Innovative Projects Realized

Systematic evaluation and optimization of immune-targeting modalities for GBM and brain metastases.

The Centre for the Commercialization of Antibodies and Biologics (CCAB) is working with Empirica Therapeutics (Empirica), a Canadian start-up company focused on developing data-driven treatments for cancer, to address the unmet medical needs of glioblastoma (GBM), the most common adult malignant primary brain tumor. Current therapies are only partly effective, with frequent relapse and poor patient survival, which correlates with the presence of CD133+ brain tumor-initiating cells that are also implicated in treatment-resistant GBM. By partnering with Dr. Jason Moffat at the University of Toronto (UofT) and collaborators at McMaster University (MAC), Empirica has used genomic screening technology to identify CD133 as a promising target for effective treatment in both in vitro and in vivo models using Chimeric Antigen Receptor (CAR)-T cell therapy. CCAB and Empirica will work with the Moffat group’s technological expertise in CRISPR-Cas9-mediated gene editing toward the pre-clinical development of allogeneic, armoured CD133-targeting CAR-Ts as novel, improved and more affordable treatments for potentially all types of cancer, including GBM. The overall aim of this work is for CCAB and Empirica to fund clinical trials in GBM patients at Canadian hospitals and centres, thus offering Canadian patients access to new therapeutic options.

Évaluation du projet pilote de navette autonome et électrique : sécurité routière, acceptabilité sociale et analyse des interactions entre les usagers de la route.

Le projet-pilote de navette autonome (et électrique) de la ville de Candiac représente une opportunité intéressante pour étudier les effets de la présence d’une navette autonome sur le réseau routier. C’est précisément ce que nous proposons avec ce projet de recherche, qui compte trois objectifs : le premier vise à connaître les perceptions et pratiques des usagers de la navette (projet-pilote). Le deuxième objectif vise à connaître les perceptions des riverains par rapport à l’arrivée des véhicules autonomes sur le réseau routier. Finalement, le troisième objectif vise à documenter les comportements des usagers de la route en présence de la navette autonome sur le réseau routier. Tous ces objectifs impliquent des collectes de données le long du parcours de la navette, que ce soit des questionnaires auprès des usagers (aux arrêts et dans la navette) ou des riverains (sur le web), des observations directes aux intersections (surtout pour les piétons et les cyclistes en interaction avec la navette, et des collectes de vidéos à partir de caméras sur la navette et aux intersections. To be continued.

Green Chemistry for Green Solvents

This project focuses on the development of new solvents, to replace those that are currently used in industrial processes. Currently, the majority of solvents used in industry are harmful to both people and the environment. These solvents are full of volatile organic compounds, which are released to the atmosphere and contribute to smog formation. Globally, smog is a major risk factor for human health, following only malnutrition, dietary risks, high blood pressure, and tobacco. We plan on developing new solvents that are free of volatile organic compounds, and thus cannot contribute to smog formation. This project will further help to cement both TBF Environmental and Canada’s commitment to developing clean technology.

Simulation et optimisation de la chaîne logistique de l’entrepôt d’Air Canada Cargo

Le stage consiste a modeliser, a I’aide d’un simulateur, I’entrepot d’Air Canada Cargo afin

d’optimiser les processus de chaine logistique. Nous voulons voir, entre autres, comment

integrer les nouvelles regles legislatives liees a des mesures de secUr’lte dans les

procedures, I’impact de nouveaux horaires de travail ou des nouvelles technologies Ie lies

que les etiquettes electroniques. Cet outil d’aide a la decision utilisant simulation et

optirnisation permettra a Air Canada Cargo de rnieux quantifier les differentes eta pes reliees

a la gestion du fret dans son entrepot de Montreal. De plus, I’entreprise sera en mesure de

comparer des solutions a I’aide d’indicateurs de performance fournis par Ie modele. Ces

indicateurs aideront les gestionnaires a prendre des decisions eclairees et a realiser

d’economies en identifiant les endroits ou des gains sont possibles.

Dance Like the Machine’s Watching

We are proposing an investigation of techniques and technologies to support media-enhanced group performances that integrate different performative art forms (dance, theatre, clown, voice, choral) with responsive mixed reality technologies and public data sets. We will work with a group of young performers (13-17 years old) and a local Vancouver choreographer to deeply investigate, with embodied methods, the potential ways of creating a group performance that truly benefits from a layered digital reality. Several interim performances will be held to gather feedback from audiences at venues to be determined. A larger final public performance will be scheduled near the end of the internship. We expect the knowledge gained from this investigation will inform performers/choreographers who want to integrate mixed reality into a performance lexicon, and will inspire more technologists to target creative expression as a goal in machine learning and interaction design. The results will also be indicative of new cultural expressions that will be made possible when augmented reality technologies are ubiquitous and integrated into public spaces of all kinds.

Real-Time Fashion Landmark Detection for Fashion Analysis and Understanding

The goal of this research is to develop an algorithm which allows Dataperformers to detect and match the apparel present in the video with the apparels in their inventory. To uniquely identify apparels it is very important to match them based on certain key areas. Fashion landmarks are the position of functional key-points defined on the fashion items such as the corners of a neckline, hemline, and cuffs. In this research we propose an algorithm which can find fashion landmarks in real time. We do so by learning to extract features which can provide location information as well as visibility of the fashion landmarks. This algorithm can be the core component to design the in-video store where a video consumer can purchase apparels from the videos. It is one of its kind approach for ecommerce.

Étude de la fiabilité opérationnelle des pompes centrifuges soumises à des hautes pressions

Un équipement sous pression est un réservoir ou une conduite conçue pour contenir des gaz ou des liquides à une pression nettement différente de la pression atmosphérique. Ce type d’équipement peut être fabriqué, entre autres, en métal ou en matériau composite. La production de ces équipements évolue de manière très significative et le développement informatique lié à ce domaine ne cesse pas d’avancer vu qu’il est maintenant possible de faire des calculs numériques précis sur la distribution des contraintes, les pressions, les températures et les écoulements. Beaucoup de chercheurs ont élaboré des méthodes expérimentales et des méthodes numériques afin d’atteindre un objectif commun consistant à réduire les risques d’éclatement de ces cylindres lors de l’augmentation excessive des pressions internes/externes et des températures. L’objectif principal de ce projet est d’étudier la fiabilité opérationnelle des équipements de type pompe soumis à des hautes pressions et des températures variables. À l’aide du logiciel commercial Abaqus couplé avec le langage de programmation Python, nous prévoyons mettre en place un modèle éléments finis 3D d’une enceinte de pompe pour simuler son comportement élastoplastique basé sur une variation de température allant jusqu’à 100 °C. To be continued.

Modèles d’estimation a priori des efforts de développement de logiciels embarqués pour les communications dans les mines

Toutes les entreprises font face au défi d’avoir à estimer les efforts de développement de leurs logiciels. Dans la littérature, la quasi-totalité des modèles d’estimation des efforts de développement de logiciels sont basés sur des données collectées a posteriori sur des projets complétés : ils correspondent donc à des modèles a posteriori modélisant le passé. Les objectifs de cette recherche sont d’opérationnaliser et expérimenter dans le contexte de Newtrax la proposition d’une mesure a priori de la taille fonctionnelle d’un logiciel puis en évaluer la contribution dans des modèles d’estimation a priori avec les données historiques de Newtrax dans le contexte spécifique de développement de logiciels embarqués pour les communications sous-terraines dans les mines. Les projets de logiciels de Newtrax développés par Newtrax au cours des 12 derniers mois seront mesurés avec la norme COSMIC – ISO 19761.

Power at the Edge: Exploring Sustainable Energy Security in the Rural and Remote Communities of Atlantic Canada

The rural and remote communities of Atlantic Canada are plagued with insufficient and interrupted access to energy sources. Lately, the provinces of Atlantic Canada have realigned their future clean energy goals to include increased collaboration with Locally Owned Renewable Energy Small-Scale (LORESS) projects. However, no study has examined the effect of these programs on the sustainability and energy security concerns of the rural and remote communities of Atlantic Canada. In our study, we attempt to address this research gap and ultimately understand the challenges in generating, distributing, and transmitting renewable energy through the collaborations between major electric utilities and locally owned small-scale projects in Atlantic Canada

Learning Jungle AI Recommender System for Enhanced Education

Devhaus Corporation operates 20 early child education centers across 5 countries including Canada, USA, Singapore, Cambodia and Philippines. To further implement its principle of Observation to Education, Devhaus is partnering with York University research team to develop an Artificial Intelligence Recommender System to help teachers across the world select optimal lesson plans for each kid based on the learner’s behaviors. The interns will analyze the set of existing lessons, historical recommendations, and experts’ opinions to better understand the temporal and logical dependence of the lessons; and more importantly, the interns will customize the state-of-art recommendation algorithms for this business problem. Devhaus shall get a powerful AI tool to implement its successful Observation to Education practice and principle in its learning centers in different countries and cultures.

Synchronous Collaboration in Multi-user CAD environments

Advances in cloud computing have enabled the Computer-aided design industry to develop fully-synchronous, collaborative CAD. Synchronous CAD is unique in that it allows multiple users to manipulate the same CAD model at the same time, and saves changes in real time—much like a “Google Docs” document. These new design environments engender real-time collaboration and are touted to be the future of CAD. This work aims to understand the effectiveness and limitations of such platforms, and study how they may affect design workflow and methods. To date, we have consolidated prior art, engaged with potential industry partners, and conducted a baseline pilot study. Our preliminary analysis identified coupling effects to be a challenge in synchronous collaboration tasks. We would like to further our investigation to understand the difficulties arising in the use of synchronous CAD. After an in-depth analysis, we would propose a design support that will mitigate some of the shortcomings of working in collaborative CAD environments.

Modeling the viscosity of binary and ternary mixtures of ionic liquids

Ionic liquids are organic-cation salts that feature the property of being liquid at lower temperatures than their inorganic counterparts. This peculiar characteristic added to their versatility and recoverability make those compounds excellent candidates for many applications such as a replacement for conventional toxic and hardly recyclable organic solvents, among others. However, their high viscosity is often a hindering factor in the implementation of ionic liquids in viable industrial processes. Mixtures of ionic liquids are a way of fine-tuning their physical and chemical properties. Mathematical models of physical properties are therefore essential to save time and money on the design of those mixtures. The aim of this project is to build a viscosity model for mixtures of ionic liquids, valid over wide ranges of composition and temperature. Since viscosity data for ionic liquid mixtures over wide ranges of composition and temperature are very scarce, the objective of this project is to obtain experimental data, which will permit to calibrate the model. We expect that the data will permit the development of a viscosity model that will pave the way for process simulation with ionic liquid mixtures.