Innovative Projects Realized

Machine Learning based Combustion Control for Zero Carbon fuels

The Canadian Net-Zero Emissions Accountability Act targets net-zero greenhouse gas (GHG) emissions by 2050 with similar commitments around the globe. In the short-term, emissions from heavy-duty internal combustion engines (ICEs) that dominate the power generation in freight transportation industry can either be reduced or eliminated with zero-carbon fuels such as Hydrogen / Ammonia. One solution is the implementation of advanced combustion and optimal control strategies for the best performance and lifespan of the ICE. Model predictive control (MPC) is one of the most promising control strategies for handling these highly constrained nonlinear systems. The research will focus on integrating machine learning (ML) for the model and controller to discover state of the art control methods to optimize energy conversion in
mobile applications. The student will have the opportunity to gain experience in machine learning, MPC and experimental engine testing during their stay at the University of Alberta.

Schéma conceptuel et conception d’environnements immersifs appliqués en contexte de loisir pour l’inclusion des personnes autistes

Ce projet vise à améliorer la participation sociale des enfants autistes et de leur famille en utilisant des activités de loisir immersives basées sur la réalité virtuelle (RV), en particulier dans un environnement de type CAVE. Actuellement, les enfants autistes rencontrent des obstacles à la participation sociale en raison de divers facteurs, tels que des environnements inconfortables et des malentendus liés à leurs caractéristiques personnelles. Le projet propose d’utiliser la RV pour créer des activités inclusives qui tiennent compte des besoins et des forces des personnes autistes, favorisant ainsi leur participation sociale et leur bien-être. Le projet a trois objectifs principaux. Tout d’abord, élaborer un schéma conceptuel novateur en classifiant les activités de loisir préférées des enfants autistes, en mettant l’accent sur le type de jeu, les compétences développées et le niveau d’interaction. Ensuite, développer un scénario de jeu spécialement conçu pour encourager des interactions fortes entre les utilisateurs, adapté aux divers intérêts et niveaux de fonctionnement des enfants autistes. Enfin, expérimenter le jeu dans des organismes partenaires. Le projet contribue à la formation du stagiaire et s’inscrit dans une initiative plus large visant à renforcer l’inclusion sociale des enfants autistes au Canada en utilisant la RV.

Decoding Political Messaging to Working-Class Voters In Canada

This research project, “Decoding Political Messaging to Working-Class Voters In Canada,” is interested in understanding how the three major Canadian political talk to working-class voters. We will be looking at what the Liberals, Conservatives, and New Democrats say about important topics like jobs, climate change, and healthcare. By exploring and analyzing their party platforms from 2003 to 2021, we want to understand the similarities, differences, and significance of what and how they are communication to working-class Canadians. This study is valuable because it can offer practical recommendations for communicators, policymakers, and leaders to do a better job of reaching everyday Canadians. The partner organization, Resonant Strategic, will gain useful information and tips on connecting with working-class citizens, making their messages clear, and tackling issues that matter to everyone in Canada.

Mechanical Design and Power Drive Improvements for Moovee’s One-seater Prototype

An emerging concept in urban transportation systems is utilization of small electric vehicles that meet the demands for enclosed personal mobility. These types of vehicles are generally small and lightweight but require much less space than more conventional vehicles such as the Smart Car. Furthermore, the vehicle is all battery electric. Recent developments have utilized innovative in-wheel electric motors mounted on carbon fiber platforms. In such systems, each wheel unit contains a drive motor enabled with regenerative braking, steering, and suspension, all digitally controlled by a computer. The in-wheel motor concept enables maneuvers such as spinning on the wheel’s own axis, moving sideways into parallel parking spaces, and lane changes while facing straight ahead. Furthermore, the vehicle is foldable, resulting in smaller space requirements when parked. The folding mechanism also allows for safety in crash scenarios. The above features make the vehicle ideal for crowded cities with limited spaces. The proposed activity involves improvements in power drive and mechanism design for the Moovee’s Insectra vehicle and their proof-of-concept demonstration.

Machine learning based classification of protein states from lipid fingerprints

This project is dedicated to unveiling how proteins within cell membranes adapt to their surroundings, particularly the lipid environment. Employing computer simulations and machine learning (ML), we focus on RAS signaling proteins and Mga2 transcription factors. RAS proteins, crucial for cell growth and division, are anchored to the cellular membrane and often exhibit mutations in cancer patients. Conversely, the Mga2 dimer, a transmembrane protein, plays a role in regulating the synthesis of unsaturated fatty acids. Through simulations of one of the proteins, RAS-RAF complex or Mga2, in diverse lipid environments, we collect data to train ML models, aiming to predict distinct protein states in varied lipid mixtures. Additionally, we explore if different protein states trigger shifts in the lipid environment. At the Centre for Molecular Simulations at the University of Calgary, our expertise lies in leveraging computer simulations to investigate lipid-protein interactions. Integrating ML with our studies opens new avenues for exploring lipid redistribution in cellular membranes and its impact on protein dynamics. Simultaneously, the Lawrence Livermore National Laboratory will benefit from an extended protocol for more complex systems, expanding its application to other proteins and using other lipid parameters.

Effects of rotational grazing implementation at the Thunder Bay Community Pasture on soil and forage health

This project is about creating dynamic maps of cattle movement over pasture foraging patches that will be characterized by forage plant composition, cover, and nutrition and takes place at the Thunder Bay Community Pasture (TBCP). The project is intended to test how the costs of implementing rotational grazing on the TBCP can be minimized by working with principles of cow-calf pair cohesion to manage the placement of “leader” cows in paddocks, and to make recommendations on how average summer daily gains for the cattle on the pasture can be increased along with increasing soil health, forage plant diversity and pasture utilization. The results will be matched to Ontario’s pasture utilization targets, which are currently being defined by OMAFRA, the Ontario Ministry of Agriculture, Food and Rural Affairs.

How does the prefrontal cortex respond to various obstacle avoidance tasks

The proposed project will look at participant’s brain activity while completing a stone-stepping task. Brain activity will be measured through EEG while the stone-stepping task will be projected through the Motek C-Mill treadmill. The research goal is to synchronize the data from a motor event occurring on the treadmill to cortical brain activity. The participants will be asked to complete a Stroop stone stepping task, where a green stone means to step on the stone, while a red stone means to avoid it. By Synchronizing the cortical activity to a motor decision-making task allows researchers to answer a fundamental question of what is occurring in the brain during various motor tasks. Wilfrid Laurier University will benefit from this partnership by strengthening an existing connection between Dr. Michael Cinelli and Dr. Mark Hollands, who were colleagues at the University of Waterloo. This connection will strengthen Wilfrid Laurier and Liverpool John Moores by creating an opportunity for future research and knowledge translation. Liverpool John Moores University will benefit from the partnership by having a dedicated intern understanding the nuances of the Motek C-Mill treadmill as this equipment is new to Dr. Mark Hollands’ laboratory.

Study Cluster melting by enhancing Parallel Tempering Monte Carlo Simulation with Gaussian Software Interface through GPU Acceleration for Efficient Energy Calculation

This project aims to simulate the melting of clusters that are important in the field of nanotechnology and catalysis. We will improve the computational efficiency of Parallel Tempering Monte Carlo (PTMC) simulations by integrating GPU capabilities and interfacing with Gaussian software for energy calculations. The project is an essential part of a Ph.D. thesis that aims to speed up simulations. It will involve developing compatible codes for various GPU architectures and establishing a connection between PTMC simulations and Gaussian software. This will expand the research capabilities in nanoscience, allowing for a deeper understanding of cluster melting. The project will benefit the participating institutions in Toronto and Berlin by building expertise in high-performance computing and nanotechnology, This knowledge will advance scientific research and equip future scientists and students with valuable skills in utilizing cutting-edge computational tools and methodologies.

New spin cross-over complexes for quantum calculations

Most computers and materials work on scales such that quantum effects can be comfortably ignored. But as we aim to make computers ever smaller, quantum effects will cause difficulties; however, they also provide opportunities. Spin-crossover (SCO) materials are molecules that can “Flip” between two states: either high or low spin binary states, making them essentially the miniaturization goal for electronics. These molecules do not exist in a vacuum, but rather in crystals. When molecules crystallize they can do so in several different ways, called polymorphs that affect the space around the individual molecules and this can make a molecule either show or fail to show SCO activity. It’s hard to make molecules, and to have it then fail to crystallize in a polymorph that is conducive to SCO behaviour would be unfortunate. It is really hard to predict the polymorph that a compound will make; however, it might be possible to do so with a large enough dataset and modern machine learning tools. In this project we are looking to build this model with the help of an international intern so that we can move towards building highly miniaturized logic gates and perhaps eventually, very, very small computers.

Neighbourhood Sustainability Assessment: Connecting Impact with Policy Intent

The Neighbourhood Sustainability Assessment: Connecting Impact with Policy Intent project seeks to conduct a sustainability assessment of the UniverCity neighbourhood on Burnaby Mountain. The Community Capital NSA tool will be used to evaluate how well the UniverCity neighbourhood is meeting its vision of being a model sustainable complete community. Results will be subjected to a comparative analysis with the results of an earlier assessment done by the Foundation for Sustainable Area Development’s FSA assessment tool. The comparative results analysis will contribute to the international dialogue surrounding rapid vs. in-depth assessment practices, sustainability assessment frameworks and indicators. The comparative analysis will also work to validate the results of the two assessments, influencing the future sustainability action and reporting priorities of one of Canada’s leading sustainable neighbourhood developments.

Ultimarii – Market Entry and Product Launch

Ultimarii is focused on accelerating the approval process for major projects by leveraging advanced large language model (LLM) technology to streamline environmental impact assessments (EIAs) and other regulatory filings. Our platform offers tools for auto-drafting, summarizing, analyzing, and predicting outcomes of regulatory applications, thereby increasing the efficiency and reducing the costs associated with project approvals. Ultimarii aims to support projects across various sectors, including renewable energy, carbon capture storage, small modular reactors, mining, and more, indirectly contributing to the reduction of greenhouse gas emissions and the promotion of sustainable development.

The selected intern will play an important role in supporting Ultimarii’s growth trajectory by independently executing crucial marketing activities, such as digital marketing campaigns, branding initiatives, and market research projects. The intern will establish Ultimarii’s online presence by creating branded social media accounts and crafting engaging content spotlighting the co-founders’ expertise and the company’s value proposition in streamlining regulatory filings for environmental impact assessments. Additionally, the intern will conduct comprehensive market research to draft a competitive analysis, identify potential partnerships, refine marketing strategies, and design a targeted campaign to establish Ultimarii as a thought leader in regulatory compliance. Through these initiatives as well as some general administrative duties, the intern will play a pivotal role in accelerating Ultimarii’s growth, increasing its market presence in Alberta and positioning it for success across Canada.

Thin Air Labs Funding Catalyst: Unlocking sustainable operating models for non-dilutive funding delivery

Thin Air Labs is a venture capital and services firm in Calgary Alberta. We are a founder first organizations that supports start-ups with data management, capital strategy and software development. Our Funding Catalyst team has secured over $40,000,000 in non-dilutive funding fro innovative ventures, through grant writing and capital strategy consulting.

The intern role will be a critical addition to the funding catalyst team and contribute to the creation, maintenance and strategy of the funding catalyst business line. The intern will synthesize complex information to articulate founders vision, support the creation of a grants database, and contribute to developing sustainable tools for grant writing and capital strategy, management. The Intern will report to the Funding Catalyst team lead, and work directly with the funding Catalyst team, with specific development goals over four months. At the end of the internship, the intern will be expected to produce a summary report on their activities and achievements over the four months. They will also be expected to generate an impact report on how the Thin Air Funding Catalyst team has influenced Calgary ventures and Canadian startups, highlighting its contributions and broader societal impacts.