Please read this if you are considering doing an honours thesis with me.
Please read this if you are considering doing graduate studies under my supervision.
I am a professor of computer science at the University of Ontario Institute of Technology. I also direct the visual computing lab that focuses on problems residing at the intersection of pattern recognition, computer vision, visual sensor networks, large-scale processing and computer graphics.
Visual computing lab is involved in number of exciting research problems:
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Latent Dirichlet VAE proposes a new view of hyperspectral pixel unmixing where the VAE's latent representation follows a Dirichlet distribution and models per-pixel abundances.
Using implicit neural representations for hyperspectral image compression.
A systematic study of the effects of spectral compression on hyperspectral pixel classification.
Optimal scale selection for object-based image analysis and interpretation in hyperspectral images.
A method for hyperspectral pixel unmixing that does not require labelled per-pixel "training" data.
A method that bridges the gap between the performance of trimap-based networks and the convenience of trimap-free networks.
What and where attention for convolutional neural networks
Cost-volume filtering for fast optical flow estimation
Accelerated cost-volume filtering for depth analysis
A formal algebraic framework for the mathematical description of computer vision pipelines.
Extracting three-dimensional flight trajectories of liquid droplets from video data.
Road boundary detection adverse lighting and environmental conditions.
A new deep learning unit, residual-dyad, for remote sensing image matching.
Cognitive/behavior visual serving controllers for capturing free-flying uncooperative satellites.
Motion vectors extracted from crowd videos are used to synthesize artificial crowds.
Caregiver feet localization from wheelchair mounted cameras for autonomous navigation.
A temporal boosted YOLOv4 model for bird detection around wind farms.
A web-based system for deploying anomalib for visual anomaly detection.
On aggregated vs. separating scoring methods for multivariate anomaly detection tasks.
Advanced computer graphics and vision simulation technologies to serve the needs of camera networks research.
Behavior-based controllers for passive and active PTZ cameras.
Neural networks learn general representations when trained to solve differential equations.
University of Toronto Hyperspectral-301 dataset consisting of three 301-channel hyperspectral images covering (1) suburban, (2) urban, and (3) forest landtypes.
Hyperspectral pixel unmixing benchmark. A synthetic hyperspectral image with nine endmembers and per-pixel abundances.
Synthetic hyperspectral dataset comprise materials (endmembers) found in Cuprite dataset. Unmixing models trained on this dataset can be used to perform unmixing on Cuprite dataset via transfer learning.
Covers topics discussed in both undergraduate and graduate computer vision courses.
Covers topics discussed in a first-year C++ programming courses.
Discusses the unreasonable effectiveness of convolutional neural networks for object detection.
Discusses topics, such as t-SNE, gradient descent, and variational and conditional autoencoders.
Discusses topics covered in the undergraduate simulation and modeling course.
CSCI 3240U
[Web]
Computational Photography
Fall 2025
CSCI 5520G
[Web]
Computer Vision and Deep Learning (graduate course)
Fall 2025
CSCI 3010U
[Web]
Simulation and Modeling
Last offered in Winter 2025
CSCI 4220U
[Web]
Computer Vision
Last offered in Winter 2025
CSCI 4440U
[Web]
Topics in Computer Science 1 (Human Action Recognition)
Last offered in Fall 2024
CSCI 5770G
[Web]
Machine Learning (graduate course)
Last offered in Winter 2023
MCSC 6230G/7230G
[Web]
Machine Learning and Deep Learning (Adv. Topics in HPC)
Last offered in Fall 2017
CSCI 1061U
[Web]
Programming Workshop II
Last offered in Winter 2021
CSCI 2050U
Computer Architecture
CSCI 5550G
[Web]
Topics in Digital Media
Last offered in Fall 2018
From time to time I find myself compelled to do some coding. Below I list some open source software that I have written that you may find useful.