Vic Rayward-Smith

Vic Rayward-Smith

Professor

  • 2.34 Sciences

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Personal profile

External Activities

  • Editor-in-chief: Journal of Mathematical Modelling and Algorithms
  • Editorial Board Member: Journal of Scheduling, Journal of Applied Intelligence
  • Funded invited senior research fellow, Monash, Australia, 2005
  • Joint guest editor of a special issue of JORS (Journal of OR Society) on data mining
  • International Conference on Intelligent Data Engineering and Automated Learning, programme committee (2002-2008)
  • GECCO, programme committee (2001-2010)
  • CIS, programme committee member (2005-2010)
  • CEC, programme committee member (2005-2010)
  • AIE/IEA, programme committee member (2005-2010)
  • EVOBIO, programme committee member (2004-2007)
  • OR Society, Accreditation panel
  • Fellow of BCS and Vice Chairman of BCS (East Anglia)
  • Fellow of OR Society
  • EPSRC college member

Specialisms

Application of modern techniques in computer science to the solution of large scale practical problems; data mining.

Academic Background

Vic gained an M.A. degree in Mathematics from Oxford and then a Diploma in Machine Intelligence from Edinburgh followed by a Ph.D. in formal language theory from London.

Some of this time has been spent on sabbatical, at UCSB and UCB in America, at SFU in Canada and at Monash in Australia.

He is on the programme committee of a number of conferences including IDEAL, GECCO and IEEE CEC, IEA/AIE

Biography

Professor Rayward-Smith moved to UEA some thirty years ago, and is a Fellow of the BCS, of the OR Society and of the IMA, a Chartered Engineer and a Chartered Mathematician. He is the editor-in-chief of the Journal of Mathematical Modelling and Algorithms (JMMA) published by Springer.

Editorial Work:

  • Editor-in-chief of Journal of Mathematical Modelling and Algorithms
  • Board member of Journal of Scheduling
  • Board member of Journal of Applied Intelligence.

Key Responsibilities

  • Director of Data Mining, Machine Learning and Statistics Laboratory
  • Member of Science Executive
  • Member of Senate
  • Member of University Disciplinary Committee

Key Research Interests and Expertise

Vic Rayward-Smith is part of the Data Mining, Machine Learning and Statistics Laboratory 

He comes from a mathematical background and has always enjoyed the more theoretical aspects of computing. However, his research is focussed on developing new models and algorithmic approaches for solving important practical problems. He has mostly been concerned with the application of new techniques to the solution of problems in scheduling and in machine learning. Most recently, he has been addressing problems arising from clustering, from aggregated data and from unreliable data as well as undertaking several medical data mining projects.

Selected Publications

Rayward-Smith, V.J., Measure Based Metrics for Aggregated Data, ,Intelligent Data Analysis, Vol 15, no 2 (in press)

Rayward-Smith, V. J. and Rebaine, D. Analysis of Heuristics for the UET two-machine flow-shop problem with time delays, Computers and Operations Research, Volume 35, Issue 10, Pages 3049-3392 (2008).

Rayward-Smith, V. J., Statistics to measure correlation for data mining applications. Computational Statistics and Data Analysis, Volume 51, Issue 8, Page(s) 3968-3982, 2007.

Reynolds, A. P., Richards, G., Iglesia, B. de la., and Rayward-Smith, V.J., Clustering Rules: A Comparison of Partitioning and Hierarchical Clustering Algorithms. Journal of Mathematical Modelling and Algorithms, Volume 5, Number 4, Page(s) 475-504, 2006.

List all publications by Professor Vic Rayward-Smith