Kirsten has worked in robotics and electrical engineering creating ethanol from waste cellulose, reducing pain from pressure on neurofibromas, and on building underwater robots, adjustable high-heeled shoes, operating systems for Blackberries, and energy models.
My primary research interests lie in visual scene understanding. I am mainly concerned with solving problems arising in visual perception and action recognition, which are key components in many vision applications such as surveillance, robot guidance, multi-modal image interpretation, remote sensing, and visual field monitoring. I also focus my attention on the processing of optical/sonar images for underwater vision applications. Recently I’ve had a chance to explore many aspects falling at the edges between computer vision, computer graphics, and machine learning, such as performance-based animation, procedural animation, shape descriptors and spectral geometry for shape analysis.
I finished my B.Sc. and M.Sc. degrees in 2009 and 2012 respectively from the school of remote sensing and information engineering of Wuhan University in China. In Sep. 2012, I enrolled in University of Waterloo as a PhD candidate working under the co-supervision of Prof. Andrea Scott and Prof. David Clausi. I have a extensive background in satellite image classification, photogrammetry, remote sensing, data assimilation and LiDAR data processing.
My research interests include stochastic graphical learning and modeling for large-scale networks and data mining and visualization, affective computing, image processing, computer vision, signal processing, femtocell networking, network control theory, wideband spectrum sensing, and dynamic spectrum access. My current focus is on efficient high-resolution, remote spatial biosignals measurements using video imaging for affective computing.
His research interests primarily lie in artificial intelligence and computational imaging. 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).
Wen Zhang received his BASc in Systems Design Engineering from the University of Waterloo, Canada, in 2007, and his MASc in Systems Design Engineering from the University of Waterloo in 2009, where he was the recipient of the NSERC Graduate Scholarship. He currently works at Janro Imaging Laboratory in Montreal, Canada, the developers of the Stereoscopic Animation and Drawing Device (SANDDE), a system that allows artists and animators to create artwork directly in immersive 3D space.