Innovative Projects Realized

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

30156 Completed Projects

2861
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5059
BC
812
MB
673
NL
842
SK
8957
ON
9368
QC
96
PE
579
NB
1120
NS

Projects by Category

Comparative Analysis on Various Blockchain Technologies and How Can They Transform the Financial Services for Scotiabank

Blockchain is an emerging technology that has the potential to change the way financial participants transact with each other. It enables direct transfer of value and financial assets between participants over networks without the need for a central authority (internet of value). It does this by combining the functionality of different technologies – distributed systems, smart contracts, mutual consensus verification, and cryptography. Given its potential Scotiabank is investing in technical research and business application. The intern will:
• Research blockchain protocols to understand how they operate, their strengths and weaknesses, and key differing characteristics.
• Collaborate with Product and Business Units to apply the technology through proofs-of-concept to determine how it can alter business models and to gain applied insights into the technology.

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Faculty Supervisor:

Sam Toueg

Student:

Partner:

Scotiabank

Discipline:

Computer science

Sector:

Technology; Finance and Insurance; Information and Communications Technology

University:

University of Toronto

Program:

Accelerate

Labeling a user’s speech in real-time for always-on VoIP

TurnMeUp is an iOS app for always-on voice communications. Users leave the app running in the background and can talk to the recipient (also using the app) at any time. This app is especially useful for coworkers listening to their own music in the background without needing to enter and exit voice call sessions manually. To conserve bandwidth and ensure that users listen to music without being unnecessarily interrupted, TurnMeUp sends voice signals to the recipient only if the user is speaking. The purpose of this project is to improve the algorithm used for detecting when the user is speaking (as opposed to background noise or other people speaking) in real time, using contemporary machine learning methods. This project will potentially improve the performance of TurnMeUp; to the greatest extent possible, it will ensure that the entirety of a user’s speech, and nothing else, is sent to the recipient.

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Faculty Supervisor:

Frank Rudzicz

Student:

Partner:

Synervoz Communications Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Toronto

Program:

Accelerate

Laboratory and Field Assessment of Performance of Treated Wildland Vegetative Fuels

The proposed project will assess and quantify the energy transfer from wildland fires as it relates to coverage of vegetative fuel with wildland fire chemicals for protection of wildland/urban interfaces. The project will extend on preliminary work on the relative performance of wildfire chemicals (e.g., water, gel, foam, and long-term retardants) on forest vegetation. The results of this proposed project will further develop proactive fire control measures, a priori to the occurrence of a fire, for community protection.

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Faculty Supervisor:

André McDonald

Student:

Partner:

FPInnovations

Discipline:

Engineering

Sector:

Agriculture; Professional, scientific and technical services

University:

University of Alberta

Program:

Accelerate

User Centered Design and Usability of a mHealth intervention for COPD management

Mobile health (mHealth) strategies hold a great promise to enhance treatment outcomes while mitigating health care costs (Hayes et al., 2014). It allows health care providers to tailor treatments to each individual based on their lifestyle. The primary objective is to involve COPD patients and their health care providers in the development of a mobile health infrastructure that aims to improve COPD management.

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Faculty Supervisor:

John Hawboldt

Student:

Partner:

Sequence Bioinformatics

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Advancing Design for Sea Level Rise—Fraser River Delta

With the onset of climate change, sea level rise is a major global concern including distinct local issues. This project looks at the extremely venerable coastal city/port city of Vancouver. Recent reports call for major infrastructure improvements primarily focused on engineering and not on spatial and design approaches to this challenge. Currently there is no coordinated effort to find innovative solutions to Sea Level Rise adaptation. This project looks at exploring Sea Level Rise adaptation as an opportunity to address multiple issues including opportunities for recreation, habitat creation, energy development and food security. This multi-scalar and multi-jurisdictional challenge is a unique opportunity to setup a collaboration between professional practice and academia. This project will bring together students and professionals to sponsor knowledge sharing between these various landscape architecture firms as well as with many different municipalities in the Vancouver Region

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Faculty Supervisor:

Kees Lokman

Student:

Partner:

Space2Place Landscape Architects;PFS Studio;University of Toronto Scarborough;Hapa Landscape Architecture Collaborative Inc.;PWL Partnership Landscape Architects Inc

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Data analysis for a Bridge Structural Health Monitoring System (SHM)

The world has many ageing bridge structures which are being used well beyond their design service life time. It is of essential interest for the governments and public to insure safety and sustainability of bridges. One of the most advanced techniques used to investigate the conditions of bridges is the Structural Health Monitoring (SHM). The targeted bridge is instrumented with several sensors and the data collection is performed using appropriate Data Acquisition System (DAQ). Several software and algorithms are used to stream the data life to the cloud and perform analysis on the data to extract the vital signals of the bridge. Decision is made after that based on the health condition of the bridge.

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Faculty Supervisor:

Aftab Mufti

Student:

Partner:

Intelligent Structures Canada Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

Accelerate

Real Time Tone Mapping of HDR Video Content

High Dynamic Range (HDR) content and displays are available on the market but the vast majority of the users displays are Standard Dynamic Range (SDR), not able to reproduce the enriched, higher quality and with more details HDR content. Thus, operators to compress the HDR content and make it ready to be able to be displayed on the SDR displays with the minimum possible loss of information are needed. These algorithms are called Tone Mapping Operators (TMOs). The majority of the TMO operators were designed to address HDR images but not video sequences. The naïve application of such an operator to HDR video sequences raises visual artifacts such as flickering, ghosting and temporal inconsistency. On this work we aim to extend an existing TMO to be able to handle HDR video without suffering from the before mentioned issues. TO BE CONT’D

View Full Project Description
Faculty Supervisor:

Panos Nasiopoulos

Student:

Partner:

TELUS (Vancouver, BC)

Discipline:

Engineering

Sector:

Information and cultural industries

University:

The University of British Columbia

Program:

Accelerate

An Assessment of Local Business’ Understandings and Needs for Community Leadership in a Small Urban Setting

Community leadership development and training programs must respond to changing corporate and public perceptions. There has been a lack of research on community leadership within small urban settings, where the impact that training and development programs have may be high. Our objective is to describe how local businesses in a small urban setting understand community leadership and what needs they have with respect to training and development. We will conduct fifteen in-depth interviews with a diverse range of local business leaders in Greater Victoria, British Columbia. Community leadership will be understood as something distinct from marketing and philanthropy. Understanding of community leadership will vary greatly by business and a diverse range of development needs identified to help inform Leadership Victoria’s future program and service offerings. This research will help to build and support stronger community leadership in Greater Victoria and other smaller urban settings across North America.

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Faculty Supervisor:

Nathan Lachowsky

Student:

Partner:

Leadership Victoria Society

Discipline:

Sociology

Sector:

Other services (except public administration)

University:

University of Victoria

Program:

Accelerate

Visualization, understanding and engineering of machine learning models for entity recognition

Machine learning is a discipline of teaching computers repeatable tasks that humans do well but slowly. At Interdata we are on a mission to use Artificial intelligence to understand the data being stored by organizations and the relationships between those data assets. As such Darrell will be working on methodologies and tools to expand our understanding of the algorithms we develop in order to improve them. He will then use those methodologies and tools to engineer new algorithms to be used by the organization to categorize and tranform data.

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Faculty Supervisor:

David Kristjanson Duvenaud;V. Radu Craiu

Student:

Partner:

Interdata Laboratories Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Learning robotic grasping for e-commerce sortation

We are conducting research on using techniques from Artificial Intelligence (specifically Machine Learning, Reinforcement learning, and computer vision) to automate the ability of a robotic arm equipped with a hand-like gripper to pick a wide variety of items. The robot uses the visual scene, provided through cameras, in order to choose which item to pick, and needs to then plan and execute a grasp. This is an open research problem at the cutting edge of robotics and AI and we plan to use a combination of state of the art academic research as well as internally developed algorithms.

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Faculty Supervisor:

Sanja Fidler

Student:

Partner:

Kindred AI

Discipline:

Computer science

Sector:

Technology; Automotive; Commercial Services

University:

University of Toronto

Program:

Accelerate

Synthesis of curcumin analogues and their profiling against various cancer biomarkers

Curcumin is a well-studied wonder molecule that displays many health benefits, including anticancer and cancer preventive activities. It has undergone / is undergoing over 100 clinical trials but has not yet culminated into a clinical drug owing to its poor uptake in body. Curcumin’s chemical structure offers an excellent prototype for modification potentially leading to a more effective anticancer agent. To address the unmet need in cancer treatment, we plan to synthesize and bioevaluate two series of rationally designed curcumin analogs, in collaboration of Paraza Pharma Inc. In this endeavor, clinically relevant curcumin analogs will be identified in an expedited fashion utilizing the biomarker profiling approach. Over the period of 8-months, ~25 rationally-designed curcumin analogs will be synthesized, purified and characterized at Acadia University and bioevaluated at Paraza Pharma, Inc.

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Faculty Supervisor:

Amitabh Jha

Student:

Partner:

Paraza Pharma Inc

Discipline:

Physics

Sector:

Manufacturing; Professional, scientific and technical services

University:

Acadia University

Program:

Accelerate

Deep Collaborative Filtering using two stage information Retrieval

The company wants to develop a state of art recommendation system for the clients. A recommendation system is a piece of software that provides products’ suggestions to customers on a website. For example the products suggestions that can be seen on Amazon’s web page are generated by its recommendation engine.
The typical recommendation engines work by utilizing the existing user-product preferences information. They recommend products to a user by comparing his preferences to other similar users’ preferences. The typical example of this is Users who bought item-A also bought item-B. This suffers from the problem of cold-start. This happens say when a user logins for the first time and has no preference information.
We propose to solve this problem by using user-content information and using a technique called deep learning. TO BE CONT’D

View Full Project Description
Faculty Supervisor:

Richard Zemel

Student:

Partner:

Layer 6 AI

Discipline:

Computer science

Sector:

Information and Communications Technology; Technology; Commercial Services

University:

University of Toronto

Program:

Accelerate

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