The high throughput sequencing (HTS) platforms generate unprecedented amounts of data that introduce challenges in computational infrastructure. The requirement of large investments for this purpose almost signaled the end of the Sequence Read Archive hosted at the NCBI, which holds most of the sequence data generated worldwide. Currently, most HTS data is compressed through general […]

The HIV epidemic and risk behaviour in the DTES will be modelled as stochastic processes on a network. Nodes in the network will represent individuals and links social interactions between them. Stochastic contact processes on the network links will be used to model both transmission of HIV and social influence. The network will capture transmission […]

Dunes are common bed features in large sand-bedded rivers and are significant sources of in-channel roughness. Reliably estimating roughness is crucial for the prediction of flood flows, but roughness is crudely represented in hydraulic models widely used by environmental consultants and engineers. Roughness is treated as a calibration knob in these models, adjusted to force […]

Dunes are common bed features in large sand-bedded rivers and are significant sources of in-channel roughness. Reliably estimating roughness is crucial for the prediction of flood flows, but roughness is crudely represented in hydraulic models widely used by environmental consultants and engineers. Roughness is treated as a calibration knob in these models, adjusted to force […]

The Thingery Sharing Inc. is the logistics provider and parent organization of five co-operatively owned community-level goods lending libraries known as Thingeries located throughout the Lower Mainland of BC. As a data-intensive enterprise, Thingery Sharing Inc. has the potential to track the social and ecological impacts of community level goods sharing. However, the existing literature […]

Deep learning has shown great success in a variety of tasks with large amounts of labeled data in image classification. These achievements have relied on the fact that optimization of these deep, high-capacity models requires many iterative updates across many labeled examples. This type of optimization breaks down in the small data regime where we […]

We will create new software technology for generating intelligent-looking movement behavior of virtual characters in video games. When characters move around in game worlds, they typically plan their path around fixed obstacles and use some simple rules to avoid dynamic obstacles, such as other characters. Recently a family of methods based on the concept of […]

Architectural design data have mostly been limited to visual representations, specifications and contractual documents. Today, design firms generate vastly more and diverse data, but lack adequate access to tools to gain insight from such data. Yet the field of “visual analytics” provides concepts and systems exactly for working with such data. The proposed research aims […]

This research project aims to explore how civil society organizations in Metro Vancouver might devise Community Land Trusts that allow their property interests to intersect with their social mission. Metro Vancouver Alliance, a broad-based community organizing alliance of faith, labour, community, and education sectors, previously conducted listening campaigns identifying reconciliation and affordable housing as common […]

Antibody-based medicines are playing an ever increasing role in the arsenal of treatments of many diseases, from cancer to obesity to Alzheimer’s. Cell surface proteins, called membrane receptors, are considered key therapeutic targets in many of these pathologies, yet targeting them with antibodies has proven to be a challenge. Amgen British Columbia is dedicated to […]

Machine learning approaches are transforming fields such as finance, healthcare, electronic commerce, social networks, and natural disaster forecasting. We propose collaborative research that develops novel methods and applications of machine learning techniques for event prediction, modeling relations between entities, and inference techniques that can impact these domains. In the context of event prediction, we will […]

The Embedding Project is a public-benefit research project that relies on strong social science research methods to bring together thoughtful sustainability intrapreneurs from across industries and around the world, and harnesses their collective knowledge to develop rigorous and practical guidance that benefits everyone. This internship will offer an MBA student the opportunity to gain experience […]