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  2. David Calvert

David Calvert

David Calvert

Professor Emeritus

College of Computational, Mathematical and Physical Sciences, School of Computer Science

Available positions for grads/undergrads/postdoctoral fellows
Yes

Research Areas

  • Parallel
  • Music
  • Modelling
  • Classification
  • Artificial neural networks
  • Agriculture

Education and Employment Background

Dr. David Calvert received his PhD from the University of Waterloo. He has held positions as a programmer/researcher at INM Inc., E.S. Aquatic Co., and Mortice Kem Systems Inc. He joined the School of Computer Science at the University of Guelph in 1998 where he is now an Associate Professor.

Research Themes

Calvert’s research focusses on classification and modelling, primarily using artificial neural networks. It generally involves biological data from agricultural or public health sources. Recently, he has been working with parallel patterns on GPUs and with visualizing pitch class sets for 20th century music. Key areas of focus include:

  1. Artificial Neural Networks (ANNs) in applied and theoretical contexts. Calvert examines network architectures and their application to several different problem domains. This work centers around the use of ANNs for sequence modelling and simulation.
  2. Analysis of atonal music. Here, Calvert is developing software tools to read data files, generate the sets from music data, and graphically display the results. Calvert will analyze the structures identified by the sets.

Highlights

  • Natural Science and Engineering Research Council of Canada grant, 1999, 2005
  • Site Leader Grant, SHARCNET, 2007