Jeff OrchardResearch interests

Professor Orchard's main research interest is computational neuroscience, using mathematical models and computer simulations of neural networks to understand how the brain works. Guided by both theory and anatomy, he is building large-scale neural networks based on computational theories of the brain, such as predictive coding, to uncover the way we perceive the world. His research also includes projects in decision-making network models of the basal ganglia, unsupervised learning of vision networks, spatial navigation, and population coding. He is a core member of the Centre for Theoretical Neuroscience.

Professor Orchard has also done research in the area of image processing and medical imaging. He developed a method to register (align) several images simultaneously; this is a departure from the conventional two-at-a-time registration. He has also published a number of other papers on image registration, image reconstruction for MRI and CT, denoising, image mosaicking, and forensic image processing

Degrees and awards

BMath (Waterloo), MSc (British Columbia), PhD (Simon Fraser)

Representative publications

J. Orchard, H. Yang, X. Ji, Does the Entorhinal Cortex use the Fourier Transform?, Frontiers in Computational Neuroscience, 7, article 179, 2013.

B.P. Tripp, J. Orchard, Population Coding in Sparsely Connected Networks of Noisy Neurons, Frontiers in Computational Neuroscience, 6, article 23, 2012.

J. Orchard, H.-Y. Kim, J. T. W. Yeow, Plausibility of Image Reconstruction Using a Proposed Flexible and Portable CT Scanner, The Open Medical Imaging Journal,  6:1-11, 2012. 

J. Orchard, R. Mann. Registering a Multi-Sensor Ensemble of Images. IEEE Transactions on Image Processing, 19(5):1236-1247, 2010.

Y. Wang, J. Orchard, Fast Discrete Orthonormal Stockwell Transform, SIAM Journal on Scientific Computing, 31(5):4000-4012, 2009.

J. Orchard and C. Kaplan. Cut-Out Image Mosaics. Proceedings of the 6th Symposium on Non-Photorealistic Animation and Rendering (NPAR), pp. 79-87, 2008.

J. Orchard. Multimodal Image Registration using Floating Regressors in the Joint Intensity Scatter Plot. Medical Image Analysis, 12(4):385-396, 2008.

J. Orchard, J.T.W. Yeow. Toward a Flexible and Portable CT Scanner. Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 188-195, 2008.

J. Orchard. Efficient Least-Squares Multimodal Registration with a Globally Exhaustive Alignment Search. IEEE Transactions on Imaging Processing, 16(10):2526-2534, 2007.

J. Orchard, C. Greif, G.H. Golub, B. Bjornson, and M.S. Atkins. Simultaneous Registration and Activation Detection for fMRI. IEEE Transactions on Medical Imaging special issue on Medical Image Registration, 22(11):1427-1435, 2003.

University of Waterloo
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