Alan Yuille

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Alan L. Yuille
NationalityAmerican, English, Australian
Alma materUniversity of Cambridge (B.A., 1976)
University of Cambridge (Ph.D., 1981)
Scientific career
FieldsComputer Vision
Machine Learning
Statistical Modeling
Artificial Intelligence
ThesisTopics in Quantum Gravity
Doctoral advisorS. W. Hawking
WebsiteCCVL Group website

Alan Yuille (born 1955) is a Bloomberg Distinguished Professor of Computational Cognitive Science[1] with appointments in the departments of Cognitive Science[2] and Computer Science[3] at Johns Hopkins University. Yuille develops models of vision and cognition for computers, intended for creating artificial vision systems.[1] He studied under Stephen Hawking at Cambridge University on a PhD in theoretical physics, which he completed in 1981.


Alan Yuille obtained a Bachelor of Arts degree in mathematics from the University of Cambridge in 1976, where he also earned his PhD in theoretical physics in 1981.[3] He then completed a postdoctoral fellowship at the University of Texas at Austin and the University of California, Santa Barbara. Yuille served as a research scientist first at the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology, where he stayed from 1982 until 1986, and then at Harvard University. Here, he was promoted to Assistant Professor of Computer Science in 1988 and Associate Professor in 1992. In 1995, he joined the Smith-Kettlewell Eye Research Institute in San Francisco as a Senior Research Scientist. In 2002, he was appointed as a full professor in the Department of Statistics at the University of California, Los Angeles with joint appointments in the departments of computer science, psychiatry, and psychology.[4] He also served as co-director of the UCLA Center for Cognition, Vision, and Learning.[5] In 2016, Yuille joined Johns Hopkins University as the Bloomberg Distinguished Professor of Computational Cognitive Science.[6] The Bloomberg Distinguished Professorship program was established in 2013 by a gift from Michael Bloomberg to endow professors whose areas of expertise bridge traditional academic disciplines and promote cross-disciplinary research and collaboration.[7][8] Yuille holds appointments in the Department of Cognitive Science in the Zanvyl Krieger School of Arts and Sciences and in the Department of Computer Science in the Whiting School of Engineering.[1]


Yuille develops mathematical models of vision and cognition that enable computers to reconstruct three-dimensional structures based on images or videos.[6] His research interests include computational models of vision, mathematical models of cognition, medical image analysis, and artificial intelligence and neural networks.[3] He directs the Computational Cognition, Vision, and Learning (CCVL) research group at Johns Hopkins University.[2] Yuille and the CCVL develop models for designing artificial vision systems to provide assistance for people with vision impairments;[9] computational models of biological vision;[10] computational models of cognition to study how humans and animals perform tasks such as learning and reasoning;[11][12] and models for machine learning to interpret medical images.[13]

Yuille is currently working on The Felix Project (named after the fictional potion Felix Felicis, which, in the world of Harry Potter, brings drinkers unusually good luck). The project aims to use deep learning to improve early detection of pancreatic cancer by training computers to recognize it in CT scans and magnetic resonance images.[14][15] Yuille and collaborators are attempting to develop algorithms to interpret CT and MR images of the pancreas and distinguish between a normal pancreas and a pancreas with a range of pathologies including tumors.[16]


  • Helmholtz Test of Time Award, 2013
  • IEEE Fellow, 2009
  • Marr Prize, ICCV 2003[4]
  • Honorary mention Marr Prize, ICCV 1988
  • Rayleigh Research Prize, 1979
  • Rouse Ball Prizes, 1974, 75, 76, and 77


Yuille has over 300 publications[17] including three books (one co-edited).


  • Two- and Three- Dimensional Patterns of the Face, P.W. Hallinan, G. Gordon, A.L. Yuille, P.J. Giblin and D.B. Mumford, Research Monograph, A K Peters, Ltd. 1999.
  • Active Vision, Eds. A. Blake and A.L. Yuille, MIT Press, Cambridge, MA, Oct. 1992.
  • Data Fusion for Sensory Information Processing Systems, J.J Clark and A.L. Yuille, Kluwer Academic Publisheres, Boston, 1990.


  1. ^ a b c "Bloomberg Distinguished Professorships | Alan Yuille". Johns Hopkins Office of Research.
  2. ^ a b "Cognitive Science Faculty Page".
  3. ^ a b c "Computer Science Faculty Page".
  4. ^ a b "Alan Yuille". IEEE Explore Digital Library. Retrieved 3 February 2020.
  5. ^ "Statistics professors' paper awarded for impact in field of computer vision". UCLA. Retrieved 2020-03-03.
  6. ^ a b July 8, Kelly Brooks / Published; 2015 (2015-07-08). "Four new Bloomberg Distinguished Professors named at Johns Hopkins". The Hub. Retrieved 2020-03-03.CS1 maint: numeric names: authors list (link)
  7. ^ "Michael R. Bloomberg Commits $350 Million to Johns Hopkins for Transformational Academic Initiative « News from The Johns Hopkins University". Retrieved 2020-03-03.
  8. ^ Jan 26, Hub staff report / Published; 2013 (2013-01-26). "Michael R. Bloomberg commits $350 million to Johns Hopkins for transformational academic initiative". The Hub. Retrieved 2020-03-03.CS1 maint: numeric names: authors list (link)
  9. ^ Zhuowen Tu; Xiangrong Chen; Yuille; Zhu (2003). "Image parsing: unifying segmentation, detection, and recognition". Proceedings Ninth IEEE International Conference on Computer Vision. IEEE: 18-25 vol.1. doi:10.1109/iccv.2003.1238309. ISBN 0-7695-1950-4. S2CID 37907570.
  10. ^ Tu, Zhuowen; Yuille, Alan L. (2004), "Shape Matching and Recognition – Using Generative Models and Informative Features", Lecture Notes in Computer Science, Springer Berlin Heidelberg, pp. 195–209, doi:10.1007/978-3-540-24672-5_16, ISBN 978-3-540-21982-8
  11. ^ Chater, Nick; Tenenbaum, Joshua B.; Yuille, Alan (July 2006). "Probabilistic models of cognition: Conceptual foundations". Trends in Cognitive Sciences. 10 (7): 287–291. doi:10.1016/j.tics.2006.05.007. ISSN 1364-6613. PMID 16807064. S2CID 7547910.
  12. ^ Lu, Hongjing; Yuille, Alan L.; Liljeholm, Mimi; Cheng, Patricia W.; Holyoak, Keith J. (2008). "Bayesian generic priors for causal learning". Psychological Review. 115 (4): 955–984. doi:10.1037/a0013256. ISSN 1939-1471. PMID 18954210.
  13. ^ Corso, J.J.; Sharon, E.; Dube, S.; El-Saden, S.; Sinha, U.; Yuille, A. (May 2008). "Efficient Multilevel Brain Tumor Segmentation With Integrated Bayesian Model Classification". IEEE Transactions on Medical Imaging. 27 (5): 629–640. doi:10.1109/tmi.2007.912817. ISSN 0278-0062. PMID 18450536. S2CID 2018752.
  14. ^ "For Some Hard-To-Find Tumors, Doctors See Promise In Artificial Intelligence". Retrieved 2020-03-03.
  15. ^ "Innovator Honored with Endowed Professorship". Johns Hopkins Center for Innovative Medicine. Retrieved 2020-03-03.
  16. ^ Lugo-Fagundo, Carolina; Vogelstein, Bert; Yuille, Alan; Fishman, Elliot K. (2018-02-01). "Deep Learning in Radiology: Now the Real Work Begins". Journal of the American College of Radiology. 15 (2): 364–367. doi:10.1016/j.jacr.2017.08.007. ISSN 1546-1440. PMID 29290592.
  17. ^ "Alan Yuille Google Scholar".