
David Westwick
Professor
BASc
MScE
PhD
Contact information
Phone
Location
Preferred method of communication
Please contact me by email.
Research
Research areas
- System identification
- Optimization
Research activities
System identification
System Identification, essentially data driven modelling, involves the creation of mathematical models of dynamic systems using measurements of their inputs and outputs, while relying on a bare minimum of a-priori assumptions. My group focuses on developing methods for identifying nonlinear systems, in applications ranging from neuromuscular control and robotics to chemical process control and electric power systems.
Optimization
System Identification often boils down to minimizing the errors between the outputs of unknown system and the of model, resulting in an optimization problem. As a result, I have developed efficient techniques for solving several system identification related optimization problems.
Biography
David T. Westwick the BASc degree in engineering physics from The University of British Columbia (1986), and the MScE and PhD degrees in electrical engineering from The University of New Brunswick (1988) and McGill University (1995), respectively. His doctorate was followed by postdoctoral fellowships in the Department of Biomedical Engineering at Boston University, and the Systems and Control Engineering Group at Delft University of Technology. Since 1999, he has been a faculty member in the Department of Electrical and Computer Engineering at the Schulich School of Engineering, where he is currently holds the position of Professor and Department Head. He has held appointments as a Visiting Scholar at the Department of Fundamental Electricity and Instrumentation (ELEC) at the Vrije Universiteit Brussel, and at the Sensory Motor Performance Lab at the Rehabilitation Institute of Chicago/Northwestern University. His publications include over 150 papers in peer-reviewed journals and international conferences, as well as the book “Identification of Nonlinear Physiological Systems” (2003) published by John Wiley and Sons as part of the IEEE Engineering in Medicine and Biology Society book series.
Publications
Sadeghassadi, M, Macnab, CJB, Gopaluni, B, and Westwick, D, Application of Neural Networks for Optimal-Setpoint Design and MPC Control in Biological Wastewater Treatment, Computers and Chemical Engineering, 115:150-160, 2018.
Westwick, DT, Hollander, G. Karami, K, and Schoukens, J., Using Decoupling Methods to Reduce Polynomial NARX Models, IFAC System Identification Symposium pp. 796{801, 2018.
Farshidi, A., Behjat, L, Rakai, L, and Westwick, D., A Multiobjective Cooptimization of Buffer and Wire Sizes in High-Performance Clock Trees, IEEE Transactions on Circuits and Systems II, Express Briefs 64(4):412-416, 2017.
Dreesen, P., Westwick, D., Schoukens, J., and Ishteva, M., Modeling Parallel Wiener-Hammerstein Systems Using Tensor Decomposition of Volterra Kernels, 13th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2017), pp. 16-25, 2017.
Sadeghassadi, M., Macnab, C.J.B. and Westwick, D., Design of a Generalized Predictive Controller for a Biological Wastewater Treatment Plant, Water Science & Technology, 73(8):1986-2006, 2016.
Aldhaifallah, M., Westwick, D.T., and Nisar, K.S., Support Vector Machine Identification of a Parallel Cascade Model of Human Ankle Stiffness, Applied Mathematical Sciences, 10(28):1353{1358, 2016.Publication 1, 2016
Awards
2017
Fellow, Engineers Canada
Honorary Fellow, Geoscientists Canada
2013
Senior Member IEEE
2012
ECE Professor of the year
2010
ECE Professor of the year