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

Toward Operation Improvement of HPGR and Ball Mill Circuits Through the Dynamic Optimization and Mill Speed Control in Response to Variation in Measurable Process Variables

Crushing and grinding processes are the largest consumers of energy at a mining operation. The High-Pressure Grinding Roll (HPGR) has gained popularity because it is much more energy efficient than conventional processes. The HPGR product is then ground in ball mills to prepare ore for mineral separation. These processes are controlled to optimize their performance by minimizing energy usage while maximizing productivity. The rotational speed of the rollers and of the ball mills can be controlled in response to changes in ore properties. The research will investigate and advance strategies for controlling the speed to optimize their performance.

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Faculty Supervisor:

Bern Klein;Sanja Miskovic

Student:

Max Hesse;Bill Tubbs

Partner:

Copper Mountain Mining Corporation

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of British Columbia

Program:

Accelerate

Strengthening Process Efficiencies in a Changing Industry

This study aims to improve process efficiencies while supporting the development of products that best respond to market trends in the context of a post COVID-19 globalized market. From a process engineering perspective, the proposed activities seek to improve mill competitiveness through waste management to both reduce load on water treatment systems and obtain value added products from wastewaters, and investigate recovery of lignin, hemicellulose, and cellulose recovery from mill residues for further product development in biomaterials. The study offers possibilities for more environmentally sustainable processing, potential reduction of current expenses, and potential creation of new revenue streams to increase competitiveness for CBPPL while strengthening university-industry collaborations between Memorial University, and CBPPL. This collaboration further develops subject matter expertise in Corner Brook and Newfoundland and offers students valuable experience with applied research and industry trends.

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Faculty Supervisor:

William Newell;Kelly Hawboldt

Student:

David Hopkins;Rene Alberto Silva;Mery Perez;Lucas Knill

Partner:

Corner Brook Pulp and Paper Limited

Discipline:

Engineering

Sector:

University:

Memorial University of Newfoundland

Program:

Accelerate

Applying machine learning techniques for demand forecasting in retail

An important component to every growing retail business is demand forecasting which can affect the strategic plans of a business. The impact extends across the business’ function including budgeting, financial planning, price optimization, sales and marketing plans, capacity planning, staff management, risk assessment and mitigation plans.
In this project, we want to apply machine learning technologies to improve the accuracy and granularity of retail demand forecast. ML Models will be built from historical data and enriched with additional external factors using state-of-the-art machine learning techniques. This would result in shortening the company’s inventory age and improving the customer fulfillment rate.

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Faculty Supervisor:

Sudhakar Ganti

Student:

Naghmeh Dezhabad

Partner:

Flashana Technologies Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Victoria

Program:

Accelerate

Investigations into the mechanism of action and potential in idiopathic pulmonary fibrosis of the novel ruthenium based therapeutic BOLD-100

Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal disease lung disease with unknown cause. There are limited treatment options for IPF and investigations into new treatment options is needed. BOLD-100 is a clinical-stage small molecule that is currently being investigated as a treatment option in oncology and viral infections. The pathway that BOLD-100 impacts, the unfolded protein response, is important in IPF and therefore this project’s objective is to use preclinical models to test whether BOLD-100 can affect development of IPF. The interns will gain experience using a range of different models to test an industry backed compound and will interaction with industry veterans at the partner organization, Bold Therapeutics. Bold Therapeutics will benefit by utilizing the expertise of the Ask laboratory to potentially expand the potential of BOLD-100 into IPF.

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Faculty Supervisor:

Kjetil Ask

Student:

Soumeya Abed;Olivia Mekhael;Parichehr Yazdanshenas;Vaishnavi Kumaran

Partner:

Bold Therapeutics

Discipline:

Biochemistry / Molecular biology

Sector:

Professional, scientific and technical services

University:

McMaster University

Program:

Accelerate

Developing fluorescent viability stain compounds and uses for anti-cancer drug screening

Breast cancer is the fourth most frequent cancer in Canada, and affects one in X women during their lifetimes. A variety of different treatments have been tried, some of which damage cellular DNA of the quickly growing cancer cells. High-level DNA damage causes cells to die, and can shrink the tumour and arrest cancer growth. The Sabatinos lab studies how cells deal with DNA damage caused by drugs, and how this impacts their ability to grow and divide. A long-time drug used in cancer chemotherapy is a drug called cis-platinum. Our collaborator, Dr. R. Gossage, has generated new compounds that contain platinum, or, other metals such as copper, nickel or palladium. These compounds are predicted to also work for breast cancers, but must be tested in cell cultures. To do this we use a variety of dyes and stains that monitor cell proliferation, cell division, DNA replication, DNA damage and cell death. These tests give data that will inform which of the new metal-containing compounds, or compound families, is most promising at specifically targeting breast cancer cells while persevering non-cancer cells in the body. Koivisto Materials Consulting Inc is our industrial partner.

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Faculty Supervisor:

Sarah Sabatinos;Robert (Rob) Gossage

Student:

Gillian Okura

Partner:

Koivisto Materials Consulting Inc

Discipline:

Biology

Sector:

Professional, scientific and technical services

University:

Ryerson University

Program:

Accelerate

High performance robotic drilling and inspection systems for aerospace composite manufacturing

Manufacturing of aerospace composite structures requires drilling of thousands of holes for rivet and bolt attachments. Traditionally, required holes have been drilled and inspected manually, which is extremely time-consuming, inconsistent due to human error, and potentially hazardous to workers. The proposed research will develop a high performance robotic drilling and inspection technology for aerospace composite manufacturing. In order to improve hole quality in robotic drilling, a novel two-axis actuator will be developed to actively measure and suppress robot vibrations during operation. Advanced optimization techniques will be developed to maximize productivity and quality in robotic drilling. Finally, an intelligent inspection technology will be developed to autonomously inspect the accuracy and quality of drilled holes without a need for human intervention. The proposed robotic technology will help Canadian aerospace manufactures improve the productivity and quality of their drilling operations, thus giving them a leading edge over the global competition.

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Faculty Supervisor:

Matt Khoshdarregi;Olanrewaju Ojo

Student:

Michael Newman;Jasper Arthur;Seyedali Maghami

Partner:

TetraGen Robotics Inc

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

University of Manitoba

Program:

Applying real-time virtual reality and artificial intelligence for risk-based safety assessment of autonomous operations in a shared airspace

The objective of the research project that is the subject of this proposal is to simulate autonomous flight for the purpose of risk-based safety assessment using machine learning applications. Simulation methodologies are developed and implemented for the purpose of extracting data from real-time, publicly-accessible sources to create a virtual environment that represents actual airspaces including air traffic, weather, terrain obstacles and navigation aids. A simulated model of an autonomous aircraft can be flown in the virtual environment in order to study the risks associated with flying un-crewed aircraft in a shared airspace. Multiple scenarios can be developed and flown in a safe environment to help us better understand and mitigate the risks of new technologies. Artificial intelligence tools are used to help identify patterns in the complex interactions that characterize the aerospace eco-system of the future. The industrial partner in this project will be able to use the results of the research to better align their business model with the users of artificial intelligence in the context of autonomous aircraft operations.

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Faculty Supervisor:

Catharine Marsden

Student:

Nicolas Vincent-Boulay;Angelina Cui

Partner:

Marinvent

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

Royal Military College of Canada

Program:

Accelerate

Deep neural networks for floorplan vectorization and feature tagging for first responders

An area of exploration that can lead to a critical improvement in the way first responders can better respond to situations (e.g., fires, shootings, etc.) in indoor scenarios is in the development of intelligent indoor mapping systems that provide critical navigation details to the first responders. This enables first responders to not only plan out their strategies in handling a particular indoor incident, but also provide them with real-time navigation details to accelerate these strategies. Two important components to building such intelligent indoor mapping systems is: 1) the digitalization of floorplans and 2) the identification and location of key features (fire extinguishers, hose attachment locations, stairs, doors, etc.) based on symbols in the floorplans. Doing these two components manually is intractable given the time-consuming and laborious nature of these steps. In this project, working with Mappedln, we aim to develop deep neural networks for automating the conversion of raster floorplans into digital vector formats, and automatically interpreting symbols in raster floorplans to identify what key feature they symbolize.

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Faculty Supervisor:

Alexander Wong;Mohammad Javad Shafiee

Student:

Brennan Gebotys;Saad Rasheed Abbasi

Partner:

Mappedin

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Improving User Experience and Accessibility of Online Medical Test Data via Gameful Design

In this project, we plan to study and improve the existing Best Tests section of the Clinician Portal from Alpha Laboratories. Best Tests provides metrics to clinicians that allow them to compare the effectiveness and cost of their test ordering patterns. However, the problem is that many of these comparison metrics are not easy to understand and even harder to integrate into the existing routines of doctors, nurse practitioners, and lab orderers (i.e., clinicians). This is a significant research problem, because if clinicians could alter their testing strategies based on these metrics, it would result in savings for the healthcare sector and faster results for patients. To address this design problem, we propose to improve the user experience and accessibility of the currently existing Best Tests online medical test data section using gameful design. We will iteratively improve the online experience using online prototypes and data collection from real clinicians, following a rapid iterative testing (RITE) approach alongside traditional online user studies. We will work closely with Alpha Laboratories to ensure the iterative implementation of our prototype design into the current online software.

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Faculty Supervisor:

Lennart Nacke

Student:

Katja Rogers;Triskal deHaven

Partner:

Alpha Laboratories

Discipline:

Design

Sector:

Health care and social assistance

University:

University of Waterloo

Program:

Accelerate

Feasibility of the Get A-Head® App for Clinical Psychology Research and Training in Emotion Focused Family Therapy

Due to COVID-19, adoption of and investment in technological solutions for remote mental health services (teletherapy) is rapidly increasing. While the evidence-base for teletherapy for individuals is robust, teletherapy research with families has been limited. Further, uptake of teletherapy by clinical training programs has been slow and knowledge about the feasibility of using these interfaces for remote live supervision has not yet been established. This pilot study will assess the feasibility of training student-clinicians in the delivery of Emotion Focused Family Therapy (EFFT) through the Get A-Head® app. This study will follow two families over the course of 12 weeks (two weeks pre-intervention, eight weeks of the EFFT intervention, and two weeks post-intervention). The process and results of the study are expected to generate critical feedback and preliminary results about the feasibility of using the Get A-Head® app as a tool for providing family therapy and training student-clinicians.

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Faculty Supervisor:

Dillon Thomas Browne

Student:

Jackson Smith

Partner:

Get A-Head Inc.

Discipline:

Psychology

Sector:

Health care and social assistance

University:

University of Waterloo

Program:

Accelerate

Non-Invasive Real-time Glucose-Monitoring Smart Textiles

You may have heard of monitoring heart rate in a smartphone using lasers for measurement. Now think of having the wristband or some other wearable gadget and your health status is monitored in your smartphone or your doctors’ cloud. Glucose is one of these parameters that can be measured by this wearable device but the challenge is measuring the concentration of glucose in sweat which is almost 1000 times lower than the glucose in the blood. Our group could measure these ultra-low levels of glucose in synthetized sweat. If this can be completed, it can be used beside other sensors to eliminate the need of needling yourself when you need to check your blood sugar. This is not the only issue; this wearable device will be on a textile platform to make easier and comfortable for whom are wearing this device. This will help doctors to make the best decision based on their records and health status. This project will also enable the chance of using microneedles for auto-injection of insulin in the case of an emergency.

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Faculty Supervisor:

Hadis Zarrin;Mehrab Mehrvar

Student:

Reza Eslami

Partner:

Sensofine Inc

Discipline:

Engineering - chemical / biological

Sector:

Manufacturing

University:

Ryerson University

Program:

Exploiting wild tomato genetic resources and pathogen effector diversity for resistance

Plant pathogens, including bacteria, can damage plants and cause significant crop losses. Among those Pseudomonas syringae is a major pathogen of tomato plants. It is now accepted that domesticated plant crops are often more sensitive to pathogens than their wild relatives. We aim to exploit a library of pathogens virulence factors to find new bacterial gene that trigger an immune response. Then we will use a targeted approach to sequence wild tomato resistance genes. Finally, we will exploit this data to generate a high-throughput library to identified new resistance genes in Tomato against Pseudomonas syringae. This project will provide benefit to the partner by idetifying new resistance genes in Tomato crops using both the diversity of the pathogen and of the wild relatives of domesticated tomato.

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Faculty Supervisor:

David Guttman;Darell Desveaux

Student:

Fabien Lonjon

Partner:

George Weston

Discipline:

Biology

Sector:

University:

University of Toronto

Program:

Accelerate

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