynamic Analysis of Apparent Contours. Proc. 3rd Int. Conf. Computer Vision, Osaka, Japan, 616-625. PDF
    • C. Marinos and A. Blake (1990). Shape from texture: the homogeneity hypothesis. Proc. 3rd Int. Conf. Computer Vision, Osaka, Japan, 350-334. PDF
    • A. Blake (1989). Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction. IEEE Trans. Pattern Analysis and Machine Intelligence, 11, 1, 2-12. PDF
    • A.Blake and A. Zisserman. (1987). Visual Reconstruction. MIT Press, Cambridge, USA. PDF
    • A. Blake (1985). Boundary conditions for lightness computation in Mondrian World. Computer Vision, Graphics and Image Processing, 32, 314-327. PDF
    • A. Blake (1985). Specular stereo. Proc. Int. Joint Conf. on Artificial Intelligence 973-976.
    • A. Blake (1984). Reconstructing a visible surface. Proc. Conf. American Association for Artificial Intelligence, 23-26.
    • A. Blake (1983). The least-disturbance principle and weak constraints. Pattern Recognition Letters, 1, 393-399. PDF
    • A. Blake (1982). Fixed point solutions of recursive operations on boolean arrays. Computer Journal, 25, 2, 231-233.J.
  • Books

    Markov Random Fields for Vision and Image Processing (2011)

    Markov Random Fields for Vision and Image Processing (2011)

    Edited by Andrew Blake, Pushmeet Kohli and Carsten Rother

    Markov Random Fields for Vision and Image Processing demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications.

    Markov Random Fields for Vision and Image Processing MIT Press


    Active Contours (1998)

    Active Contours (1998)

    By Andrew Blake and Michael Isard

    Active Contours is about the computer analysis of moving video images. It develops geometric and probabilistic models for shapes and their dynamics. The models are applied to the real-time analysis of shapes in motion, and addresses issues of learning, temporal filtering and the problems of visual clutter. Numerous applications are illustrated from computer graphics animation, user-interface design, medical imaging, automated surveillance and robotics.

    Active Contours Springer-Verlag


    Active Vision (1992)

    Active Vision (1992)

    Edited by Andrew Blake and Alan Yuille

    Active Vision explores important themes emerging from the active vision paradigm at the time of publication, which had only recently become an established area of machine vision. In four parts the contributions look in turn at tracking, control of vision heads, geometric and task planning, and architectures and applications, presenting research that marked a turning point for both the tasks and the processes of computer vision.


    Visual Reconstruction (1987)

    Visual Reconstruction (1987)

    By Andrew Blake and Andrew Zisserman

    Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. Two concepts, which were new at the time of publication, are introduced, analyzed, and illustrated.


  • Short CV

    1974-77 Scholar in mathematics, Trinity College Cambridge.
    1977 BA Electrical Sciences, 1st class with distinction.
    1977-78 Kennedy Fellow at Massachusetts Institute of Technology, Cambridge, USA.
    1978-80 Scientist with Ferranti Edinburgh, Electro-optics group.
    1980-83 Research Associate and Ph.D. student at Edinburgh University. Awarded Ph.D. in Computer Vision, 1983.
    1983-87 Lecturer in Computer Science, Edinburgh University.
    1984-87 Royal Society Research Fellow.
    1987-96 Lecturer in Image Processing, Dept. Engineering Science, University of Oxford.
    1987-99 Fellow of Exeter College, Oxford.
    1996-9 Professor of Engineering Science, University of Oxford.
    1998-9 Royal Society Senior Research Fellow.
    1999-02 Senior Research Scientist, Microsoft Research, Cambridge.
    1999 Visiting Professor of Engineering Science, University of Oxford.
    2000 Fellow of Clare Hall, University of Cambridge.
    2002 Principal Research Scientist, Microsoft Research.
    2005 Partner, Microsoft Corporation.
    2006 Visiting Professor of Informatics University of Edinburgh.
    2007 Visiting Professor of Machine Intelligence, University of Cambridge.
    2008 Deputy Laboratory Director Microsoft Research Cambridge
    2010 Microsoft Distinguished Scientist & Laboratory Director, Microsoft Research Cambridge
    1977 Lamb prize of the University of Cambridge for Electrical Sciences.
    1977 ver Heyden der Lancey prize, Trinity College, Cambridge.
    1977-78 John F. Kennedy Fellow, MIT, USA.
    1984 Nominated for publisher-s prize at the American Association for Artificial Intelligence (AAAI) conference, in Austin, Texas.
    1984-87 Awarded the Royal Society IBM Research Fellowship.
    1986 Commendation for paper presented to the IEEE Conference on Computer Vision and Pattern Recognition, Miami, USA.
    1987 Appointed Associate Editor of J. Image and Vision Computing, Butterworth.
    1991-92 Associate Editor of Transactions on Pattern Analysis and Machine Intelligence of the IEEE.
    1991-90 Editorial board, Vision Research, Pergamon Press.
    1991 Appointed joint organiser (with Professors D.Mumford, Harvard and B.Ripley, Oxford) of a 6 month programme in Computer Vision for 1993, at the Isaac Newton Institute, Cambridge, UK.
    1992 Winner (with R. Cipolla) of the biennial prize of the European Vision Society.
    1993 Visiting Fellowship at Clare Hall, Cambridge, July-December.
    1993 Appointed to the Editorial board, International Journal Computer Vision, Kluwer.
    1994 Elected Fellow of the Institute of Electrical Engineers.
    1994-5 Program Chairman, IEEE International Conference on Computer Vision, Cambridge, USA.
    1996 Winner (with M. Isard) of the biennial prize of the European Vision Society.
    1996 Paper (with E. Rimon) nominated for the annual prize of the IEEE Robotics and Automation society.
    1997-02 Editorial board member for Computer Vision and Image Understanding, Academic Press.
    1998 Elected Fellow of the Royal Academy of Engineering.
    1998-9 Program Chairman, IEEE International Conference on Computer Vision, Greece.
    1998-9 Royal Society Senior Research Fellow (Amersham).
    2000 Elected Fellow of Clare Hall College, Cambridge.
    2000-5 Appointed to the Technical Advisory Board of the Max Planck Institute for Biological Cybernetics, T-ubingen.
    2001-4 Appointed to the Governing Body of the BBSRC Silsoe Research Institute, UK.
    2001 Awarded (with K. Toyama) the David Marr Prize of the IEEE, for Computer Vision.
    2004 Elected the Distinguished Fellow of the British Machine Vision Association for 2004.
    2005 Awarded (with V. Kolmogorov, A. Criminisi, G. Cross, C. Rother) honourable mention for best paper at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
    2005 Promoted to Partner, Microsoft Corporation.
    2005 Elected Fellow of the Royal Society.
    2006 Awarded Silver Medal of Royal Academy of Engineers.
    2007 Awarded Mountbatten Medal of the Institution of Engieering and Technology.
    2008 Elected fellow of the IEEE.
    2010 Elected to the Council of the Royal Society
    2010 Appointed Laboratory Director, Microsoft Research Cambridge
    2011 Recipient of Royal Academy of Engineering MacRobert Award
    2012 Elected to the Board of the EPSRC
  • Favourite Publications

    • A. Blake (1985). Boundary conditions for lightness computation in Mondrian World. Computer Vision, Graphics and Image Processing, 32, 314-327. PDF
    • A. Blake (1989). Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction. IEEE Trans. Pattern Analysis and Machine Intelligence, 11, 1, 2-12. PDF
    • A. Blake and C. Marinos (1990). Shape from texture: estimation, isotropy and moments. J. Artificial Intelligence, 45(3), 323-380. PDF
    • A. Blake and H. B-ulthoff (1990). Does the brain know the physics of specular reflection? Nature, 343(6254):165-168. PDF
    • A. Blake and H.H. B-ulthoff (1991). Shape from specularities: computation and psychophysics. Phil. Trans. Roy. Soc. B, 331, 237-252. PDF
    • L. Tarassenko and A. Blake (1991). Analogue computation of collision-free paths. Proc. IEEE Int. Conf. Robotics and Automation, 540-545. PDF
    • R. Cipolla and A. Blake (1992). Surface shape from the deformation of apparent contours. Int. J. Computer Vision, 9, 2, 83-112. PDF
    • A. Blake, H.H. B-ulthoff and D. Sheinberg (1993). Shape from Texture: Ideal Observers and Human Psychophysics Vision Research, 33, 12, 1723-1737. PDF
    • A. Blake, R. Curwen and A. Zisserman (1993). A framework for spatio-temporal control in the tracking of visual contours. Int. J. Computer Vision, 11, 2, 127-145. Abstract and .ps.gz
    • A. Blake and M. Isard (1994). 3D position, attitude and shape input using video tracking of hands and lips. Proc. ACM SIGGRAPH Conference, Orlando, USA, 185-192. Abstract and.ps.gz
    • R. Brockett and A. Blake (1994). Estimating the shape of a moving planar curve. Proc. IEEE Int. Conf. Decision Theory and Control, 3247-3252. PDF
    • A. Blake (1995). A symmetry theory of planar grasp. Int. J. Robotics Research, 14, 5, 425-444. Abstract and .ps.gz
    • A. Blake, M. Isard and D. Reynard (1995). Learning to track the visual motion of contours. Artificial Intelligence, 78, 101-134. Abstract and .ps.gz
    • R. A. Eagle and A. Blake. (1995). Two-dimensional constraints on three-dimensional structure from motion tasks. Vision Research, 35, 20, 2927-2941. PDF
    • M. Isard and A. Blake (1996). Contour tracking by stochastic propagation of conditional density. Proc European Conf. Computer Vision, Cambridge, UK, 343-356. Abstract and .ps.gz
    • D. Reynard, A. Wildenberg, A. Blake and J. Marchant (1996). Learning Dynamics of Complex Motions from Image Sequences. Proc European Conf. Computer Vision, Cambridge, UK, 357-368. Abstract and .ps.gz
    • E. Rimon and A. Blake (1996). Caging 2D bodies by one-parameter, two-fingered gripping systems. Proc Int. Conf. Robotics and Automation, 1458-1464, IEEE Press. PDF
    • R. Cipolla and A. Blake (1997). Image divergence and deformation from closed curves. Int. J. Robotics Research, 16, 1, 77-96. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). ICondensation: Unifying low-level and high-level tracking in a stochastic framework Proc European Conf. Computer Vision, 893-908. Abstract and .ps.gz
    • M. Isard and A. Blake (1998). A mixed-state Condensation tracker with automatic model switching. Proc 6th Int. Conf. Computer Vision, 107-112. Abstract and .ps.gz
    • J. MacCormick and A. Blake (2000). Probabilistic exclusion and partitioned sampling for multiple object tracking. Int. J. Computer Vision, 39(1), 57-71, 2000. PDF
    • B. North, A. Blake, M. Isard and J. Rittscher. (2000). Learning and Classification of Complex Dynamics. IEEE Trans. Pattern Analysis and Machine Intelligence, 22, 9, 1016-1034. PDF
    • J. Deutscher, A. Blake and I. Reid (2000). Articulated Body Motion Capture by Annealed Particle Filtering Proc. Conf. Computer Vision and Pattern Recognition, 2, 126- 133. Abstract and.ps.gz and movies
    • J. Sullivan, A. Blake, M. Isard and J. MacCormick (2001). Bayesian Object Localisation in Images. Int. J. Computer Vision, 44, 2, 111-136. PDF
    • J. Vermaak, A. Blake, M. Gangnet, and P. P-erez (2001). Sequential Monte Carlo fusion of sound and vision for speaker tracking. Proc. Int. Conf. on Computer Vision (ICCV), I:741-746. PDF
    • P. P-erez, A. Blake, and M. Gangnet (2001). JetStream: Probabilistic contour extraction with particles. Proc. Int. Conf. on Computer Vision (ICCV), II:524-531. PDF
    • K. Toyama and A. Blake (2002). Probabilistic tracking with exemplars in a metric space. Int. J. Computer Vision, 48, 9-19. PDF
    • O. Williams, A. Blake and R. Cipolla (2003). A sparse probabilistic learning algorithm for realtime tracking. Proc. Int. Conf. on Computer Vision (ICCV), 353-360. PDF
    • P. Perez, M. Gangnet and A. Blake (2003). Poisson image editing. ACM Trans. Graphics (SIGGRAPH), 2(3):313-318. PDF
    • C. Rother, V. Kolmogorov and A. Blake (2004). GrabCut – interactive foreground extraction using iterated graph cuts. ACM Trans. Graphics (SIGGRAPH), 309-314. PDF
    • C. Rother, L. Bordeaux, Y. Hamadi and A. Blake (2006). AutoCollage. ACM Trans. Graphics (SIGGRAPH), in press. PDF
    • V. Kolmogorov, A. Criminisi, A. Blake, G. Cross and C. Rother (2006). Probabilistic fusion of stereo with colour and contrast for bi-layer segmentation. IEEE Trans. Pattern Analysis and Machine Intelligence, in press. PDF
    • V. S. Lempitsky, A. Blake, C. Rother(2008).Image Segmentation by Branch-and-Mincut. Proc. Eur. Conf. on Computer Vision, 15-29. PDF
    • J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake (2011), Real-Time Human Pose Recognition in Parts from a Single Depth Image. In Proc. IEEE CVPR (Best Paper). PDF
    • D.J. Holland, A. Blake, A.B. Tayler, A.J. Sederman, L.F. Gladden (2011), A Bayesian approach to characterising multi-phase flows using magnetic resonance: Application to bubble flows. J. Magnetic Resonance, 209, 1, 83–87. PDF Download

CEO

Sir Alan Wilson

Sir Alan Wilson FBA FAcSS FRS is CEO of The Alan Turing Institute and Professor of Urban and Regional Systems in the Centre for Advanced Spatial Analysis at University College London. He is Chair of the Home Office Science Advisory Council.

He is a Cambridge Mathematics graduate and began his research career in elementary particle physics at the Rutherford Laboratory. He turned to the social sciences, working on cities, with posts in Oxford and London before becoming Professor of Urban and Regional Geography in Leeds in 1970. He was a member of Oxford City Council from 1964-1967. In the late 1980s, he was the co-founder of GMAP Ltd, a University spin-out company. He was Vice-Chancellor of the University of Leeds from 1991 to 2004 when he became Director-General for Higher Education in the then DfES. After a brief spell in Cambridge, he joined UCL in 2007. From 2007-2013 he was Chair of the Arts and Humanities Research Council; and from 2013-2015, he was Chair of the Lead Expert Group for the Government Office for Science Foresight Project on The Future of Cities. He is a Member of Academia Europaea, an FBA, an FAcSS and an FRS. He was knighted in 2001. In August 2017, he received an honorary degree from the School of Advanced Study, University of London in recognition of his outstanding contributions to higher education.

His research field covers many aspects of mathematical modelling of cities and the use of these models in planning. These techniques are now in common use internationally – including the use of the concept of entropy in building spatial interaction models – summarised in Entropy in urban and regional modelling (re-issued in 2011 by Routledge). These models have been widely used in areas such as transport planning, demography and economic modelling. His recent research is on the applications of dynamical systems theory in relation to modelling the evolution of urban structure in both historical and contemporary settings. This led to the laying of the foundations of a comprehensive theory of urban dynamics described in Complex spatial systems (2000). He has published over 200 papers and his recent books include The science of cities and regions (2012), his five volume Urban modelling (2012, edited), Explorations in urban and regional dynamics (2015, with Joel Dearden), Global dynamics (2016, edited) and Geo-mathematical modelling (2016, edited). He has a particular interest in interdisciplinarity and published Knowledge power in 2010; he writes the quaestio blog (www.quaestio.blogweb.casa.ucl.ac.uk).

Chair

Howard Covington

Howard is a graduate of St John’s College, Cambridge. He has a double first in theoretical physics and a distinction in post-graduate maths.

His first career was in the City as an investment banker and asset manager. He became a director of SG Warburg and then European chief executive of Wasserstein Perella, a US investment bank. He co-founded New Star Asset Management and was its chief executive until it was sold to Henderson in 2009. In 2014 he cofounded Greenrock Homes, a property developer.
His second career is in promoting mathematical sciences and action to reduce climate change.

He has been a trustee of the Science Museum, is chair of the Isaac Newton Institute for Mathematical Sciences, the UK’s national maths research institute at Cambridge, and is the inaugural chair of The Alan Turing Institute. He is vice-chair of ClientEarth, an environmental law firm, and an adviser to Preventable Surprises, a think-tank. He has written on the response of the investment industry to climate change for the Wall Street Journal, the Financial Times and Nature.

Board of Trustees

Howard Covington (Chair of Trustees)

Howard Covington is the founding chair of the Alan Turing Institute. He had a career in the City as an investment banker and asset manager. He became a director of SG Warburg and then European chief executive of Wasserstein Perella, a US investment bank. He co-founded New Star Asset Management and was its chief executive until it was sold to Henderson in 2009.

Professor Peter Grindrod CBE

Professor of Mathematics at the University of Oxford’s Mathematical Institute

Peter Grindrod is a Professor of Mathematics at the Mathematical Institute at the University of Oxford. He was appointed a CBE in 2005 for services to mathematics R&D, is a former member of the EPSRC Council (2000–04) and chair of the EPSRC’s User Panel. He is a former president of the Institute of Mathematics and its Applications, the UK’s professional and learned society for mathematicians (2006–08). He is also former member of BBSRC Council (2009–13). He is an independent member of the MOD Defence Scientific Advisory Council (2008– ).

He obtained a degree in maths from the University of Bristol (1981) and a PhD from the University of Dundee (1983), after which followed a short period of post doctoral research in dynamical systems and nonlinear PDEs at Dundee. Between 1984 and 1989 he worked at the Mathematical Institute at the University of Oxford, largely on both applications of modelling within physiology and biology.

In 1989 he joined a commercial consulting company working in the environmental sciences, building up a mathematical modelling group on multidisciplinary projects in the UK, Europe, US and Japan.

In 1998 he was co-founder and Technical Director of a start–up  company, Numbercraft Limited, supplying services and software to retailers and consumer goods manufacturers. He worked with all of the major grocery retailers in the UK and their largest suppliers. Numbercraft, designed as a five-year project, was acquired by Lawson Software (St Paul, US) in 2003.

Professor Frank Kelly CBE

Professor of the Mathematics of Systems, University of Cambridge

Frank Kelly is Professor of the Mathematics of Systems at the University of Cambridge and was awarded a CBE for services to mathematical sciences in 2013. His main research is in random processes, networks and optimisation, with a specialist focus on applications to the design and control of networks and to the understanding of self-regulation in large-scale systems.

He has received several prizes for his work. These include the Royal Statistical Society’s Guy Medal in Silver, the John von Neumann Theory Prize of INFORMS, the David Crighton Medal of the London Mathematical Society and Institute of Mathematics and Applications, and the Alexander Graham Bell Medal of the IEEE. He is a Fellow of the Royal Society and a Foreign Member of the National Academy of Engineering.

He served as Chief Scientific Adviser to the Department for Transport (2003-2006), and as Master of Christ’s College, Cambridge (2006-2016).

Professor Richard Kenway OBE

Tait Professor of Mathematical Physics and Vice-Principal High Performance Computing, University of Edinburgh

Richard Kenway was appointed to the Tait Chair of Mathematical Physics at the University of Edinburgh in 1994. His research explores theories of elementary particles using computer simulation. As Vice-Principal, Professor Kenway is responsible for the University’s provision of UK high-performance computing services and for promoting advanced computing technologies, computational and data science to benefit academia and industry. For ten years, until it closed in 2011, his responsibilities included the UK National e-Science Centre. In the Queen’s 2008 Birthday Honours, Professor Kenway was awarded an OBE for services to science. He led the establishment of the Scientific Steering Committee of the Partnership for Advanced Computing in Europe (PRACE) and chaired it from 2010 to 2012. He is a founder member of the UK e-Infrastructure Leadership Council and a member of the Science & Technology Facilities Council.

Dr Julie Maxton CBE

Executive Director of the Royal Society

Julie Maxton is the Executive Director of the Royal Society, the first woman in 350 years to hold the post.  Before taking up her position at the Royal Society in 2011 Julie was Registrar at the University of Oxford, the first woman in 550 years in the role.  She is an Honorary Fellow of University College Oxford, a Bencher of the Middle Temple, a Freeman of the Goldsmith’s Company, and a Board member of Engineering UK, the Charities Aid Foundation, Haberdasher Aske’s School and of the International Advisory Board of the Blavatnik School of Governance at Oxford University.  Originally trained as a barrister at the Middle Temple, Julie combined a career as a practising lawyer with that of an academic, holding a number of senior academic positions, including those of Deputy Vice Chancellor, Professor and Dean of the Faculty of Law at the University of Auckland, New Zealand.  She is the author of numerous articles concerned with trusts, equity, commercial and property law.

Wendy Tan White MBE

General Partner, Entrepreneur First

Wendy Tan White is a General Partner at Entrepreneur First, an organisation which invests in top technical individuals to help them build world-class deep technology start-ups from scratch in London and Singapore. She joined Entrepreneur First in 2015  to further support the growth of its companies with a £40m Next Stage Fund and programme. Since 2011, Entrepreneur First has created over 100 startups worth over $400m including Magic Pony Technology, Tractable, StackHut, Pi-Top, OpenCosmos, Status Today and Cloud NC.

Before Entrepreneur First, Wendy co-founded Moonfruit, the first software-as-a-service website builder, with Joe White who is also a General Partner at Entrepreneur First and Wendy’s husband. Wendy and Joe grew the business through the dotcom crash and financial crisis before selling to Yell Group for $37m. Wendy helped launch Zopa, the first peer-to-peer lending platform, and Egg, the first Internet bank in EU. She also supports the wider UK ecosystem on the boards of TechCityUK, Government Digital Advisory, Imperial College London Department of Computing DoC and School of Design Engineering. Recently awarded an MBE for services to technology, business and women entrepreneurs. Wendy also loves design with an MA Central St Martins as well as BEng Computer Science, Imperial College.

Professor Pam Thomas

Pro-Vice-Chancellor (Research), University of Warwick

Pam Thomas is the University of Warwick’s Pro Vice-Chancellor for Research and Professor of Physics.

Pam joined Warwick in 1990, becoming a Professor in the Department of Physics in 2005. She was appointed as the inaugural Director of the Science City Research Alliance for the Universities of Warwick and Birmingham in 2009, leading this complex interdisciplinary programme between the two universities and in the wider region. She is responsible for the inter-departmental X-ray diffraction facility and leads a research group in Ferroelectrics and Crystallography within the Condensed Matter Group. She has also held a number of key administrative research and teaching roles in the department and has previously served on the Board of Graduate Studies. Most recently, she has been the first female Chair of the Board of the Faculty of Science – a role to which she was appointed in 2011.

Pam was educated at Oxford University, where she took a DPhil in the Clarendon Laboratory and undertook post-doctoral research. She has served on many national and international committees for physics, materials and crystallography and particularly for research at large central facilities such as the Diamond Synchrotron Facility in Oxfordshire and the European Synchrotron Radiation Facility in Grenoble. She currently contributes to the work of the Science and Technology Facilities’ Council (STFC) in the UK as a member of their national Science Advisory Board.

Pam works across Warwick’s departments to maintain the University’s research excellence. Pam oversees departmental and inter-faculty developments, and heads the University’s efforts to generate the impact our research deserves. The Global Research Priorities programme, for which she provides leadership, has provided the University with significant international attention.

Her other responsibilities include support for early career research staff and research students, in addition to her academic leadership on equality and diversity matters.

Dr Neil Viner

Director, Programme Delivery at EPSRC

Neil Viner is Director of Programme Delivery at EPSRC.  He currently has oversight of a portfolio of projects investing over £800M to create a number of world leading research institutes and research infrastructure in partnership with universities.

Neil is a member of The Alan Turing Institute’s audit committee, having previously been Project Director leading the establishment of the Institute. This follows several years developing EPSRC’s People strategy, including the leading the establishment of a portfolio of Centres for Doctoral Training across the UK with investment totalling nearly £1B. Prior to this, he was head of the policy and analysis team and a specialist policy advisor at the Office of Science and Technology and has held a variety of strategy and operational roles within the Research Councils.

Professor Patrick Wolfe

Professor of Statistics and Honorary Professor of Computer Science at University College London

Patrick Wolfe holds chairs in statistics and computer science at University College London, where he specialises in the mathematical foundations of data science. A Royal Society Research Fellow and EPSRC Established Career Fellow in the Mathematical Sciences, he is Executive Director of UCL’s Big Data Institute and its Centre for Data Science. A past recipient of the Presidential Early Career Award for Scientists and Engineers from the White House, he has provided expert advice on applications of data science to policy, societal and commercial challenges including to the UK and US governments and to a range of public and private bodies. He serves on the editorial boards of the Proceedings of the Royal Society A (Mathematical, Physical & Engineering Sciences) and the Journal of the Royal Statistical Society B (Statistical Methodology), and most recently was an organiser and Simons Foundation Fellow at the Isaac Newton Institute’s 2016 programme on Theoretical Foundations for Statistical Network Analysis.

University Liaison Directors

Professor Graham Cormode, University of Warwick

Bio

Graham Cormode is a Professor in Computer Science at the University of Warwick and The Alan Turing Institute’s University Liaison Director for Warwick. He works on research topics in data management, privacy and big data analysis. Previously, he was a principal member of technical staff at AT&T Labs-Research in the USA.  He serves as an associate editor for ACM Transactions on Database Systems (TODS), and the Journal of Discrete Algorithms.

Research

Graham will work on a variety of topics at the Turing including:

  • Algorithms for scalable analytics & streaming, sketching, dimensionality reduction, compressed sensing, with applications to internet scale data, vehicle data.
  • Data Anonymization and privacy & statistical and cryptographic approaches to privacy, primarily differential privacy, with applications to telecommunications and social data.
  • Distributed algorithms & algorithms for large scale monitoring and logging of activities, drawing on ideas from approximation and distributed ledger technologies.

Professor David Pym, University College London

Bio

David Pym is Professor of Information, Logic, and Security at UCL and is The Alan Turing Institute’s University Liaison
Director for UCL. Heholds a PhD in logic and theoretical computer science from Edinburgh,and an MA and an ScD in mathematics from Cambridge. He is a Fellow of the IMA and the BCS. David spent many years with Hewlett-Packard’s Research Laboratories, where he developed interests in systems, security, and economics.

Research

David will work on a range of topics in security and privacy in distributed information-processing systems. He is interested in questions about access control in distributed systens, security and privacy policy, and the economics of security management. He is also interested in understanding basic questions in distributed systems architecture and behaviour, such as consistency and the relationship between systems management policies and systems architecture. David addresses these issues using ideas and techniques from logic, theoretical computer science, probability theory, and economics. He aims to build both conceptual and implemented tools to support decision-making in systems and policy design.

Professor Jared Tanner, University of Oxford

Bio

Jared Tanner is Professor of the Mathematics of Information at the University of Oxford and The Alan Turing Institute’s University Liaison Director for Oxford. He obtained his PhD (2002) in applied mathematics at the University of California at Los Angeles, and was a postdoctoral fellow at the University of California at Davis (Maths) and Stanford University (Stats.) where he worked with David L. Donoho.  Prior to joining the University of Oxford in 2012 he was Professor of the Mathematics of Information at the University of Edinburgh (2007-2012).  He is founding editor-in-chief of Information and Inference: A Journal of the IMA, whose mission is to publish high quality mathematically oriented articles furthering the understanding of the theory, methods of analysis, and algorithms for information and data.  He is also on the editorial board for Applied and Computational Harmonic Analysis, Multiscale modelling and simulation A SIAM Interdisciplinary Journal, and was an associate editor for the Princeton Companion to Applied Mathematics.  His research has appeared in the Proc Natl Acad Sci USA, Phil Trans Royal Soc A, and other leading journals.

Research

Jared Tanner’s research concerns extracting models of high dimensional date which reveal of the essential information in the data.  Specific contributions include the derivation of sampling theorems in compressed sensing using techniques from stochastic geometry and the design and analysis of efficient algorithms for matrix completion which minimise over higher dimensional subspaces as the reliability of the data warrants.  These techniques allow more efficient information acquisition as well as the ability to cope with missing data.

Recent interests include new models for low dimensional structure in heterogeneous data and topological data analysis.

Professor Chris Williams, University of Edinburgh

Bio

Chris Williams is Professor of Machine Learning in the School of Informatics, University of Edinburgh, and is The Alan Turing Institute’s University Liaison Director for Edinburgh. He obtained his MSc (1990) and PhD (1994) at the University of Toronto, under the supervision of Geoff Hinton. He was a member of the Neural Computing Research Group at Aston University from 1994 to 1998, and has been at the University of Edinburgh since 1998.

Research

Chris is interested in a wide range of theoretical and practical issues in machine learning, statistical pattern recognition, probabilistic graphical models and computer vision. This includes theoretical foundations, the development of new models and algorithms, and applications. His main areas of research are in models for understanding time-series, visual object recognition and image understanding, unsupervised learning, and Gaussian processes. At the Turing he also has interests in improving the data analytics process, looking to address the issues of data understanding and preparation that are widely quoted as taking around 80% of the time in a typical data mining project.

Scientific Advisory Board

Prof Sinan Aral, MIT Sloan School of Management

Sinan Aral is the David Austin Professor of Management at MIT, where he is a Professor of IT & Marketing, Chair of the Marketing Department, Professor in the Institute for Data, Systems and Society and where he co-leads MIT’s Initiative on the Digital Economy.

He was the Chief Scientist at SocialAmp, one of the first social commerce analytics companies (until its sale to Merkle in 2012) and at Humin, a social platform that the Wall Street Journal called the first “Social Operating System” (until its sale to Tinder in 2016). Sinan was a Scholar-in-Residence at the New York Times in 2013 and has worked closely with Facebook, Yahoo, Microsoft, IBM, Intel, Cisco, Oracle, SAP and many other leading Fortune 500 firms on realizing business value from big data, analytics, social media and IT investments. He is currently a general partner at Manifest Capital and on the Advisory Board of the Alan Turing Institute for Data Science in London. Sinan’s research has won numerous awards including the Microsoft Faculty Fellowship, the PopTech Science Fellowship, an NSF CAREER Award and a Fulbright Scholarship. In 2014, he was named one of the “World’s Top 40 Business School Professors Under 40.” Sinan is a Phi Beta Kappa graduate of Northwestern University, holds Master’s degrees from the London School of Economics and Harvard University, and received his PhD from MIT. He enjoys cooking, skiing and telling jokes about his own cooking and skiing. His most recent hobby is learning from his three-year-old son.You can find him on Twitter @sinanaral.

Sir Robert Devereux, KCB, Department for Work and Pensions, UK Government

Robert is the Permanent Secretary at the Department for Work and Pensions, a post he has held since January 2011.

He became a Permanent Secretary at the Department for Transport in May 2007. His earlier career within the Civil Service included a decade working in HM Treasury, and posts in what were then the Department for Social Security and the Overseas Development Administration. He spent two years on secondment with Guinness Brewing Worldwide.

Robert has a degree in maths, and masters in statistics, and was the previous head of the Policy Profession within the Civil Service.

He was knighted in 2016, for services to transport and welfare, and for voluntary service in Kilburn, London.

Dr Cynthia Dwork, Harvard (Chair)

Cynthia Dwork is renowned for placing privacy-preserving data analysis on a mathematically rigorous foundation. A cornerstone of this work is differential privacy, a strong privacy guarantee, frequently permitting highly accurate data analysis. Dr. Dwork has also made seminal contributions in cryptography and distributed computing, and is the recipient of two “test-of-time” awards. She is a member of the US National Academy of Sciences, the US National Academy of Engineering, and the American Philosophical Society, and a Fellow of the American Academy of Arts and Sciences.

Dwork, previously Distinguished Scientist at Microsoft Research, joined Harvard in January 2017 as the Gordon McKay Professor of Computer Science at the Paulson School of Engineering and Applied Sciences, Radcliffe Alumnae Professor at the Radcliffe Institute for Advanced Study, and an Affiliated Faculty Member at Harvard Law School.

Dr Michael Kearns, University of Pennsylvania

Dr. Michael Kearns is Professor and National Center Chair in the Department of Computer and Information Sciences at the University of Pennsylvania, with secondary appointments in the departments of Economics, and in Statistics, and Operations, Information and Decisions of the Wharton School. Kearns is the Founding Director of Penn’s Warren Center for Network and Data Sciences, as well as the Penn Program in Networked and Social Systems Engineering.

His research includes topics in machine learning, algorithmic game theory, computational social science, and quantitative finance and algorithmic trading.  Kearns spent a decade at AT&T Bell Labs, where he was head of the AI department, which conducted a range of systems and foundational AI and machine learning research. He has consulted extensively in the technology and finance industries, and is currently Chief Scientist of MANA Partners, a New York trading and technology company.

He studied math and computer science at UC Berkeley, and completed his Ph.D. in computer science at Harvard University in 1989. He is an elected Fellow of the American Academy of Arts and Sciences, the Association for Computing Machinery, the Association for the Advancement of Artificial Intelligence, and the Society for the Advancement of Economic Theory.

Dr. Mike Lynch OBE FRS FREng, Invoke Capital and Council for Science and Technology

Mike Lynch is a fellow of the Royal Society and of the Royal Academy of Engineering, and he is an Honorary Fellow of Christ’s College, Cambridge.

The founder of Invoke Capital, a $1billion fund which invests in fundamental European technologies, Mike Lynch has been described by the Financial Times as “the doyen of European software” and by the Sunday Times as “Britain’s Bill Gates”. He holds a PhD from the University of Cambridge in Machine Intelligence, he sits on the Prime Minister’s Scientific Advisory Panel and is a UK Business Ambassador. Mike has founded a number of companies, including Autonomy, the UK’s largest software company, with a market capitalisation of $11bn. He has invested in a number of start-ups, including Darktrace, Luminance, Neurence, Sophia Genetics and Featurespace and he specialises in areas such as in Cybersecurity, Machine learning, Bioinformatics and big data.

He was a non-executive director of Cambridge Enterprise and previous directorships include the BBC, the British Library and Nesta. He is a council member of the of the Foundation for Science and Technology.

Prof Stéphane Mallat, École Polytechnique

Stéphane Mallat received the Ph.D. degree in electrical engineering from the University of Pennsylvania, in 1988. He was then Professor at the Courant Institute of Mathematical Sciences, until 1994. In 1995, he became Professor in Applied Mathematics at Ecole Polytechnique, Paris and Department Chair in 2001. From 2001 to 2007 he was co-founder and CEO of a semiconductor start-up company. In 2012 he joined the Computer Science Department of Ecole Normale Supérieure, in Paris.

Stéphane Mallat’s research interests include learning, signal processing, and harmonic analysis. He is a member of the French Academy of sciences, an IEEE Fellow and an EUSIPCO Fellow.  In 1997, he received the Outstanding Achievement Award from the SPIE Society and was a plenary lecturer at the International Congress of Mathematicians in 1998. He also received the 2004 European IST Grand prize, the 2004 INIST-CNRS prize for most cited French researcher in engineering and computer science, the 2007 EADS grand prize of the French Academy of Sciences, the 2013 Innovation medal of the CNRS, and the 2015 IEEE Signal Processing best sustaining paper award.

Prof Bin Yu, University of California, Berkeley

Bin Yu is Chancellor’s Professor in the Departments of Statistics and of Electrical Engineering & Computer Science at the University of California at Berkeley and a former Chair of Statistics at Berkeley. She is founding co-director of the Microsoft Joint Lab at Peking University on Statistics and Information Technology. She is engaged in interdisciplinary research with scientists from genomics, neuroscience, and medicine.  In order to solve data problems in these domain areas, she develops statistics and machine learning methods/algorithms and theory and integrates with domain knowledge and quantitative critical thinking in the process.

She is Member of the U.S. National Academy of Sciences and Fellow of the American Academy of Arts and Sciences. She was a Guggenheim Fellow in 2006, an Invited Speaker at ICIAM in 2011, the Tukey Memorial Lecturer of the Bernoulli Society in 2012, and 2016 Rietz Lecturer of the Institute of Mathematical Statistics (IMS). She was President of IMS in 2013-2014, and is a Fellow of IMS, ASA, AAAS and IEEE.

Programme Directors

Mark Briers

Mark Briers is Programme Director for the Alan Turing Institute-Defence and Security partnership.

Mark Briers has worked in the defence and security industry for over 16 years, directing research programmes in the area of statistical data analysis, and leading large teams to deliver operational capability.

He completed his PhD in 2007 at Cambridge University where he developed Sequential Monte Carlo based techniques for state-space filtering and smoothing. He is an Honorary Senior Lecturer at Imperial College London, and a member of several committees at the Royal Statistical Society. His current research interests include scalable Bayesian inference, sequential inference, and anomaly detection.

Professor Mark Girolami FRSE

Mark Girolami is Programme Director for the Alan Turing Institute-Lloyd’s Register Foundation Programme in Data-Centric Engineering.

An internationally leading researcher in statistical sciences, Mark has had a broad career including 10 years as an engineer at IBM. He brings to the programme significant experience of developing and applying advanced statistical and computational techniques to engineering challenges.

Mark joins the Institute from the Department of Mathematics at Imperial College London where he holds a Chair in Statistics.

He is an EPSRC Established Career Research Fellow (2012 – 2018) and previously an EPSRC Advanced Research Fellow (2007 – 2012). Most recently he was awarded a £3 million research grant from EPSRC to test and improve predictive policing and tackle other challenges for future cities.

In 2011 he was elected to the Fellowship of the Royal Society of Edinburgh when he was also awarded a Royal Society Wolfson Research Merit Award.

 

Dr Anthony Lee

Anthony Lee is Programme Director for the Alan Turing Institute-Intel partnership.

A computational statistician in the Department of Statistics at the University of Warwick, Anthony received BSc. and MSc. degrees in Computer Science from the University of British Columbia, and a DPhil. in Statistics from the University of Oxford. He was previously a Centre for Research in Statistical Methodology Research Fellow at the University of Warwick.

He serves on the Editorial Board for Statistics and Computing and the Journal of Computational and Graphical Statistics, and is the first Course Director of the BSc. Data Science degree at the University of Warwick.

Dr Jonathan Shaw

Jonathan Shaw is Programme Director for the Alan Turing Institute-HSBC partnership. Jonathan is an economist and data scientist whose research focuses on modelling individual behaviour, evaluating education and labour market programmes, and understanding the effects of taxes and benefits across life. Before joining the Alan Turing Institute, he worked at the Institute for Fiscal Studies for almost 15 years, the last four of which he was Deputy Director of the Tax Administration Research Centre. He has done work for government departments in the UK and abroad, regulators and private charitable foundations and has provided economic advice to a wide variety of policymakers in governmental and quasi-governmental organisations. He did his PhD in empirical economics at University College London under Professor Sir Richard Blundell.

Programme Committee

Professor Andrew Blake

BIO

Professor Andrew Blake is Research Director at The Alan Turing Institute. Prior to joining the institute in 2015, Professor Blake held the position of Microsoft Distinguished Scientist and Laboratory Director of Microsoft Research Cambridge, England. He joined Microsoft in 1999 as a Senior Researcher to found the Computer Vision group. In 2008 he became a Deputy Managing Director at the lab, before assuming the directorship in 2010. Before joining Microsoft Andrew trained in mathematics and electrical engineering in Cambridge England, and studied for a doctorate in artificial intelligence in Edinburgh. He was an academic for 18 years, latterly on the faculty at Oxford University, where he was a pioneer in the development of the theory and algorithms that can make it possible for computers to behave as seeing machines.

In 2006 the Royal Academy of Engineering awarded him its Silver Medal and in 2007 the Institution of Engineering and Technology presented him with the Mountbatten Medal (previously awarded to computer pioneers Maurice Wilkes and Tim Berners-Lee, amongst others.) He was elected Fellow of the Royal Academy of Engineering in 1998, Fellow of the IEEE in 2008, and Fellow of the Royal Society in 2005. In 2010, Andrew was elected to the council of the Royal Society. In 2011, he and colleagues at Microsoft Research received the Royal Academy of Engineering MacRobert Award for their machine learning contribution to Microsoft Kinect human motion-capture. In 2012 Andrew was elected to the board of the EPSRC and also received an honorary degree of Doctor of Science from the University of Edinburgh. In 2013 Andrew was awarded an honorary degree of Doctor of Engineering from the University of Sheffield. In 2014, Andrew gave the prestigious Gibbs lecture at the Joint Mathematics Meetings (transcript available here). Professor Andrew Blake has been named as the recipient of the 2016 BCS Lovelace Medal, the top award in computing in the UK, awarded by BCS, The Chartered Institute for IT. The award is presented annually to individuals who, in the opinion of BCS, have made a significant contribution to the advancement of Information Systems.

Professor Blake recorded a Short Talk discussing his research, you can view the full video here.

  • Short CV

    1974-77 Scholar in mathematics, Trinity College Cambridge.
    1977 BA Electrical Sciences, 1st class with distinction.
    1977-78 Kennedy Fellow at Massachusetts Institute of Technology, Cambridge, USA.
    1978-80 Scientist with Ferranti Edinburgh, Electro-optics group.
    1980-83 Research Associate and Ph.D. student at Edinburgh University. Awarded Ph.D. in Computer Vision, 1983.
    1983-87 Lecturer in Computer Science, Edinburgh University.
    1984-87 Royal Society Research Fellow.
    1987-96 Lecturer in Image Processing, Dept. Engineering Science, University of Oxford.
    1987-99 Fellow of Exeter College, Oxford.
    1996-9 Professor of Engineering Science, University of Oxford.
    1998-9 Royal Society Senior Research Fellow.
    1999-02 Senior Research Scientist, Microsoft Research, Cambridge.
    1999 Visiting Professor of Engineering Science, University of Oxford.
    2000 Fellow of Clare Hall, University of Cambridge.
    2002 Principal Research Scientist, Microsoft Research.
    2005 Partner, Microsoft Corporation.
    2006 Visiting Professor of Informatics University of Edinburgh.
    2007 Visiting Professor of Machine Intelligence, University of Cambridge.
    2008 Deputy Laboratory Director Microsoft Research Cambridge
    2010 Microsoft Distinguished Scientist & Laboratory Director, Microsoft Research Cambridge
    1977 Lamb prize of the University of Cambridge for Electrical Sciences.
    1977 ver Heyden der Lancey prize, Trinity College, Cambridge.
    1977-78 John F. Kennedy Fellow, MIT, USA.
    1984 Nominated for publisher-s prize at the American Association for Artificial Intelligence (AAAI) conference, in Austin, Texas.
    1984-87 Awarded the Royal Society IBM Research Fellowship.
    1986 Commendation for paper presented to the IEEE Conference on Computer Vision and Pattern Recognition, Miami, USA.
    1987 Appointed Associate Editor of J. Image and Vision Computing, Butterworth.
    1991-92 Associate Editor of Transactions on Pattern Analysis and Machine Intelligence of the IEEE.
    1991-90 Editorial board, Vision Research, Pergamon Press.
    1991 Appointed joint organiser (with Professors D.Mumford, Harvard and B.Ripley, Oxford) of a 6 month programme in Computer Vision for 1993, at the Isaac Newton Institute, Cambridge, UK.
    1992 Winner (with R. Cipolla) of the biennial prize of the European Vision Society.
    1993 Visiting Fellowship at Clare Hall, Cambridge, July-December.
    1993 Appointed to the Editorial board, International Journal Computer Vision, Kluwer.
    1994 Elected Fellow of the Institute of Electrical Engineers.
    1994-5 Program Chairman, IEEE International Conference on Computer Vision, Cambridge, USA.
    1996 Winner (with M. Isard) of the biennial prize of the European Vision Society.
    1996 Paper (with E. Rimon) nominated for the annual prize of the IEEE Robotics and Automation society.
    1997-02 Editorial board member for Computer Vision and Image Understanding, Academic Press.
    1998 Elected Fellow of the Royal Academy of Engineering.
    1998-9 Program Chairman, IEEE International Conference on Computer Vision, Greece.
    1998-9 Royal Society Senior Research Fellow (Amersham).
    2000 Elected Fellow of Clare Hall College, Cambridge.
    2000-5 Appointed to the Technical Advisory Board of the Max Planck Institute for Biological Cybernetics, T-ubingen.
    2001-4 Appointed to the Governing Body of the BBSRC Silsoe Research Institute, UK.
    2001 Awarded (with K. Toyama) the David Marr Prize of the IEEE, for Computer Vision.
    2004 Elected the Distinguished Fellow of the British Machine Vision Association for 2004.
    2005 Awarded (with V. Kolmogorov, A. Criminisi, G. Cross, C. Rother) honourable mention for best paper at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
    2005 Promoted to Partner, Microsoft Corporation.
    2005 Elected Fellow of the Royal Society.
    2006 Awarded Silver Medal of Royal Academy of Engineers.
    2007 Awarded Mountbatten Medal of the Institution of Engieering and Technology.
    2008 Elected fellow of the IEEE.
    2010 Elected to the Council of the Royal Society
    2010 Appointed Laboratory Director, Microsoft Research Cambridge
    2011 Recipient of Royal Academy of Engineering MacRobert Award
    2012 Elected to the Board of the EPSRC

Mark Briers

Mark Briers is Programme Director for the Alan Turing Institute-Defence and Security partnership.

Mark Briers has worked in the defence and security industry for over 16 years, directing research programmes in the area of statistical data analysis, and leading large teams to deliver operational capability.

He completed his PhD in 2007 at Cambridge University where he developed Sequential Monte Carlo based techniques for state-space filtering and smoothing. He is an Honorary Senior Lecturer at Imperial College London, and a member of several committees at the Royal Statistical Society. His current research interests include scalable Bayesian inference, sequential inference, and anomaly detection.

Professor Graham Cormode, University of Warwick

BIO

Graham Cormode is a Professor in Computer Science at the University of Warwick and The Alan Turing Institute’s University Liaison Director for Warwick. He works on research topics in data management, privacy and big data analysis. Previously, he was a principal member of technical staff at AT&T Labs-Research in the USA.  He serves as an associate editor for ACM Transactions on Database Systems (TODS), and the Journal of Discrete Algorithms.

Graham will work on a variety of topics at the Turing including:

  • Algorithms for scalable analytics & streaming, sketching, dimensionality reduction, compressed sensing, with applications to internet scale data, vehicle data.
  • Data Anonymization and privacy & statistical and cryptographic approaches to privacy, primarily differential privacy, with applications to telecommunications and social data.
  • Distributed algorithms & algorithms for large scale monitoring and logging of activities, drawing on ideas from approximation and distributed ledger technologies.

Professor Jon Crowcroft (Chair), University of Cambridge

BIO

Jon Crowcroft has been the Marconi Professor of Communications Systems in the Computer Laboratory since October 2001. He has worked in the area of Internet support for multimedia communications for over 30 years. Three main topics of interest have been scalable multicast routing, practical approaches to traffic management, and the design of deployable end-to-end protocols. Current active research areas are Opportunistic Communications, Social Networks, and techniques and algorithms to scale infrastructure-free mobile systems. He leans towards a “build and learn” paradigm for research.

He graduated in Physics from Trinity College, University of Cambridge in 1979, gained an MSc in Computing in 1981 and PhD in 1993, both from UCL. He is a Fellow the Royal Society, a Fellow of the ACM, a Fellow of the British Computer Society, a Fellow of the IET and the Royal Academy of Engineering and a Fellow of the IEEE.

He likes teaching, and has published a few books based on learning materials.

 

Professor Mark Girolami FRSE

Mark Girolami is Programme Director for the Alan Turing Institute-Lloyd’s Register Foundation Programme in Data-Centric Engineering.

An internationally leading researcher in statistical sciences, Mark has had a broad career including 10 years as an engineer at IBM. He brings to the programme significant experience of developing and applying advanced statistical and computational techniques to engineering challenges.

Mark joins the Institute from the Department of Mathematics at Imperial College London where he holds a Chair in Statistics.

He is an EPSRC Established Career Research Fellow (2012 – 2018) and previously an EPSRC Advanced Research Fellow (2007 – 2012). Most recently he was awarded a £3 million research grant from EPSRC to test and improve predictive policing and tackle other challenges for future cities.

In 2011 he was elected to the Fellowship of the Royal Society of Edinburgh when he was also awarded a Royal Society Wolfson Research Merit Award.

Dr Philippa Hemmings, Engineering and Physical Sciences Research Council

Bio

Philippa has been the EPSRC Theme Leader for the Mathematical Sciences for the past six years.   She also acts as the Strategic Lead within EPSRC for UKCRIC, a £138M government capital investment project and the EPSRXC Lead for the cross RCUK and Innovate Urban Living Partnership. EPSRC is the main Government Funding agency for research in the engineering and physical sciences, which includes mathematical sciences, in the UK.   In addition to overseeing the funding of mathematical sciences research, including partnerships with other disciplines and PhD training and working with the UK community to identify and develop new opportunities, responsibilities include undertaking evaluations and obtaining evidence to inform future strategy and funding and to help communicate the importance of the mathematical sciences.

She has had a number of previous roles within EPSRC including Theme lead for Living with Environmental Change and Head of the Engineering for Sustainability Programme (which included civil, environmental and chemical engineering).  She also spent a number of years managing the EPSRC Council and its advisory Panels, and overseeing evaluation and strategic planning within EPSRC and a short time at the Department for Business, Innovation and Skills working on the UK Government’s Science & Innovation Strategy as a member of the Tera Allas-led project team that produced the  2014 report: Insights from International Benchmarking of the UK Science & Innovation System.

Dr Stephen Jarvis, University of Warwick

BIO

Professor Jarvis studied at London, Oxford and Durham Universities before taking his first Lectureship at the Oxford University Computing Laboratory. Here he worked on the development of performance tools for the BSP programming library, as well as teaching at Brasenose, Lincoln and Keble Colleges. After a short secondment to Microsoft Research in Cambridge, he joined the University of Warwick, rising to Professor in 1999. Professor Jarvis acted as Director of Research from 2008 to 2013, leading the Department to rank 2nd (out of 89 UK Computing Departments) in the 2014 UK Research Excellence Framework (REF). In 2013 he was appointed Chair of Department. Professor Jarvis is a Visiting Exchange Professor at New York University and is currently engaged in the establishment of the Alan Turing Institute, the UK’s national institute for data science.

Professor Jarvis heads Warwick’s High Performance Systems Group, whose research is focused on the analysis, performance evaluation and optimisation of software/systems combinations. In particular, the group are developing predictive techniques capable of determining the detailed execution characteristics and resource use of industrial-strength applications running on large high-performance and distributed systems. These techniques have been used to support procurement, system optimisation, resource scheduling and software redesign. Much of this research has been focused on computationally intense applications of interest to the science and engineering community. In 2009, Professor Jarvis was awarded a four-year Royal Society Industry Fellowship with Rolls-Royce, focused on HPC code development, optimisation and performance modelling. In 2013, collaborative work with the US National Laboratories led to a R&D Top 100 award, widely recognised as an ‘Oscar of Innovation’. More recently Professor Jarvis has applied these techniques to data-intensive domains and architectures. Professor Jarvis has run funded research projects with IBM, UK MOD, Rolls-Royce Plc, Intel, Bull Information Systems, Microsoft Research and others.

Professor Jarvis heads Warwick’s High Performance Systems Group, whose research is focused on the analysis, performance evaluation and optimisation of software/systems combinations. In particular, the group are developing predictive techniques capable of determining the detailed execution characteristics and resource use of industrial-strength applications running on large high-performance and distributed systems. These techniques have been used to support procurement, system optimisation, resource scheduling and software redesign. Much of this research has been focused on computationally intense applications of interest to the science and engineering community. In 2009, Professor Jarvis was awarded a four-year Royal Society Industry Fellowship with Rolls-Royce, focused on HPC code development, optimisation and performance modelling. In 2013, collaborative work with the US National Laboratories led to a R&D Top 100 award, widely recognised as an ‘Oscar of Innovation’. More recently Professor Jarvis has applied these techniques to data-intensive domains and architectures. Professor Jarvis has run funded research projects with IBM, UK MOD, Rolls-Royce Plc, Intel, Bull Information Systems, Microsoft Research and others.

Professor Ruth King, University of Edinburgh

BIO

Ruth King is the Thomas Bayes’ Chair of Statistics at the University of Edinburgh. She was awarded her PhD in 2001 from the University of Bristol, supervised by Steve Brooks. She then held positions at the Universities of Cambridge (PDRA; 2001-3) and St Andrews (EPSRC post-doctoral fellow in Mathematics 2003-5; lecturer 2003-10; reader 2010-15) before taking up her current appointment at the University of Edinburgh in 2015. Ruth was elected a Fellow of the Learned Society of Wales in 2017.

Ruth’s research lies in the development of statistical methodology and their applications, primarily within the fields of ecology and epidemiology. A significant part of her research has involved dealing with intractable likelihoods, and the associated tools to fitting such models using a variety of different approaches, including Bayesian approaches, approximate likelihoods, imputation approaches and numerical integration. State-space models and hidden (semi-)Markov models have proven to be a very powerful tool in modelling a vast range of different systems, separating the true underlying system from the associated observation process are of particular interest, including the associated model-fitting tools. Further interest lies in integrating different forms of data within a single robust analysis; dealing with missing data and incorporating different forms of heterogeneity.

Dr Anthony Lee

Anthony Lee is Programme Director for the Alan Turing Institute-Intel partnership.

A Computational Statistician in the Department of Statistics at the University of Warwick, Anthony received BSc. and MSc. degrees in Computer Science from the University of British Columbia, and a DPhil. in Statistics from the University of Oxford. He was previously a Centre for Research in Statistical Methodology Research Fellow at the University of Warwick.

He serves on the Editorial Board for Statistics and Computing and the Journal of Computational and Graphical Statistics, and is the first Course Director of the BSc. Data Science degree at the University of Warwick.

Professor Helen Margetts, University of Oxford

BIO

Helen Margetts is Professor of Society and the Internet and Director of the Oxford Internet Institute, University of Oxford. She is a political scientist specialising in digital era governance and politics, investigating political behaviour and political institutions in the age of the internet, social media and big data. She has published over a hundred books, articles and major research reports in this area, including Political Turbulence: How Social Media Shape Collective Action (with Peter John, scott Hale and Taha Yasseri, 2015); Paradoxes of Modernization (with Perri 6 and Christopher Hood, 2010); Digital Era Governance(with Patrick Dunleavy, 2006); and The Tools of Government in the Digital Age (with Christopher Hood, 2007). In 2003 she and Patrick Dunleavy won the ‘Political Scientists Making a Difference’ award from the UK Political Studies Association, in part for a series of policy reports onGovernment on the Internet for the UK National Audit Office (1999, 2002 and 2007), and she continues working to maximise the policy impact of her research. She is editor-in-chief of the journal Policy and Internet. She is a fellow of the Academy of Social Sciences and a Faculty Fellow of the Alan Turing Institute for Data Science.

Professor Margetts joined the OII in 2004 from University College London where she was a Professor in Political Science and Director of the School of Public Policy. She began her career as a computer programmer and systems analyst with Rank Xerox after receiving her BSc in mathematics from the University of Bristol. She returned to study at the London School of Economics and Political Science in 1989, completing an MSc in Politics and Public Policy in 1990 and a PhD in Government in 1996. She worked as a researcher at LSE from 1991 to 1994 and a lecturer at Birkbeck College, University of London from 1994 to 1999.

Professor David Pym, University College London

BIO

David Pym is Professor of Information, Logic, and Security at UCL and is The Alan Turing Institute’s University Liaison Director for UCL. He holds a PhD in logic and theoretical computer science from Edinburgh,and an MA and an ScD in mathematics from Cambridge. He is a Fellow of the IMA and the BCS. David spent many years with Hewlett-Packard’s Research Laboratories, where he developed interests in systems, security, and economics.

David will work on a range of topics in security and privacy in distributed information-processing systems. He is interested in questions about access control in distributed systens, security and privacy policy, and the economics of security management. He is also interested in understanding basic questions in distributed systems architecture and behaviour, such as consistency and the relationship between systems management policies and systems architecture. David addresses these issues using ideas and techniques from logic, theoretical computer science, probability theory, and economics. He aims to build both conceptual and implemented tools to support decision-making in systems and policy design.

Dr Jonathan Shaw

Jonathan Shaw is Programme Director for the Alan Turing Institute-HSBC partnership. Jonathan is an economist and data scientist whose research focuses on modelling individual behaviour, evaluating education and labour market programmes, and understanding the effects of taxes and benefits across life. Before joining the Alan Turing Institute, he worked at the Institute for Fiscal Studies for almost 15 years, the last four of which he was Deputy Director of the Tax Administration Research Centre. He has done work for government departments in the UK and abroad, regulators and private charitable foundations and has provided economic advice to a wide variety of policymakers in governmental and quasi-governmental organisations. He did his PhD in empirical economics at University College London under Professor Sir Richard Blundell.

Professor Jared Tanner, University of Oxford

BIO

Jared Tanner is Professor of the Mathematics of Information at the University of Oxford and The Alan Turing Institute’s University Liaison Director for Oxford. He obtained his PhD (2002) in applied mathematics at the University of California at Los Angeles, and was a postdoctoral fellow at the University of California at Davis (Maths) and Stanford University (Stats.) where he worked with David L. Donoho.  Prior to joining the University of Oxford in 2012 he was Professor of the Mathematics of Information at the University of Edinburgh (2007-2012).  He is founding editor-in-chief of Information and Inference: A Journal of the IMA, whose mission is to publish high quality mathematically oriented articles furthering the understanding of the theory, methods of analysis, and algorithms for information and data.  He is also on the editorial board for Applied and Computational Harmonic Analysis, Multiscale modelling and simulation A SIAM Interdisciplinary Journal, and was an associate editor for the Princeton Companion to Applied Mathematics.  His research has appeared in the Proc Natl Acad Sci USA, Phil Trans Royal Soc A, and other leading journals.

Jared Tanner’s research concerns extracting models of high dimensional date which reveal of the essential information in the data.  Specific contributions include the derivation of sampling theorems in compressed sensing using techniques from stochastic geometry and the design and analysis of efficient algorithms for matrix completion which minimise over higher dimensional subspaces as the reliability of the data warrants.  These techniques allow more efficient information acquisition as well as the ability to cope with missing data.

Recent interests include new models for low dimensional structure in heterogeneous data and topological data analysis.

Professor Ulrike Tillmann, University of Oxford

BIO

Prof. Ulrike Tillmann FRS has been at the University of Oxford since 1992. She is an algebraic topologist, known in particular for her work on Riemann surfaces and the homology of their moduli spaces. She has long standing research interest in homology stability questions. In 2011 she introduced an annual course (with Abramsky) in Computational Algebraic Topology at masters level. In the last year, Tillmann has co-organized four workshops on topological data analysis, as well as an CMI-LMS research school.

She held an EPSRC Advanced Fellowship 1997-2003. She was invited to present at the ICM in 2002 and was a member of the topology subject panel for both the 2010 and 2014 ICMs. In 2008 she was made a Fellow of the Royal Society and received the Bessel Forschungspreis from the Humboldt Gesellschaft. She is an inaugural Fellow of the AMS.

Algebraic topology and its applications. Algebraic topology is a very effective tool to study the global properties of geometric objects. For example, take the surface of a ball and divide it into triangles; now count the number of faces, add the number of vertices and subtract the number of edges; no matter how you choose your triangles, the result will always be 2. Do the same with the surface of a donut and the result is always 0. These numbers were already known by Euler and are foreshadows of homology developed in the 20th century. By now the basic ideas of algebraic topology have permeated nearly every branch of research in mathematics.

Her own research has been motivated by questions in quantum physics and string theory. In particular, she has contributed to our understanding of the ‘space of surfaces’.

Professor Chris Williams, University of Edinburgh

BIO

Chris Williams is Professor of Machine Learning in the School of Informatics, University of Edinburgh, and is The Alan Turing Institute’s University Liaison Director for Edinburgh. He obtained his MSc (1990) and PhD (1994) at the University of Toronto, under the supervision of Geoff Hinton. He was a member of the Neural Computing Research Group at Aston University from 1994 to 1998, and has been at the University of Edinburgh since 1998.

Chris is interested in a wide range of theoretical and practical issues in machine learning, statistical pattern recognition, probabilistic graphical models and computer vision. This includes theoretical foundations, the development of new models and algorithms, and applications. His main areas of research are in models for understanding time-series, visual object recognition and image understanding, unsupervised learning, and Gaussian processes. At the Turing he also has interests in improving the data analytics process, looking to address the issues of data understanding and preparation that are widely quoted as taking around 80% of the time in a typical data mining project.

Sir Alan Wilson

BIO

Sir Alan Wilson FBA FAcSS FRS is CEO of The Alan Turing Institute and Professor of Urban and Regional Systems in the Centre for Advanced Spatial Analysis at University College London. He is Chair of the Home Office Science Advisory Council.

He is a Cambridge Mathematics graduate and began his research career in elementary particle physics at the Rutherford Laboratory. He turned to the social sciences, working on cities, with posts in Oxford and London before becoming Professor of Urban and Regional Geography in Leeds in 1970. He was a member of Oxford City Council from 1964-1967. In the late 1980s, he was the co-founder of GMAP Ltd, a University spin-out company. He was Vice-Chancellor of the University of Leeds from 1991 to 2004 when he became Director-General for Higher Education in the then DfES. After a brief spell in Cambridge, he joined UCL in 2007. From 2007-2013 he was Chair of the Arts and Humanities Research Council; and from 2013-2015, he was Chair of the Lead Expert Group for the Government Office for Science Foresight Project on The Future of Cities. He is a Member of Academia Europaea, an FBA, an FAcSS and an FRS. He was knighted in 2001. In August 2017, he received an honorary degree from the School of Advanced Study, University of London in recognition of his outstanding contributions to higher education.

His research field covers many aspects of mathematical modelling of cities and the use of these models in planning. These techniques are now in common use internationally – including the use of the concept of entropy in building spatial interaction models – summarised in Entropy in urban and regional modelling (re-issued in 2011 by Routledge). These models have been widely used in areas such as transport planning, demography and economic modelling. His recent research is on the applications of dynamical systems theory in relation to modelling the evolution of urban structure in both historical and contemporary settings. This led to the laying of the foundations of a comprehensive theory of urban dynamics described in Complex spatial systems (2000). He has published over 200 papers and his recent books include The science of cities and regions (2012), his five volume Urban modelling (2012, edited), Explorations in urban and regional dynamics (2015, with Joel Dearden), Global dynamics (2016, edited) and Geo-mathematical modelling (2016, edited). He has a particular interest in interdisciplinarity and published Knowledge power in 2010; he writes the quaestio blog (www.quaestio.blogweb.casa.ucl.ac.uk).

Commercial Development Board

Howard Covington (Chair)

Howard Covington is the founding chair of the Alan Turing Institute. He had a career in the City as an investment banker and asset manager. He became a director of SG Warburg and then European chief executive of Wasserstein Perella, a US investment bank. He co-founded New Star Asset Management and was its chief executive until it was sold to Henderson in 2009.

John Barker

John Barker has made his career in M&A and corporate finance, principally at Dresdner Kleinwort Benson as Global Head of the Electronics and Engineering sectors. He founded Mid-Market Capital, a corporate finance firm of which he is chairman, in 2001. John is the founding Chairman and Senior Adviser to Demeter, the board and executive search company, where he works with many of the Chairmen and CEOs of FTSE 100 and 250 PLCs and private equity firms. He sat until recently on the development board of the Isaac Newton Institute for Mathematical Sciences, Cambridge University.

Michael Ross

Michael is a graduate of Trinity College, Cambridge where he received a double first in mathematics and he has spent the last 23 years at the intersection of the digital and data worlds.  He is the co-founder and chief scientist of DynamicAction, a leader in big data analytics and AI for retail.  He was previously the founder and CEO of figleaves.com. Michael started his career at McKinsey consulting in the early days of the internet. He is a non-executive director of Sainsbury’s Bank, and a trustee of In Kind Direct.

Hitesh Thakrar

Hitesh Thakrar is an experienced investor in the technology sector, having spent over 20 years investing in public equities in the life sciences, information technology and innovation sectors. He is a partner of Syncona Investment Management and a member of the investment committee of the LBA Scale Up Innovation Fund. He is also a director of Desktop Genetics, a CRISPR IP library company and is an angel investor in early stage innovation companies.

Hitesh has worked at various institutions in equity research and fund management including ADIA, Abu Dhabi’s sovereign wealth fund, JP Morgan, Aviva Group, Dresdner Bank and New Star Asset Management. He has been a top 1 percentile manager in global innovation companies. Hitesh has a degree in chemistry from Kings College, London, an MBA from Cranfield University and a CFA from the American Association of Investment Analysts.