Many conversational agents blend the functionalities of question-answering and chit-chat into a single system. This lays the foundation for a more interactive type of question-answering models which is the primary focus of the research project. Interaction between a user and the agent allows the user to ask an underdefined or ambiguous question, and, instead of the system returning its best response, the system is able to ask clarifying questions to help it hone in on an answer it can be more confident in.
The global challenge for COVID-19 is to create a vaccine. A key step in the development of a subunit vaccine is the identification of the parts of viral proteins (epitopes) that will trigger immune protection against the SARS-CoV-2 virus. The purpose of this work is two-fold: 1) On the computer, we will develop and test the functionality of a new algorithm for selecting optimal epitopes for vaccine construction and for creating a diagnostic assay; 2) In the lab, we will identify SARS-CoV-2 peptides directly from cells infected with the virus or challenged with viral proteins.
Over 200,000 new cancer cases are diagnosed in Canada each year. With imaging using an appropriate modality, many types of cancer that manifest as solid tumors can be detected, treated or managed effectively. Positron emission tomography (PET) combined with computed tomography (CT) is the primary imaging modality in a range of cancer types. Scientific studies have determined that measuring the size, shape, and texture of tumors from PET/CT images can help identify patients at high risk of early cancer recurrence, or for whom the standard treatment may fail.
How to build a medical education ecosystem and improve the learning outcome? Currently a medical education system based on mixed reality is missing and bad user interfaces can leave students confused and struggling instead of learning efficiently. The goal of this project is to leverage mixed reality technology, develop a medical education system, and make it easy to use.
We are proposing an investigation of techniques and technologies to support media-enhanced group performances that integrate different performative art forms (dance, theatre, clown, voice, choral) with responsive mixed reality technologies and public data sets. We will work with a group of young performers (13-17 years old) and a local Vancouver choreographer to deeply investigate, with embodied methods, the potential ways of creating a group performance that truly benefits from a layered digital reality.
Municipal governments and urban centres across Canada are being inundated with datadata that have potential to improve public service. Despite this, local governments do not have enough data expertise to extract insight from these overwhelming datasets. Simultaneously, high-quality personnel (HQP) in the domains of data science and urban analytics lack opportunities to work closely with local government to address this gap.
In order to design and operate more efficient urban transport infrastructure networks along the Cascadia Corridor, improved spatial and temporal data is required to understand travel activity patterns.
Our proposed research investigates how K-12 teachers learn and customize digital classroom tools and learning management systems and how they share this information with each other. In particular, we will be working with our partner Microsoft to investigate the use and customization of the recently developed OneNote Class Notebooks software that is increasingly being used by teachers for various content delivery and content management tasks.
Software teams and organizations use various tools -- either by design or appropriation -- to manage and share knowledge. Software engineering practitioners recognize that good documentation and effective knowledge sharing are critical to the success of a project and also to developer productivity. Yet, writing and maintaining documentation is often an afterthought for software engineering teams, and its very utility is subject to the software development methodology followed.
Due to rapid development of technology, such as the Internet of Things, collecting data is easier and cheaper than ever before. As a result, municipal governments and urban centres across Canada are being inundated with dataâdata that have potential to improve public service. Despite this, local governments do not have enough data expertise to extract insight from these overwhelming datasets, which are often unstructured and âdirtyâ (i.e., incomplete, inaccurate, and/or erroneous).