Alexander Wong

Alexander Wong, PhD, 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 Lab, and an associate professor in the Department of Systems Design Engineering at the University of Waterloo.

He received the BASc degree in Computer Engineering from the University of Waterloo in 2005, the MASc degree in Electrical and Computer Engineering from the University of Waterloo in 2007, and the PhD degree in Systems Design Engineering from the University of Waterloo 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.

• 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 102 - Seminar
  • Taught in 2016, 2017
• SYDE 770 - Communication & Info Systems
  • Taught in 2016
• SYDE 780 - Topics in Engineering Sciences
  • Taught in 2016, 2018, 2019
• BME 122 - Data Structures and Algorithms
  • Taught in 2016, 2017, 2018
• SYDE 372 - Intro to Pattern Recognition
  • Taught in 2016, 2017, 2018, 2019, 2020

• Kronfli, Nadine and Young, Jim and Wang, Shouao and Cox, Joseph and Walmsley, Sharon and Hull, Mark and Cooper, Curtis and Martel-Laferriere, Valerie and Wong, Alexander and Pick, Neora and others, Liver fibrosis in HIV-Hepatitis C virus (HCV) co-infection before and after sustained virologic response: what is the best non-invasive marker for monitoring regression?, Clinical Infectious Diseases, 2020
• Gunraj, Hayden and Wang, Linda and Wong, Alexander, Covidnet-ct: A tailored deep convolutional neural network design for detection of covid-19 cases from chest ct images, Frontiers in Medicine, 7, 2020
• Yu, Jingxin and Tang, Song and Zhangzhong, Lili and Zheng, Wengang and Wang, Long and Wong, Alexander and Xu, Linlin, A Deep Learning Approach for Multi-Depth Soil Water Content Prediction in Summer Maize Growth Period, IEEE Access, 8, 2020, 199097 - 199110
• Shafiee, Mohammad Javad and Jeddi, Ahmadreza and Nazemi, Amir and Fieguth, Paul and Wong, Alexander, Deep Neural Network Perception Models and Robust Autonomous Driving Systems: Practical Solutions for Mitigation and Improvement, IEEE Signal Processing Magazine, 38(1), 2020, 22 - 30
• Fewster, Kayla M and Haider, Shahid and Gooyers, Chad E and Callaghan, Jack and Wong, Alexander, A computerised system for measurement of the radial displacement of the intervertebral disc using a laser scanning device, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 8(3), 2020, 287 - 293

• Just say the word: New voice tech could run home appliances
• Redirecting research during the pandemic
• DarwinAI makes global list of promising AI startups
• Waterloo tech company helping farm crickets for food
• Screening for COVID-19 with AI
• Key advancement announced in COVID X-ray project
• Help pours in from around the world to develop new COVID-19 test
• Key advancement announced in COVID x-ray project
• Help pours in from around the world to develop new COVID-19 test
• New touchless device makes earlier detection of heart problems possible

• Currently accepting applications for graduate students