DR RICHARD DAVIS

Research Associate

Computer Engineering Lab
School of Electrical and Information Engineering
Room 856, Building J03, Maze Cresent
University of Sydney
Australia 2006
Tel: +61 2 9351 4491
Email: Firstname DOT Lastname AT sydney DOT edu DOT au

Biography:

Since June 2012 Dr Richard Davis has been a Research Associate in the School
of Electrical & Information Engineering, University of Sydney.

Research Interests:

  • Machine learning
  • Pattern recognition
  • Reconfigurable computing
  • Signal processing
  • Information theory

Selected Publications:

Journal articles:

  • Richard Davis and Brian C. Lovell, ‘Comparing and Evaluating HMM Ensemble Training Algorithms Using Train and Test and Condition Number Criteria’, Journal of Pattern Analysis and Applications, 2003.
  • R. I. A. Davis, R. Delbourgo, P. Jarvis, ``Quantum Covariance and Entanglement’’, Journal of Physics A (2000). [quant-ph/0001076].
  • R. I. A. Davis, R. Delbourgo, P. Jarvis, ``Quantum Covariance and Entanglement’’ (Addendum), Journal of Physics A (2000) [quant-ph/0002090]

Conference papers:

  • R. I. A. Davis, B. Lovell, “Learning Hidden Markov Models from Multiple Observation Sequences, International Congress on Pattern Recognition, Quebec 2002.
  • R. I. A. Davis, C. J. Walder and B. C. Lovell, Improved Classification using Hidden Markov Averaging from Multiple Observation Sequences, In the Proceedings of the Workshop on Signal Processing and Applications, Brisbane, 2002
  • R. I. A. Davis and B. C. Lovell, Improved Ensemble Training for Hidden Markov Models using Random Relative Node Permutations, Proceedings of the Workshop on Digital Image Computing (WDIC2003), pp. 83-86, February 7, Brisbane, Australia, 2003
  • N. Liu, R. I. A. Davis, B. C. Lovell, P. J. Kootsookos, Effect of Initial HMM Choices in Multiple Sequence Training for Gesture Recognition'', Proceedings of the International Conference on Information Technology, Las Vegas, Nevada USA, 2004.
  • M. Howlett, T. Nguyen, R.I.A. Davis, “A 3-channel biorthogonal filter bank construction based on predict and update lifting steps”, Workshop on Signal Processing and Applications 2002
  • Nianjun Liu, Brian C. Lovell, Peter J. Kootsookos and Richard I.A. Davis, Model Structure Selection and Training Algorithms for a HMM Gesture Recogniser", 9th IAPR International Workshop on Frontiers in Handwriting Recognition (IWFHR-9), Toyko, Japan. October 26-29, 2004.
  • Nianjun Liu, Brian C. Lovell, Peter J. Kootsookos and Richard I.A. Davis, "Special Shape Gestures to enhance HMM Model Training." IEEE TENCON 2004, ChangMai, Thailand. 21-24, November 2004

PhD projects offered

  • Feature generation and selection
  • Parallisation of machine learning algorithms.
  • Hidden markov model and FPGAs

Potential students should investigate ARC and Sydney university PhD scholarship options on the respective websites.