Hancock is Emeritus Professor of Computer Vision in the Department of Computer Science at the University of York, and Adjunct Professor and Principal Investigator of the Beijing Innovation Centre for Big Data and Brain Computing at Beihang University. He commenced his research career in the field of high energy nuclear physics, working on bubble chamber experiments performed at CERN and SLAC between 1977 and 1984. During this period he used partial wave analysis to study the angular momentum resonances of Ʌ and Σ hyperons and was involved in the first determination of charm quark lifetimes. In 1985 he changed fields to work in computer science, and currently undertakes research in the use of graph-based methods in computer vision, pattern recognition and complex networks. He focuses on how pattern recognition and machine learning can be performed using data in the form of graphs, trees and strings. He is best known for his work on graph matching and spectral graph theory. He also works on physics based vision, where he has focused on how to recover surface shape and surface sub-structure from information conveyed by the scattering of light and from polarisation measurements. He has published extensively on these topics. He was named Fellow of the Institute of Electrical and Electronics Engineers in 2016 for contributions to pattern recognition and computer vision, and as a Fellow of the International Association for Pattern Recognition in 2000. He was awarded a doctorate honoris causa by the University of Alicante in 2015. In 2016 he was appointed Editor-in-Chief of the journal Pattern Recognition. Between 2016 and 2018 he was second vice-president of the International Association for Pattern Recognition. Between 2009 and 2014, he held a Royal Society Wolfson Research Merit Award. In 1991 he was awarded the Seventeenth Annual Pattern Recognition Award, for his paper titled "Discrete Relaxation", co-authored with Josef Kittler and published in the journal Pattern Recognition, and in 1999 an honourable mention in the Twentyfourth Award for the paper "Matching Delaunay Graphs", with Andrew M. Finch and Richard C. Wilson. The British Machine Vision Association awarded him its Distinguished Fellowship for 2016. In 2018 he received the Pierre Devijver Award from the International Association for Pattern Recognition.
Selected publications
;Research Articles
Richard C. Wilson, Edwin R. Hancock, Structural Matching by Discrete Relaxation. IEEE Trans. Pattern Anal. Mach. Intell. 19: 634–648.
Andrew D. J. Cross, Edwin R. Hancock, Graph Matching With a Dual-Step EM Algorithm. IEEE Trans. Pattern Anal. Mach. Intell. 20: 1236–1253.
Philip L. Worthington, Edwin R. Hancock, New Constraints on Data-Closeness and Needle Map Consistency for Shape-from-Shading. IEEE Trans. Pattern Anal. Mach. Intell. 21: 1250–1267.
Bin Luo, Edwin R. Hancock, Structural Graph Matching Using the EM Algorithm and Singular Value Decomposition. IEEE Trans. Pattern Anal. Mach. Intell. 23: 1120–1136.
Marco Carcassoni, Edwin R. Hancock, Correspondence Matching with Modal Clusters. IEEE Trans. Pattern Anal. Mach. Intell. 25: 1609–1615 : 1112–1124.
Antonio Robles-Kelly, Edwin R. Hancock, Graph Edit Distance from Spectral Seriation. IEEE Trans. Pattern Anal. Mach. Intell. 27: 365–378.
William A. P. Smith, Edwin R. Hancock, Recovering Facial Shape Using a Statistical Model of Surface Normal Direction. IEEE Trans. Pattern Anal. Mach. Intell. 28: 1914–1930.
Andrea Torsello, Edwin R. Hancock, Learning Shape-Classes Using a Mixture of Tree-Unions. IEEE Trans. Pattern Anal. Mach. Intell. 28: 954–967.
Gary A. Atkinson, Edwin R. Hancock, Shape Estimation Using Polarization and Shading from Two Views. IEEE Trans. Pattern Anal. Mach. Intell. 29: 2001–2017.
Huaijun Qiu, Edwin R. Hancock, Clustering and Embedding Using Commute Times. IEEE Trans. Pattern Anal. Mach. Intell. 29: 1873–1890.
