Research

Artificial Intelligence at UBC focuses on decision-making and action, particularly on the design and application of AI systems that cooperate with human decision-makers. This AI research group and the breadth of its work is establishing UBC as leaders in sub-areas like privacy.

This area conducts research in areas like molecular computation, empirical algorithm design, algorithmic game theory, optimization and theoretical computer science.

CAIDA is UBC's ground zero for artificial intelligence. CAIDA is focused on the development, analysis, and application of AI systems for decision-making and action, enabled by core AI technologies such as machine learning and automated reasoning. It is part of the Institute for Computing, Information and Cognitive Systems (ICICS).

 The DFP cluster addresses complex human-facing design problems by accelerating creativity at the nexus of social and technical problem-solving. 

The data management and mining lab focuses on how to manage or mine data, relational or otherwise. This lab focuses on topics such as data understanding and exploration,  health data analysis, social networks , and web and graph databases.

The group works across the university's data science community and advanced computing teams, equipping researchers and external partners with the approaches, tools and expertise they need to fully leverage the potential of big data.

Our long term vision is to create ethical AI systems that humans can trust and collaborate with. Our major research areas are user-adaptive visualization, interfaces for decision support, multimedia interactive visualizations for opinion mining, and adaptivity in unstructured and open-ended interfaces.

This lab is inter-disciplinary, with members working together to advance the science of computer graphics, computer animation, visualization, haptics, and human computer interaction.

InfoVis focuses on developing visual representations and interaction techniques to take advantage of the human eye’s broad entry into the mind to allow users to see, explore, and understand large amounts of information at once.

The ISD group is interested in principles, techniques, methodologies, and tools for the specification, design, implementation, and verification of protocols, circuits, and integrated hardware/software systems. 

The Natural Language Processing Group conducts research in Computational Linguistics, Text Mining, Machine Learning, and Visual Text Analytics.

This lab is ground zero for conducting research on operating systems, distributed systems, security, and program analysis. 

 This group works in collaboration with partners from across industry and academia to develop production-quality, open-source software with applications in computational neuroscience, image recognition, robotics and AI.

In this lab, researchers develop fast, reliable, and robust numerical algorithms needed for modeling and simulation in many fields, like physics, engineering, life sciences, and data science.  Research areas include numerical linear algebra, optimization, numerical solution of partial differential equations, and applications of scientific computing.

SPIN is an interdisciplinary group of researchers who design and build innovative physical, touch-based user interactions to solve or advance real human issues.

This lab is a collection of researchers who want to more efficiently and effectively build better software systems.

The lab researches human movement and develops advanced computational models through computer graphics, scientific computing, computational mechanics, robotics, biomechanics, and the neural control of movement.

This group investigates visual intelligence - how human visual systems use light entering the eyes to create a variety of perceptual experiences. The knowledge gained can help with the design of effective visual displays.