ROBOTICS LAB
The Robotic Lab bring together SFU researchers in many robotic disciplines, including, multi-agent coordination, safe navigation, reinforcement learning, human-robot interactions, manipulation, human-centric AI, and affective computing.
NATURAL LANGUAGE LAB
Our lab has a particular focus on research into statistical machine translation and the visual and textual summarization of information contained in natural language.
MIA RESEARCH GROUP
Our team's research focuses on developing novel computer vision and machine learning methods capable of automatically interpreting images to mimic and complement human vision while being faster, more reproducible, and more accurate.
LIBBERCHT RESEARCH LAB
Our research group develops and applies machine learning methods for genomics. We apply these methods to various types of biological data sets, including DNA sequences, epigenetic data such as ChIP-seq and ATAC-seq and single cell data such as flow cytometry and single cell genomics. Our methods are focused on probabilistic graphical models, deep neural networks and convex and submodular optimization.
STRUCTURED MACHINE LEARNING LAB
Machine Learning for Structured Data: complex networks, multi-relational data, event logs. We apply graphical models, deep neural nets, and reinforcement learning.
DATABASE AND DATA MINING LAB
Our lab also investigates emerging applications of information systems posing new database systems challenges such as on-demand map generation and focused web crawlers. The challenges of on-demand map generation, for example, are the complexity of map generalization operations and the ill-defined notion of the quality of the resulting maps.
GRUVI LAB
We are an inter-disciplinary team of researchers working in visual computing, in particular, computer graphics and computer vision. Current areas of focus include 3D and robotic vision, 3D printing and content creation, animation, AR/VR, geometric and image-based modelling, machine learning, natural phenomenon, and shape analysis.