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

A Novel Combination Therapy to Target Primitive Acute Myeloid Leukemia Cells – Year two

Modern molecular targeted therapies have shown promise in treating some blood cancers, but a cure remains elusive for most acute leukemia patients. This is largely due to the survival of some leukemic cells that possess unique properties and can cause treatment failure or relapse, warranting identification of new, distinct targets for improved therapies. In collaboration with Signalchem Lifescience Corporation (SLC), we aim to develop and test a new drug combination strategy to target acute myeloid leukemia (AML) patient cells that are resistant to current therapies. This pre-clinical study will evaluate the efficacy of novel inhibitors (developed by SLC), alone or in combination with available chemotherapeutics, to target primitive AML cells and their survival pathways in vitro and in vivo. We expect that this new combination will be more effective in eliminating critical leukemic patient cells compared to traditional single drugs, and provide directly proof-of-concept for a subsequent clinical trial.

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Faculty Supervisor:

Xiaoyan Jiang

Student:

Katharina Rothe

Partner:

SignalChem Lifesciences Corporation

Discipline:

Genetics

Sector:

Medical devices

University:

Program:

Elevate

Use of pulp mill residues as construction and geotechnical materials

Heat and electricity generation from biomass combustion in power boilers and co-generation plants produces large quantities of ash residues in British Columbia (BC) each year. In 2013, approximately two thirds of the produced ash were landfilled in Canada and only the remaining one third beneficially utilized. On the other hand, high-quality construction materials are rare in many parts of the world, and most often engineers are forced to seek alternatives to reach the stipulated requirements. In addition, road maintenance operations in BC are often costly, but by formulating a suitable additive to the problematic sites can reduce the cost and allay the need of further maintenance. There are innumerable problems associated with engineering constructions on the problematic soil deposits in BC; for example, soft, collapsible and organic soils. TO BE CONT’D

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Faculty Supervisor:

Sumi Siddiqua

Student:

Chinchu Cherian

Partner:

FPInnovations

Discipline:

Engineering - other

Sector:

Alternative energy

University:

Program:

Elevate

Effective knowledge translation of evidence-based best practice for healthy lifestyle behaviours – Year two

The research supports the effective knowledge translation of evidence-based best practice information related to healthy lifestyle behaviours. Over a two-year period, the post-doctoral fellow will create a series of knowledge translation tools that can be used in the effective primary and secondary prevention of chronic disease through lifestyle behaviour modification. Our proposed initiative will capitalize on the best of the existing models of health promotion. We believe that the proposed development of knowledge translation tools has the potential to affect positively the health and wellbeing of thousands of Canadians. It is anticipated that through this initiative we will be able to improve the dissemination of information regarding the most effective primary and secondary preventative strategies for prominent medical conditions and obesity a key priority of the Health and Fitness Society of BC.

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Faculty Supervisor:

Shannon Bredin

Student:

Erin Shellington

Partner:

Health and Fitness Society of British Columbia

Discipline:

Kinesiology

Sector:

Medical devices

University:

Program:

Elevate

Developing solutions for safer harvesting techniques on steep terrain

The forest industry in British Columbia (BC) is facing increasingly difficult challenges regarding fibre supply. New winch-assist technology that enables fully mechanized ground-based forest harvesting on steep terrain has been increasingly used in BC since 2016. The new systems have improved safety and provide access to fibre that was previously uneconomic. New low-consumption small-size cable yarders have also received increasing interest in non-trafficable terrain. Both the winch-assist and the cable yarding systems have similar issues related to the use of tensioned wire ropes and natural anchors (stumps or trees).Rope and anchor failures have serious safety risks for the operators and the forest industry as a whole. To date, only a few studies focused on cable tensile force analysis and suitability of trees or stumps as anchors. This research aims to study the behaviour of cable-supported systems and anchors under varying conditions and improve safe practices of the newly introduced technology in BC.

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Faculty Supervisor:

Dominik Roeser

Student:

Omar Mologni

Partner:

FPInnovations

Discipline:

Forestry

Sector:

Forestry

University:

Program:

Elevate

High-Performance Control of an Ultra-Compact Industrial Robot Arm

In recent years, automation has become more accessible to small- and medium-sized businesses, leading to an increase in popularity of ultra-compact and easy-to-integrate industrial robot arms like Mecademic’s Meca500. However, because of their size constraints, it is harder for these robots to accurately follow a programmed path. This research project aims to improve the path-tracking performance of Mecademic’s Meca500 robot using more sophisticated simulation and control techniques than the ones employed in typical industrial robots. Improving the path-accuracy of the Meca500 will strengthen Mecademic’s competitive advantage in the fast-paced industrial automation market.

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Faculty Supervisor:

James Forbes

Student:

Steven Dahdah

Partner:

Mecademic

Discipline:

Engineering - mechanical

Sector:

Advanced manufacturing

University:

Program:

Accelerate

Specific Evaluation of Lesion Categories

Multiple Sclerosis (MS) is a debilitating disease that primarily affects young individuals. Disease Modifying Therapies (DMT) developed in the past two decades have greatly improved the quality of life for people living with MS. Assessment of brain lesions using Magnetic Resonance Imaging (MRI) has been a standard method to evaluate the efficacy of DMT in clinical trials and practice. However, standard techniques do not differentiate between the different stages of lesion evolution. Using advanced MRI and machine learning techniques, this project aims to develop an automated technique for Specific Evaluation of LEsion CaTegories (SELECT), with the goal of improving lesion assessment in clinical trials and practice. Building on his previous experience evaluating MS deep gray matter using machine learning, the intern will acquire valuable expertise in developing and applying machine learning techniques to MS lesions. The partner organization will benefit from the intern’s previous experience with MS machine learning techniques.

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Faculty Supervisor:

David Rudko

Student:

Ahmed Elkady

Partner:

NeuroRx Research Inc.

Discipline:

Medicine

Sector:

Medical devices

University:

Program:

Accelerate

Constrained Kalman filtering for train position estimation

Just like for the automotive industry, there is growing interest in the development of fully autonomous trains. One of the key steps in the creation of a fully autonomous solution is optaining an accurate estimate of the train position and velocity. Accurate estimates are critical component of the train safety during operation and better estimates allow more trains to operate safely on the same track. The current project deals with trains operating in areas without GPS coverage, such as subways, and so accurate position measurements cannot be obtained as frequently. This means that the estimation algorithm used to calculate the position in between measurements must be as precise as possible to reduce any possible drift. The proposed method to improve the estimate is to ensure that the train states (position, velocity, train orientation) are explicitly constrained by the track the train is traveling on. TO BE CONT’D

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Faculty Supervisor:

James Forbes

Student:

Marc-Antoine Lavoie

Partner:

Thales Canada Inc.

Discipline:

Engineering - mechanical

Sector:

Automotive and transportation

University:

Program:

Accelerate

Development of a multi-function sensor for HV apparatus

The proposed research aims to develop a novel fiber optic based technology for the monitoring and detection of defaults in power transformers, which could lead to an in-service failure and power outages. The partner company has developed a sensor that is sensitive to vibration and moisture. Also, small electrical sparks, known as partial discharges, in high-voltage equipment generate acoustic waves that can also be detected in a similar way than vibrations. The main objective of this project is thus to assist the industrial partner in the development of his sensors, to validate their efficiency in laboratory as well as in the field on real in-service power transformers, and finally to package them for their commercialization.

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Faculty Supervisor:

Eric David

Student:

Meng Guo

Partner:

QPS Photronics Inc.

Discipline:

Engineering - mechanical

Sector:

Energy

University:

Program:

Accelerate

Cloud based Machine learning algorithms on archived satellite/raster Imagery datasets

The proposed research work will be a breakthrough in the emerging data engineering field, especially in satellite data management, Machine learning algorithms, quality and quantitative analytics. The machine learning platform quickly scans vast archives of satellite images and delivers usable insights to decision makers. After processing of raster images, the data will be readily available to farmers sooner than any government or commercial desktop software or email delivery system, therefore assisting in making critical decisions early on, and reducing chances of crop failure
This project will make Beriqo a leader in Canadian Agriculture tech industry. The precision agriculture is fast growing space with expected market size of 6.43 billion [15] by 2022. Also, completion of this project results more job creation, putting Canada on the top of innovative chart, help Canadian farm operators save millions in farm operating cost, and decrease emission of nitrogen oxide (a green house gas) .

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Faculty Supervisor:

Mirza Beg

Student:

Gurman Thind

Partner:

Beriqo

Discipline:

Engineering - other

Sector:

Alternative energy

University:

Program:

Accelerate

Advanced Battery Modelling in Electric Bus Platforms to Enable Next-Gen Low-Carbon Public Transit

With the ever-increasing growth of the consumer Electric Vehicle (EV) market and environmental awareness of federal and provincial governments, electrification of public transit systems has come under the spotlight in recent years. Currently, there is limited practical knowledge on how to efficiently deploy EV buses across different Canadian regions, which results in a wide gap between advanced EV technology and Canadian environmental parameters.
EV batteries are negatively affected by cold temperatures, bad road conditions, and aggressive driving behaviours. This results in a shorter life-span of the battery pack and it’s quicker degradation. To reduce these negative effects, public transit companies need to fully understand how batteries behave under different operating and environmental conditions, and these conditions are not the same across Canada. Furthermore, EV manufacturing companies also need to adapt their designs to these conditions for successful marketing.

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Faculty Supervisor:

Olivier Trescases

Student:

Zhe Gong

Partner:

WSP

Discipline:

Engineering - computer / electrical

Sector:

Automotive and transportation

University:

Program:

Accelerate

Biomass Upgrading with Natural Gas for Fuel and Renewable Chemicals

Biomass valorization with natural gas to produce high-quality fuel and sustainable chemicals (i.e. aromatics) will be investigated under mild conditions (400ºC, <5MPa). The technical feasibility will be further verified on a laboratory scale reactor. The catalysts will be optimized, and the related mechanisms will be better explored using isotopic labeling molecular and versatile advanced characterization techniques (i.e. DRIFTS, XPS, XAS, HRTEM). This process will be finally scaled up and tested on a pilot-scale testing facility at partner organization, which will gain more useful information for further industrial applications. Once this can be done economically, it will significantly reduce the capital and operational costs associated with H2, which makes the produced bio-oil more cost competitive with conventional oil. It also will improve the competitiveness of partner organization in the market and bring more social and economic benefits.

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Faculty Supervisor:

Hua Song

Student:

Aiguo Wang

Partner:

Discipline:

Engineering - chemical / biological

Sector:

Oil and gas

University:

Program:

Accelerate

Orebody Heterogeneity Assessment for Sensor Based Sorting

Teck Resources Limited is searching for a method to characterize and quantify the heterogeneity of ore based on numerous parameters. Naturally, when characterizing an ore body’s heterogeneity, the variability in the deposit can contribute towards the sortability of the deposit.
The main objective of this research is to investigate a method to quantify the sortability and ore heterogeneity in a systematic manner with clear ranking criteria. Throughout the research, 5 – 6 operations’ resource models will be reviewed and the ore heterogeneity will be assessed for the purposes of ranking them for ore sorting

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Faculty Supervisor:

Bern Klein

Student:

Nawoong Yoon

Partner:

Teck Resources Ltd

Discipline:

Engineering - other

Sector:

Mining and quarrying

University:

Program:

Accelerate

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