Our research goals, which are a mix of theoretical and practical problems, are motivated by the practical near-term problem of delegating tasks to an untrusted remote quantum computer in a secure way. Toward this, we consider the notions of indistinguishability obfuscation for quantum circuits and quantum fully homomorphic encryption schemes. The former refers to algorithms that take a given quantum circuit and make it less intelligible, such that the new circuit still gives the same outputs as the original one.
Disengagement is not a “steady state” rather it is better conceptualized on a continuum with engagement in some areas as well as disengagement in others (Christenson and Thurlow 2004). The proposed research will explore how issues of access and equity factor into student engagement within the university setting. In particular, this research explicitly examines “push” and “pull” factors for engagement by drawing on several data sources to assess factors affecting retention rates and the experiences of students who leave post-secondary education.
Workplace discrimination is common for Indigenous people (1,2). Unacceptable behaviours may take place at work, such as threats, intimidation, or violence (2). The workplace is a location where behaviour labeled as ‘bullying’ occurs (1,3). When examining Indigenous workers, the impacts of behaviour defined as bullying (and the mere act of defining the behaviour as bullying rather than racism, violence or harassment) may be exacerbated given the unique history of Indigenous people.
The Structural Genomics Consortium (SGC) is a not-for-profit public-private partnership research organization that aims to accelerate the discovery of new medicines through open science. This Mitacs cluster will bring together SGC’s industry and academic collaborators to work together towards new and affordable medicines for challenging diseases. Sixty-three post-doctoral fellows will spend 2-3 years developing open source tools and knowledge for previously understudied proteins, thereby unlocking new areas of biology and identifying new opportunities for drug discovery.
The goal of this project is to support Indigenous economic development corporations in the establishment of technology-focused companies designed to introduce, test and market new and emerging technologies of potential application for Indigenous communities. At present, northern, remote and Indigenous communities are being left behind in the technological revolution. Companies do not reach out to First Nations, Inuit and Metis communities. The” innovation gap” is growing larger.
This Mitacs proposal tackles several outstanding issues that must be addressed to complete development of a widely applicable pipeline for quantitative analysis of 3D facial shape in medicine. Here, we focus on specific applications of imaging pipelines in genetic syndrome diagnosis and facial surgery visualization and planning.
Costs are continually declining for internet connected devices, known as the internet-of-things (IoT), offering solutions across various consumer, commercial and industrial applications. Concurrently, machine learning (ML) models are continually expanding their deployment platforms, from massive central servers down to microcomputers. Innovative IoT devices will run the ML models without support from central data centers or other computers.
The mental well-being of youth is critical at a personal, familial, and societal level. The rise of mental illness, addictions, and suicide in youth, especially among those living in low- and middle-income countries, is of significant concern. Our global health team at the University of Toronto and Centre for Addiction and Mental Health (CAMH) has focused on providing mental health and positive development curriculums for transitional youth in collaboration with international and local partners.
Nxtgen Care provides monitoring services for elderly care homes across North America. Their product provides detailed analysis in visual formats to understand the resident’s requirements and directing care in that direction. To meet this goal, voluminous data is collected from the various activities of the residents. Through this project, this data is processed and directed in a way to optimize resources for effective scheduling in a timely manner. This is done with the help of advanced Machine Learning (ML) and Artificial Intelligence (AI) techniques.
Contamination of soils with toxic hydrocarbons (e.g. benzene) is a widespread environmental concern in Canada. Remediation of contaminated soils is often destructive to land resources. In-situ remediation built on soil infiltration with biostimulatory solutions represents an effective approach that bypasses this drawback, however field studies suggest it is not effective under all conditions. The reason for this, however, is unclear.