Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

29670 Completed Projects

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801
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663
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825
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8841
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9197
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95
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568
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1088
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Projects by Category

Medical geneticists’ discussion of psychiatric risks during diagnosis of 22q11.2 deletion syndrome

22q11.2 deletion syndrome (22qDS) affects 1/4,000 newborns. People with this condition can have various medical problems. Approximately 30% develop psychiatric illness (e.g bipolar disorder or schizophrenia). A recent study explored parents’ experience of receiving a diagnosis of 22qDS for their child. Families identified an unmet need for information from their healthcare providers about the psychiatric features of 22qDS, and indicated that risk for psychiatric illness was a major source of anxiety, compared to the other features of the syndrome. No studies have ever asked medical geneticists about how they approach telling families about the features of 22qDS. The purpose of our study is to find out if and when medical geneticists discuss with families different features of 22qDS, especially psychiatric risks. This project falls directly under several aspects of the mandate of BCMHAS. It explores the practices of physicians related to psychiatric disorders and helps the development of interventions.

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Faculty Supervisor:

Jan Friedman

Student:

Partner:

BC Mental Health and Addiction Services

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

The University of British Columbia

Program:

Accelerate

Understanding Systematic and Firm-Specific Components in Credit Risk

Credit risk—the potential that a borrower will fail to make required payments—is the oldest risk in our economy. It may arise in a number of circumstances, for example, a consumer failing to make the minimum payment due on a credit card or a company defaulting on its debt. Our main goal in this summer project is to quantify both systematic—vulnerability to events which affect the whole economy—and firm-specific components in credit risk, and the interaction between them. During a 12-week period, the student is expected to propose a model that allows for both systematic and firm-specific risks, develop an estimation methodology for such a model, along pricing methods for credit-sensitive derivatives. He is also expected to perform the econometric estimation of the model using credit default swaps and give economic interpretations based on the model.

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Faculty Supervisor:

Jean-François Bégin

Student:

Partner:

Indian Institute of Technology Kanpur

Discipline:

Mathematics

Sector:

Education

University:

Simon Fraser University

Program:

Globalink Research Award

Extending and Deploying the Social CheatSheet Plugin

This project will expose the intern to key design, implementation, and evaluation research activities in human-computer interaction (HCI). We have recently started exploring the concept of social curation of software help content by developing a novel web-based platform, Social CheatSheet, that overlays relevant community-curated instructions and multi-step tutorials atop any web application and offers an easy curation interface for adding and editing content. In the proposed research, we will be extending the features of the Social CheatSheet platform to design user analytics and more intelligent content recommendation. Our goal is to contribute stronger insights into how users actually contribute and consume content related to software learning and help. For example, we will be able to investigate how participation rates compare across different domain-specific communities (e.g., users of spreadsheets vs. 3D modelling vs. health applications).

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Faculty Supervisor:

Parmit Chilana

Student:

Partner:

Discipline:

Computer science

Sector:

Information and Communications Technology; Technology; Education

University:

Simon Fraser University

Program:

Globalink Research Award

Complete classification of Littlewood cyclotomic polynomials

The objective of this proposal is to study Littlewood cyclotomic polynomials of odd degree. In algebra, the cyclotomic polynomial is one such that has all its roots on the unit circle. Since all the coefficients of Littlewood polynomials are -1 or +1, its associates a finite binary sequence with -1 or +1 entries. Therefore, their study is closely related to the study of finite binary sequences which is a basic object in the theory of information and communication. There is an extensive research in information and communication theory on studying the merit factors of finite binary sequences. Binary sequences with low autocorrelation coefficients are the most easily distinguishable signals and they are of interest in radar, sonar, and communication systems. It was observed that all Littlewood cyclotomic polynomials have very simple factorization as a product of irreducible Littlewood cyclotomic polynomials. TO BE CONT’D

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Faculty Supervisor:

Stephen Choi

Student:

Partner:

Discipline:

Mathematics

Sector:

Education; Information and Communications Technology; Technology

University:

Simon Fraser University

Program:

Globalink Research Award

Metabolic networks and applications to M. tuberculosis

The project involves the modeling of the metabolism of TB. I developed an algorithmic pipeline called MetaMerge, which allowed me to reconcile differences in format, nomenclature, and annotation, between two models of TB metabolism. MONGOOSE, another doctoral project of mine, is a tool for analyzing metabolic network models in exact arithmetic, resulting in consistent, reproducible predictions, something that is currently impossible with any other tools since they rely on floating-point arithmetic.
The student’s role will consist of completing the integration of MetaMerge into the MONGOOSE pipeline, automating the reconciliation of two metabolic network models using machine learning and data mining techniques, and running the algorithm on the metabolic network models of other organisms. This will allow us to create a unified user interface for the two programs, making both programs more user-friendly and accessible, as well as to refine it to work on other organisms. TO BE CONT’D

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Faculty Supervisor:

Leonid Chindelevitch

Student:

Partner:

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Biotechnology; Pharmaceuticals

University:

Simon Fraser University

Program:

Globalink Research Award

Learning Generative Models of Images and Patterns

This Project is an continuation of our SIGGRAPH Asia 2017 paper on “Learning to Group Graphical Patterns”.
The paper introduced a novel deep learning approach for grouping discrete patterns common in graphical designs. The approach was based on a convolutional neural network architecture that learns a grouping measure defined over a pair of pattern elements. Motivated by perceptual grouping principles, the key feature of the network was the encoding of element shape, context, symmetries, and structural arrangements. These element properties are all jointly considered and appropriately weighted in the grouping measure. To better align the measure with the human perception of grouping, the network was trained on a large, human-annotated dataset of pattern groupings consisting of patterns at varying granularity levels, with rich element relations and varieties, tempered with noise and other data imperfections. TO BE CONT’D

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Faculty Supervisor:

Richard Hao Zhang

Student:

Partner:

Discipline:

Computer science

Sector:

Technology; Information and Communications Technology; Education

University:

Simon Fraser University

Program:

Globalink Research Award

Automating Cloud Data Center Operation – Year two

Manual performance, configuration and fault management of Cloud Data Centers is vulnerable to human intervention and therefore subject to human errors. One way to circumvent this problem is to use automation of the Cloud Data Center operations based on advanced technologies which may include Machine Intelligence.
As it is known in mobile industry applications/systems are being virtualized. Therefore some applications will require to run sometime in a central Data center and also closer to the user in order to meet certain characteristics. The last can be refered as an Edge cloud where services will require to be run closer to the users in order to meet certain characteristics. Ericsson develops cloud or Data Centers management products were these services and applications will reside. Therefore the automation of the service management of cloud or Data Center resources is a key.

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Faculty Supervisor:

Foutse Khomh

Student:

Partner:

Ericsson Canada Inc (Montreal, QC)

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

École Polytechnique de Montréal

Program:

Elevate

Automating Cloud Data Center Operation

Manual performance, configuration and fault management of Cloud Data Centers is vulnerable to human intervention and therefore subject to human errors. One way to circumvent this problem is to use automation of the Cloud Data Center operations based on advanced technologies which may include Machine Intelligence.
As it is known in mobile industry applications/systems are being virtualized. Therefore some applications will require to run sometime in a central Data center and also closer to the user in order to meet certain characteristics. The last can be refered as an Edge cloud where services will require to be run closer to the users in order to meet certain characteristics. Ericsson develops cloud or Data Centers management products were these services and applications will reside. Therefore the automation of the service management of cloud or Data Center resources is a key.

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Faculty Supervisor:

Foutse Khomh

Student:

Partner:

Ericsson Canada Inc (Montreal, QC)

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

École Polytechnique de Montréal

Program:

Elevate

Testing and Characterization of next-gen PiezoMUMPS sensors

This project involves the testing and characterization of new piezoelectric vibration sensors developed by the research group led by Prof. Bahreyni at the Intelligent Sensors Laboratory. These piezoelectric sensors have now been combined with another type of sensor – one with a capacitive transduction mechanism to improve the low-frequency sensitivity and noise performance. I shall first and foremost have to design an interface circuit for each sensor and then appropriately combine these signals to generate the final output signal. This shall be followed by noise analysis involving the modeling of different noise sources that shall contaminate the actual signal for e.g, the structural housing, the electronics structure, the contributions due to the interface electronics and other environmental noise sources. Following this, mechanical characterization like resonance frequency characterization needs to be done because, if the device is used near these frequencies then rapid mechanical damage shall ensue. TO BE CONT’D

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Faculty Supervisor:

Behraad Bahreyni

Student:

Partner:

Discipline:

Engineering

Sector:

Technology; Nanotechnology

University:

Simon Fraser University

Program:

Globalink Research Award

Computational fluid dynamics modelling of heat pipes for cooling applications

The proposed project aims to develop numerical models using computational fluid dynamics (CFD) to understand and predict the performance of heat pipes in the context of cooling applications. Heat pipes are a type of enhanced heat transfer device that uses a continuous cycle of boiling and condensing a fluid to transfer heat at a very high rate. The industry partner designs and manufactures heat pipes that are used extensively in the cooling of molds for making automotive parts. This project will allow them to better understand and predict the performance of their products and provide comprehensive simulation results to potential customers.

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Faculty Supervisor:

Christopher DeGroot

Student:

Partner:

Acrolab

Discipline:

Engineering

Sector:

Automotive; Advanced Manufacturing; Technology

University:

Western University

Program:

Accelerate

Enabling and Accelerating Fragment-based Drug Discovery – An Excellent Opportunity To Combine Innovation and Education

One of the most promising strategies for discovering our future medications is via fragment-based lead discovery (FBLD). FBLD involves the screening of libraries of small molecules to first identify weak binders to essential target proteins of diseases. These binders are then synthetically matured to larger, more potent inhibitors/leads via medicinal chemistry design efforts. However, there are major bottlenecks to achieving this critical step which have discouraged many pharmaceutical scientists from pursuing this approach. This is because experimental techniques are notoriously unreliable at properly characterizing weak binders at the required high concentrations. We propose to tackle this issue, and exploit educational opportunities, by redefining the fundamental techniques at each step of FBLD. Libraries will be designed, new NMR screening strategies implemented, analysis software will be developed, and an innovative NMR Kd–SAR cycle will be introduced. TO BE CONT’D

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Faculty Supervisor:

Steven LaPlante;Pierre Talbot;Steven LaPlante

Student:

Partner:

NMX Research and Solutions Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Université du Québec : Institut national de la recherche scientifique

Program:

Accelerate

A Vision-based system for intelligent monitoring of gait poses in dementia

Impairments of gait and balance often progress through the course of dementia, and are associated with increased risk of falls. Regular assessment of gait and balance could therefore be informative in tracking changes in functional status, and identifying individuals at a high risk of falling to allow for preventative measures. We have developed a technology, called AMBIENT, which enables the frequent, accurate, unobtrusive, and cost-effective measurement of gait and balance parameters. The objectives of this project is to improve the technology of the AMBIENT for pose estimation; to replace the depth sensor of AMBEINT with RGB camera; and to concurrently validate the accuracy of the estimated Gait parameters by the camera-based version of the AMBIENT. One important outcome of this study will be the advancement of technology to allow unobtrusive monitoring of changes in mobility in older adults with dementia.

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Faculty Supervisor:

Babak Taati

Student:

Partner:

Riverview Health Centre Foundation

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology

University:

University of Toronto

Program:

Accelerate

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