Innovative Projects Realized

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

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Investigation of the protein-protein interaction network of an anti-oxidant protein TPxGl in the human malaria parasite P. falciparum

Malaria is a mosquito-borne infectious disease affecting humans with more than 214 million cases worldwide. The most dangerous (and most common) form of malaria is caused by Plasmodium falciparum. Understanding the fundamental biological mechanisms of this parasite is crucial for developing therapies to combat the humanitarian crisis caused by the spread of this disease. In order to unravel the mechanisms of how proteins are transported within the cellular environment of this parasite we must first understand how various proteins interact with one another (a network of interactions). The Patankar Lab has recently identified a particular anti-oxidant protein, TPxGl, as exhibiting unique patterns of subcellular localization which warrant further investigation. This project will apply unique computational bioinformatics tools developed by the Green Lab to investigate the protein interaction network of this, and other, proteins. Towards this goal, the complete network of interactions for P. falciparum will be determined, as well as interactions between parasitic and human proteins. Through these efforts, we aim to elucidate the protein transport pathways within P. falciparum which may ultimately lead to novel discoveries in relation to malaria.

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Faculty Supervisor:

James Green

Student:

Kevin Dick

Partner:

Discipline:

Engineering - computer / electrical

Sector:

University:

Carleton University

Program:

Globalink Research Award

Design of a gene network implementing an associative memory circuit

The main goal of this research project is to implement an associative memory module in a gene network. The idea is to use the theoretical work already done at the Signals and Systems Laboratory (L2S) and to apply it in the area of genetics. The proposed approach is innovative, as it combines techniques from two disciplines: engineering and life sciences. The work done at L2S deals with a type of systems that includes networks, and in this particular case it would be applied to a network made up of genes. In case this approach is successful it would be possible to use synthetic biology in order to build a genetic network that could be programmed to provide for flexible responses of an organism in a variety of environmental conditions.

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Faculty Supervisor:

Marc Roussel

Student:

Dina Irofti

Partner:

Discipline:

Biochemistry / Molecular biology

Sector:

University:

University of Lethbridge

Program:

Globalink Research Award

Robust statistical damage assessment of infrastructures

Structural health monitoring is regarded as the main tool in assessing the functionality of existing structures. The importance of these techniques emerges by considering that failure of an infrastructure results in catastrophic loss. With such techniques, damages in a structure can be detected, before reaching dangerous levels. Those are purely based on measurement data and no structural models are required. In recent years, a statistical framework for damage detection has been developed with significant success on real structures. In order to infer the location of a damage after its detection, a structural model is required. To achieve an efficient damage localization method, interaction between signal processing specialists at Inria and civil engineering experts at UBC is required. Models of investigated structures will be coupled with the previously developed statistical approach in this research. The objective is to develop the necessary tools to bring damage localization into practice, aiming at a robust method for real applications such as bridges and tall buildings.

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Faculty Supervisor:

Carlos Ventura

Student:

Saeid Allahdadian

Partner:

Discipline:

Engineering - civil

Sector:

University:

University of British Columbia

Program:

Globalink Research Award

Chemical Analysis of Complex Samples with High Resolution Capillary Electrophoresis Mass Spectrometry

Cheng Qian (PhD candidate) supported by this Mitacs Globalink Program will go to Nanjing (P. R. China) and work in a cooperative project under the supervision from Prof. Dr. David Chen (University of British Columbia, Canada) and Prof. Xiaohua Huang (Nanjing Normal University, P. R. China) to install a novel electro-ionization interface for high resolution Capillary Electrophoresis Mass Spectrometry (CE-MS), and analyze complex samples to verify the performance of this state of the art hyphenated instrumentation. With high resolution Orbitrap Mass Spectrometer (Orbitrap MS), the full potential of the novel CE-MS interface could be exerted and new records for the performance of CE-MS could be set up, based on the success of this international project. Complex sample analysis will directly benefit from the combination of the great CE separation efficiency and accurate Orbitrap MS detection. More collaboration can be
developed by this project, between the Canadian academia of separation science and the Chinese counterparts.

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Faculty Supervisor:

David Chen

Student:

Cheng Qian

Partner:

Discipline:

Chemistry

Sector:

University:

University of British Columbia

Program:

Globalink Research Award

A Generalized Model Predictive Path Planning System for Autonomous Vehicles on Structured Roads

Autonomous vehicles process the data received from their sensors to recognize the road and the obstacles in their perception module, and determine the desired route via the decision making module. Then, in the path planning module, they plan a path so that the vehicle follows the route while it observes the rules, avoids obstacles, and keeps the vehicle stable. Two common path planning methods, potential fields and model predictive controllers, have been combined in this project to develop a path planning module that is general, optimal, and predictive. The developed module has been simulated and showed an appropriate performance. In this project, the module is implemented on the autonomous vehicle of the host lab to validate the simulations. The path planning module is modified to be compatible with other modules used in the autonomous vehicle (the perception and decision making modules). It is also tuned for the vehicle, so that the experimental planned paths are as good as the simulation results.

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Faculty Supervisor:

Amir Khajepour

Student:

Yadollah Rasekhipour

Partner:

Discipline:

Engineering - mechanical

Sector:

University:

University of Waterloo

Program:

Globalink Research Award

Comparative analysis of merger control mechanisms in Canadian and Mexican competition law

This research project conducts a comparative analysis of the provisions of Canadian and Mexican competition laws that deal with the control of mergers and acquisitions. Usually, merger control mechanisms require that a proposed transaction whose value exceeds a certain threshold be notified to the competition authorities of the country where the transaction is to take place. Cross-border mergers and acquisitions between Canadian and Mexican firms may have to be notified to both the Canadian Competition Bureau and the Mexican Federal Economic Competition Commission. A comparative overview of the requirements and assessment framework imposed by the competition legislation of both countries in terms of mergers is valuable for the business community, lawyers and competition authorities. Business decisionmakers will be able to better strategize about cross-border expansion, lawyers will be more
adept at advising clients who intend to engage in merger and acquisitions activities abroad and competition authorities will be better equipped to coordinate their assessment of mergers notified in both countries.

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Faculty Supervisor:

Thomas Ross

Student:

Ivona-Elena Zegrean

Partner:

Discipline:

Business

Sector:

University:

University of British Columbia

Program:

Globalink Research Award

Brain Decoding Models for neurodegenerative disease aided diagnosis and classification

Globally, brain-related diseases such as Alzheimer’s disease and Epilepsy have a huge toll on patients, loved ones, and healthcare systems. The research project aims to establish a model to better diagnose neurodegenerative diseases. There is a wealth of clinical test data, symptoms, and observations associated with the long list of neurodegenerative diseases. In order to better understand underlying causes of these diseases, neuroinformaticians are developing software tools to link the volumes of data to underlying causes of each brain-related illness. The research aims to apply computational tools and approaches to understand the brain and integrate symptom information to help interpret and treat neurodegenerative diseases. The project aims to develop a generic brain decoding model which would be able to aid diagnosis, understanding, and patient treatment. The project is a significant undertaking given the structural, functional, and environmental variables across patients thus making diagnosis particularly challenging.

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Faculty Supervisor:

Rustom Bhiladvala

Student:

Timmons Wong

Partner:

Discipline:

Engineering - mechanical

Sector:

University:

University of Victoria

Program:

Globalink Research Award

Characterization of chemosensory proteins in exosomes

Cells in our body secrete round structures lined by cell membrane under normal as well as stressful conditions. These “structures” or “micro vesicles” are termed as exosomes. They contain information from parent cells that can be transferred to other cells, thereby acting as cell-to-cell communication units. In this study I aim to identify the presence of bitter taste responsive proteins in exosomes. Bitter taste responsive proteins are also known as chemosensory proteins. These proteins have demonstrated significant role in pathophysiological conditions. I will determine the presence of bitter taste responsive proteins in these exosomes by novel cellular and molecular techniques. The expected outcome has the potential to be used as a diagnostic assessment tool for certain oral diseases.

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Faculty Supervisor:

Prashen Chelikani

Student:

Manoj Medapati

Partner:

Discipline:

Biology

Sector:

University:

University of Manitoba

Program:

Globalink Research Award

Testing the response of sand samples to cyclic loading under different boundary conditions

Local site conditions can strongly influence the amplitude and duration of ground motion during an earthquake. Therefore, it is necessary to analyze and understand the mechanical properties of soils. By testing the same samples with similar conditions in different devices we can obtain more accurate results for dynamic loading tests and imitate the stress history that a soil might experience. The preparatory work will include a series of tests that will be held at Ben Gurion University under the supervision of Dr. Ronnie Kamai, followed by a test-series on a different testing device, held at University of Toronto under the supervision of Dr. Mohsen Ghafghazi. Such comparison will allow us to develop a more comprehensive understanding and quantification of the soil’s response to dynamic excitation. The mechanical properties of the soil can then be used to describe the behavior the soil during earthquake loading. With these parameters it will be possible to create an analysis that is more proper and accurate to the local conditions in Israel, contrary to what we think exists in the local building code today.

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Faculty Supervisor:

Mohsen Ghafghazi

Student:

Almog Baram

Partner:

Discipline:

Engineering - civil

Sector:

University:

University of Toronto

Program:

Globalink Research Award

Manganese Salen Systems for C-H Functionalization

Selective incorporation of valuable building blocks into feedstock chemicals is a very important, albeit often times difficult challenge. We plan to develop catalysts; materials to efficiently convert feedstock chemicals into ones with valuable functionality. The catalysts developed by the
current project will incorporate two traditional reactive sites as a means to enhance activity and selectivity of our selected transformations. Through various techniques we plan to interrogate the properties of our developed systems in order to inform decisions about second generation
materials with enhanced activity over their predecessors. This project will result in a selection of new materials for the efficient conversion of feedstock chemicals into value added products.

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Faculty Supervisor:

Tim Storr

Student:

Ryan Clarke

Partner:

Discipline:

Chemistry

Sector:

University:

Simon Fraser University

Program:

Globalink Research Award

Cross population study of white matter connectivity using dictionary learning and sparse coding

Understanding the structure and connections in the brain is an outstanding research problem. Many diseases impact the structure and hence connections between them, analyzing which may help in detection and diagnosis of these diseases. In this project, we try to learn an atlas of major connecting fibers (tube like connections) for a group of people, using dictionary learning based framework. This atlas is then used to observe the similarities and differences in fibers across the group, and to segment fibers from new person. We will use twin dataset of the Human Connectome Project to study heritability of white matter clusters. The method will also be used to understand the differences in structural connectivity between healthy subjects, mild cognitive impairment (MCI) subjects, and Alzheimer’s disease (AD) subjects.

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Faculty Supervisor:

Christian Desrosiers

Student:

Kuldeep Kumar

Partner:

Discipline:

Engineering - biomedical

Sector:

University:

École de technologie supérieure

Program:

Globalink Research Award

Integrated underground mine planning using mathematical programing

The operation of an underground mine site requires the execution of multiple tasks and involve many human and material resources. The execution of these tasks is then limited by many constraints including the order in which certain task must be done, the limits on availability of resources, congestions in the distribution of resources and many others. Because of this, scheduling the activities in an underground mine is a very complex and demanding task. In most mine, an experienced mine planner must work full time in order to achieve a good and feasible planning. The objective of this project is to create a tool relying on mathematical programming to plan all activities in an underground mine in the best way possible within seconds.

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Faculty Supervisor:

Michel Gamache

Student:

Louis-Pierre Campeau

Partner:

Discipline:

Engineering

Sector:

University:

Polytechnique Montréal

Program:

Globalink Research Award

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