Faculty profile
Leonid Sigal
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Read how they describe their research on their University of British Columbia profile.
Latest papers
CNN-extracted features generate synthetic fMRI responses to unseen images.
Vision research · 2025
Latest funding
- $55,000
Scalable and Efficient Multimodal Visual Understanding and Generation
NSERC · 2024 · Principal investigator
- $108,000
Multi-Modal Perceptual Systems for Sport Analytics
NSERC · 2024 · Co-investigator
- $450,000
Advanced Machine Learning Training Network (AML-TN)
NSERC · 2023 · Co-investigator
1 publications.
CNN-extracted features generate synthetic fMRI responses to unseen images.
Delavari P, Sigal L, Oruc I
Scalable and Efficient Multimodal Visual Understanding and Generation
Principal investigators: Sigal, Leonid
Keywords: computer vision; machine learning; neural networks; representation and deep learning; multi-modal (visual+language) learning; generative modeling; image and video understanding; recognition, detection and segmentation; weakly- and semi-supervised learning; structured learning
Multi-Modal Perceptual Systems for Sport Analytics
Principal investigators: Mohammadi, Arash A
Keywords: big data analytics; computer vision; deep learning; machine learning; signal/image processing
Advanced Machine Learning Training Network (AML-TN)
Principal investigators: Wood, Frank FD
Keywords: artificial intelligence; computer vision; differential privacy; human-centered ai; inference; kernel methods; machine learning; natural language processing; optimization; probabilistic programming
Automatic Assessment of Aortic Stenosis with Point of Care Ultrasound
Principal investigators: Abolmaesumi, Purang; Tsang, Michael Y; Tsang, Teresa S
Keywords: Aortic Stenosis; Echocardiography; Machine Learning; Point-Of-Care Imaging; Ultrasound Imaging
Computer Vision and Machine Learning
Principal investigators: Sigal, Leonid
Keywords: Computer Vision; Machine Learning; Image and Video Understanding; Multimodal (Vision + Sound + Language) Learning; Deep Learning; Structured Prediction Models; Generative Models; Human Pose Estimation; Data-efficient (zero-, few-, weak-supervision) Learning ; Semantic Recognition
UBC ML Computational Cluster
Principal investigators: Wood, Frank
Web-Scale Semantic Image and Video Understanding
Principal investigators: Sigal, Leonid
Web-Scale Semantic Image and Video Understanding
Principal investigators: Sigal, Leonid
Canada Research Chair in Computer Vision and Machine Learning
Principal investigators: Sigal, Leonid
Canada Research Chair in Computer Vision and Machine Learning
Principal investigators: Sigal, Leonid
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
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Profile data last refreshed on September 27, 2026 from the university directory, publication records and CIHR, NSERC and SSHRC funding.