Associate Professor, Canada Research Chair in AI and Medical Imaging

Contact InformationAlexander Wong

Phone: 519-888-4567 x31299
Location: EC4 2019


Biography Summary

Alexander Wong, P.Eng., is currently the Canada Research Chair in Artificial Intelligence and Medical Imaging, Member of the College of the Royal Society of Canada, co-director of the Vision and Image Processing Research Group, and an associate professor in the Department of Systems Design Engineering at the University of Waterloo. He had previously received the B.A.Sc. degree in Computer Engineering from the University of Waterloo, Waterloo, ON, Canada, in 2005, the M.A.Sc. degree in Electrical and Computer Engineering from the University of Waterloo, Waterloo, ON, Canada, in 2007, and the Ph.D. degree in Systems Design Engineering from the University of Waterloo, ON, Canada, in 2010. He was also an NSERC postdoctoral research fellow at Sunnybrook Health Sciences Centre. He has published over 550 refereed journal and conference papers, as well as patents, in various fields such as computational imaging, artificial intelligence, computer vision, and multimedia systems.

In the area of computational imaging, his focus is on integrative computational imaging systems for biomedical imaging (inventor/co-inventor of Correlated Diffusion Imaging, Compensated Magnetic Resonance Imaging, Spectral Light-field Fusion Micro-tomography, Compensated Ultrasound Imaging, Coded Hemodynamic Imaging, High-throughput Computational Slits, Spectral Demultiplexing Imaging, and Parallel Epi-Spectropolarimetric Imaging). In the area of artificial intelligence, his focus is on operational artificial intelligence (co-inventor/inventor of , Generative Synthesis, evolutionary deep intelligence, Deep Bayesian Residual Transform, Discovery Radiomics, and random deep intelligence via deep-structured fully-connected graphical models). His work in Generative Synthesis has led to the founding of DarwinAI, a leading-edge AI company focused on accelerated deep learning development. He has received numerous awards including three Outstanding Performance Awards, a Distinguished Performance Award, an Engineering Research Excellence Award, a Sandford Fleming Teaching Excellence Award, an Early Researcher Award from the Ministry of Economic Development and Innovation, a Best Paper Award at the NIPS Workshop on NIPS Workshop on Transparent and Interpretable Machine Learning (2017), a Best Paper Award at the NIPS Workshop on Efficient Methods for Deep Neural Networks (2016), two Best Paper Awards by the Canadian Image Processing and Pattern Recognition Society (CIPPRS) (2009 and 2014), a Distinguished Paper Award by the Society of Information Display (2015), three Best Paper Awards for the Conference of Computer Vision and Imaging Systems (CVIS) (2015,2017,2018), Synaptive Best Medical Imaging Paper Award (2016), two Magna Cum Laude Awards and one Cum Laude Award from the Annual Meeting of the Imaging Network of Ontario, CIX TOP 20 (2017), Technology in Motion Best Toronto Startup (2018), Top Ten Startup at AutoMobility LA (2018), AquaHacking Challenge First Prize (2017), Best Student Paper at Ottawa Hockey Analytics Conference (2017), and the Alumni Gold Medal.

An up-to-date CV can be found here:

Research Interests

  • Artificial Intelligence
  • Image processing and data analytics
  • Medical imaging
  • Scanning
  • Sensors and devices
  • Drinking water
  • Autonomous and connected car
  • Automotive
  • Operational Artificial Intelligence
  • Robotics
  • Smart Infrastructure


  • 2010, Doctorate, Systems Design Engineering, University of Waterloo
  • 2007, Master of Applied Science, Electrical and Computer Engineering, University of Waterloo
  • 2005, Bachelor of Applied Science, Computer Engineering, University of Waterloo


  • BME 122 - Data Structures and Algorithms
    • Taught in 2015, 2016, 2017, 2018
  • SYDE 750 - Topics in Systems Modelling
    • Taught in 2015
  • SYDE 770 - Selected Topics in Communication and Information Systems
    • Taught in 2016
  • SYDE 780 - Selected Topics in Engineering Sciences
    • Taught in 2016, 2018, 2019
  • BME 102 - Seminar
    • Taught in 2016, 2017
  • SYDE 372 - Introduction to Pattern Recognition
    • Taught in 2015, 2016, 2017, 2018, 2019
* Only courses taught in the past 5 years are displayed.

Selected/Recent Publications

  • Scharfenberger, Christian and Chung, Audrey G and Wong, Alexander and Clausi, David A, Salient Region Detection Using Self-Guided Statistical Non-Redundancy in Natural Images, IEEE Access, 4, 2016, 48 - 60
  • Xu, Linlin and Wong, Alexander and Li, Fan and Clausi, David A, Intrinsic representation of hyperspectral imagery for unsupervised feature extraction, IEEE Transactions on Geoscience and Remote Sensing, 54(2), 2016, 1118 - 1130
  • Siva, Parthipan and Shafiee, Mohammad Javad and Jamieson, Mike and Wong, Alexander, Scene Invariant Crowd Segmentation and Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG), arXiv preprint arXiv:1602.00386, 2016
  • Kazemzadeh, Farnoud and Wong, Alexander, Laser light-field fusion for wide-field lensfree on-chip phase contrast nanoscopy, arXiv preprint arXiv:1604.08145, 2016
  • Cameron, Andrew and Khalvati, Farzad and Haider, Masoom A and Wong, Alexander, MAPS: a quantitative radiomics approach for prostate cancer detection, IEEE Transactions on Biomedical Engineering, 63(6), 2016, 1145 - 1156
  • Xu, Linlin and Wong, Alexander and Li, Fan and Clausi, David A, Extraction of Endmembers From Hyperspectral Images Using A Weighted Fuzzy Purified-Means Clustering Model, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(2), 2016, 695 - 707
  • Shafiee, MJ and Siva, P and Scharfenberger, C and Fieguth, P and Wong, A, NeRD: a Neural Response Divergence Approach to Visual Salience Detection, arXiv preprint arXiv:1602.01728, 2016
  • Amelard, Robert and Clausi, David A and Wong, Alexander, A spectral-spatial fusion model for robust blood pulse waveform extraction in photoplethysmographic imaging, arXiv preprint arXiv:1606.09118, 2016
  • Haider, SA and Cameron, A and Siva, P and Lui, D and Shafiee, MJ and Boroomand, A and Haider, N and Wong, A, Fluorescence microscopy image noise reduction using a stochastically-connected random field model, Scientific reports, 6, 2016
  • Shafiee, Mohammad Javad and Siva, Parthipan and Wong, Alexander, Stochasticnet: Forming deep neural networks via stochastic connectivity, IEEE Access, 4, 2016, 1915 - 1924
  • Wong, Alexander and Mishra, Akshaya and Fieguth, Paul and Clausi, David, An adaptive monte carlo approach to nonlinear image denoising, Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, January 2008, 1 - 4
  • Wong, Alexander, Illumination invariant active contour-based segmentation using complex-valued wavelets, 2008 15th IEEE International Conference on Image Processing, January 2008, 1089 - 1091
  • Wong, Alexander S and Newmark, David M and Rolfson, J Brett and Whiting, Randy J and Neureuther, Andrew R, Investigating Phase-Shifting Mask Layout Issues Using a Cad Toolkit, Electron Devices Meeting, 1991. IEDM'91. Technical Digest., International, January 1991, 705 - 708

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