Innovative Projects Realized

Data Architect Co-Op

Enterprise Data Architect Co-Op

Holding Pavemetrics : Intelligence artificielle appliquée à l’analyse de titres boursiers

Le projet vise à utiliser l’intelligence artificielle pour en venir, à terme, à analyser les données boursières pertinentes en lien avec une stratégie d’investissement de type “Qualité” et en extraire des indicateurs de cause à effet ayant un pouvoir prédictif par l’utilisation d’une approche de « Machine Learning » (« Deep Neural Network », « Data Mining » et autres). Ceci permettrait ainsi de prendre des décisions d’investissement qui minimisent le risque pour un certain rendement espéré. Les données financières et économiques de plusieurs années antérieures seront tirées d’une plateforme d’information financière complète et fiable à laquelle l’entreprise a accès.

City of Toronto Heritage Census Project

The City of Toronto wishes to assemble a comprehensive set of available historical neighbourhood-scale Census data. While a wealth of historical Canadian Census data exist in the public domain, it is largely inaccessible to users who lack specialized training and skills due fragmentation of data holdings and their storage in different formats. Making use of existing data is extremely labour-intensive, as the user must contend with multiple legacy file formats and variable naming schemes and geographic unit identification codes that are inconsistent across time. Building on established historical Census, data management, and spatial analysis expertise at Western University and the University of Toronto, this project will create a fully documented spatial dataset that contains available Census data for submunicipal areas, including uniform identifier codes for variables and geographic unit across the entire time period. While useful for the City of Toronto, the techniques used are applicable to other geographic locations and levels. The historical Census database created by this project will be used as a decision support and planning tool for the Toronto Heritage Survey. Awareness of the timing and location of historical cultural communities will facilitate engagement with both historic and contemporary community groups as the City of Toronto conducts the Toronto Heritage Survey. More generally, the historical Census database will be made available to all City of Toronto divisions to allow use of these products in a wide range of possible cases.

Sustainable Energy Production Using Biomass Gasification

Considerable growth in the global population and economy leads to an increase in fuel demand. This requires production of clean fuels with minimum CO2 emissions to maintain climate, energy, political, and social security. Hydrogen is a promising carbon-free fuel that can be produced from various renewable sources such as wind and biological systems. The microalgal hydrogen production has potentials of negative CO2 emissions and is less energy intensive, compared to the fossil fuel-based hydrogen production. Also, the operating conditions in bio-hydrogen production processes are generally atmospheric pressure and temperature. The partner organization will be benefit from this effective biohydrogen production technology toward decarbonization.

Peptide-based materials for rapid sutureless and scarless surgical repair

Every year in the United States alone, over 30 million surgical incisions are performed, and another 7 million wounds are causes by trauma. Most of those wounds will heal on their own, but nonetheless always lead to scarring no matter what kind of material is used to close the wound. There are a range of materials and techniques used to close wounds. All agree, however, that an ideal approach to wound closure should be easy to use, fast and painless, cost-effective and not create permanent scarring. Many advancements have significantly improved wound healing. However, all continue to have significant drawbacks either in how useable they are in surgery, or how well they promote healing, and all continue to leave scars. To this end, we have developed a new

Automation of a direct air capture to renewable natural gas production platform

Global warming is a leading threat to humanity. Carbon capture, especially direct air capture (DAC), is the key to its reversal. The bottleneck of the DAC expansion is its high cost vs. the insufficient value of CO2. On the other hand, Atlantic Canada has unmet natural gas demand, especially after the termination of Sable and Deep Panuke gas production in 2018. Furthermore, to address the emission challenges, the Canadian Government has put forth an aspirational mandate to blend in 10% of renewable natural gas by 2030. To tackle these challenges, Gaia Refinery is developing a platform to employ a passive wind-assisted DAC system integrated with an RNG production platform utilizing direct methanation within microbial electrosynthesis cells to facilitate the economic output of pipeline grade RNG while removing CO2 from the atmosphere. Compare with traditional organic-based RNG, our system has fewer feedstock constraints, a higher output rate, and can eliminate the need for gas purification/upgrading. We are currently developing our demonstration unit. Expertise in electrical engineering and automation will help us integrate the various modules of the system and control/monitor them through a computer interface.

Bridging the gap: understanding relationships between art, “intangible” community assets, and climate actions and outcomes

A sense that arts practices have a critical role to play in supporting sustainability is long-standing; but, how arts can contribute to addressing these challenges is a question that is becoming more urgent due to climate change. Where science has lacked effective communication about climate change impacts, there is a hope that arts can create narratives and visualizations that help form a common language and change perceptions. Meeting the challenge of sustainability will also require engaging with multiple dimensions of understanding and arts practices hold promise for exploring cultural and aesthetic dimensions, in particular. However, efforts to link arts and arts-research to climate change impacts have shed light on a critical trade-off – either arts practices retain their aesthetic-focus but lead to non-linear outcomes with poor measurement prospects, or arts practices adopt a linear and measurable process but lose their aesthetic, exploratory, and emergent core capabilities. The goal of this research project is to gather existing information and knowledge to develop a middle approach. Rather than focusing on direct links between arts practices and climate outcomes, this project will review existing literature to uncover subjective, normative, and intangible outcomes (or ‘bridging outcomes’) of arts practices that are critical for inspiring transformative action on climate change. The results of this study will contribute to the efforts of the Metcalf Foundation (Dr. Maggs) in devising climate change-related recommendations, program development, and targeted investments. These, in turn, will better position the arts sector to support sustainability and climate change-related societal goals.

Application of Machine Learning in Radiation Oncology Scheduling

The Ophthalmology department of CHUM receives almost 400 patients per day, each of which needs to go through different tests and consultations. Scheduling those appointments is a complicated task as it involves multiple shared resources, precedent constraints between tests, and uncertainty in tests’ durations, cancellations, emergency patients, etc. The current manual scheduling at the department results in high fluctuations in workload between days, inefficient use of resources, and long waiting time for patients.
In this project, we aim to propose an optimization model to schedule patients’ appointments. The problem is modelled as a multi-appointment, multi-resources patient scheduling problem. The second phase of the project aims to utilise machine learning tools to measure stochastic factors of the problem and to integrate that information into a decision-making framework to deal with uncertainty in scheduling.

WCRI SimplySMART Project

Waterloo Co-operative Residence Inc (WCRI) is Canada’s largest student housing co-operative. It has been providing co-operative student housing and programming for post-secondary students in the Waterloo region for over fifty years. As a co-operative, WCRI relies on members’ involvement in providing affordable housing and creating a supportive and welcoming community.

Project SimplySMART focuses on documenting current WCRI processes, writing content for the website, conducting market research on e-commerce and ERP software vendors, identifying necessary winning conditions for digital transformation, devising execution strategy options, and preparing a strategy implementation plan.

Implementation of design controls through Quality Management System

Over 250,000 Canadians suffer from epilepsy, a debilitating neurological condition with no known cure. For many patients, the only solution is the surgical removal of the seizure-trigger zones in the brain. Unfortunately, current electrode systems that are designed to record brain activity and target the seizure foci are highly invasive, not very precise, and do not provide adequate coverage of the brain to sufficiently isolate the target sites. This limits the standard of care for patients struggling with epilepsy, as healthy tissue may get extracted as the surgeon compensates for the lack of high-resolution mapping. To help address these gaps, Neuraura Biotech Inc. has developed novel electrode technology that provides 3 times higher resolution and 20 times more coverage of the brain. To facilitate the first clinical trials of this recording and 3D brain activity visualization system, quality control systems must be expanded and regulatory approvals must be obtained. The successful translation of this Canadian technology to serve both researchers and patients will require strong adherence to regulatory requirements and market analysis for commercialization. This quality management and strategy internship will equip the student with the skills needed to commercialize products, secure partnerships, attain regulatory approvals, and work in a multidisciplinary start-up environment, which will be key in their future aspirations in serving patients. The intern’s contributions to risk analysis, project management, and regulatory approval applications will help accelerate the organization’s commercialization timeline and help us serve both researchers and patients with higher-quality devices for the treatment of neurological disorders.

Pre-training large models that generalize well across the chemical space

The intern is expected to develop a pipeline for training large machine learning models on drug-like molecules to learn a broad understanding of biochemistry. This pipeline involves developing a model that can learn on many biological and quantum mechanical tasks concurrently while evaluating and improving the structure of the model using low-cost approaches from recent literature. Then, he will implement transfer learning to evaluate the model’s performance in predicting the properties of unseen molecules for unseen tasks. This last part is very relevant for the partner organization since it is expected to improve their ability to predict molecular properties on real-world tasks and speed up the discovery of novel drugs.

Product Innovation and Process Improvement for SR.ai’s Investment Research Platform

The field of responsible investing is rapidly expanding, with even greater attention on the importance of responsible investment in 2021, as seen in the aftermath of the hugely impactful COP26 summit. Directing our financial resources in a sustainable direction has the potential to have a massive impact on helping us meet the Sustainable Development Goals set forth by the UN. Though the importance of better alignment between finance and sustainability is clear, and now has a very strong consensus around it, investors still lack the right tools to support their research process in terms of sustainability. They rely on high level data that is largely known not to be reliable, which leads to massive misallocations of capital. The mission of SR.ai is to bring more rigour to the world of responsible investment, using our technology backed by peer-reviewed research in sustainable finance, produced through collaboration with the University of Toronto RiskLab quantitative finance research center, led by our CEO Alik and his PhD Supervisor Luis Seco.

The mission of SR.ai is to help the responsible investment industry in directing global financial resources towards sustainable and socially responsible companies and initiatives. The objective of the collaboration is to improve SR.ai’s product, assist in our product management and business planning process, and identify “white space” opportunities for SR.ai’s AI technologies.