Projets novateurs réalisés

Advanced Analytics in Multiple Sclerosis Research

The multiple sclerosis (MS) clinic at St. Michael’s Hospital (SMH) is among the largest in the world. While considerable data is collected from the MS clinic in both structured and unstructured form, the ability to glean this information to assess quality of care and conduct advanced analytics such as predictive modeling is limited. In this project, a quality improvement dashboard will be developed based on automation of clinical information extraction process. Predictive models will be used on existing clinical data to optimize treatment strategies and predict patient outcomes such as relapse rates, disability progression, and treatment failure. These models could then be used in clinical practice to identify high risk patients in a timely manner for appropriate follow-up and treatment optimization.

Intelligent Character Recognition (ICR), Optical Character Recognition (OCR) and machine learning based corrections of data transcription from scanned business documents

SS&C processes more than 80% of financial scanned and faxed documents in the US and requires large amount of manual labor in order to map information from a document into another form. Advances in neural networks applied to computer vision have produced text detection and recognition that nears human performance. This project will be leveraging these approaches to address the main challenge of applying image segmentation and character recognition techniques to large volumes of documents, namely the sensitivity of the process to phenomena like the variability of text, document formats and imaging conditions. The expected benefits of the project to the industrial partner are (i) reduction of human error in the document workflow, and (ii) faster turn-around times for customers of SS&C.

Detecting Company-Specific Purchase Evidence from Twitter Posts

Delphia’s business model revolves around generating insights for investing firms that allow them to make better trading decisions. It has been shown that detecting when Twitter users post about recent or future purchases has the potential to increase the accuracy of company sales forecasts, which in turn can inform stock trading strategies. This internship project aims to develop automated means to detect and quantify purchase related posts on Twitter. The intern will conduct a machine learning project which will involve creating a dataset of purchase related tweets and using it to train a purchase tweet detector. Success in this project could lead to new data products for Delphia to sell to its financial investor clients.

Scaling simulations in population health via machine learning

Computer simulations provide a safe alternative to taking a trial-and-error approach in the real-world. If a simulating intervention is found to be inefficient or even harmful, then it can be canceled without causing harm to real individuals. Consequently, simulations are increasingly sought after for complex social problems such as homelessness and the spread of the Human Immunodeficiency Virus (HIV). However, such complex problems can be tackled using many different interventions (e.g., increasing shelters for homelessness), each being defined by several parameters (e.g., number of beds). Simulating all possible interventions and their parameter values is prohibitive; there are too many combinations to simulate, and each simulation can take a long time to complete when the computer model is highly detailed. TO BE CONT’D

Enhancing Security and Quality of Service in NFC-based Smartphone Applications

The primary objective of this MITACS Cluster project is to investigate, design and prototype novel

techniques for the integration of security and quality of service in near field communication (NFC)-

based smartphone applications. Universal NFC Cloud Connect Inc., a new start-up company based in

Halifax, Nova Scotia, that ties mobile devices to location-specific events via the Cloud, thus enabling

anyone with an NFC-based smartphone to be identified at a specific location at a specific time.

However, two important challenges that need to be addressed before the product can be successfully

deployed are security and quality of service (QoS). The project will explore techniques that will

integrate existing security and QoS protocols with novel identity-based encryption and QoS

enhancement algorithms on smartphone applications. The Cluster project will be a crucial part in the

partner organization’s road to commercialization of the product. This can open up enormous

application possibilities in a variety of consumer application areas, such as the hospitality industry…………..TBC

Visualizing Unspoken Words

In order to a facilitate a productive dialogue about contemporary Canadian race, ethnicity and religious rights, my research project entails the following three components:
1- an interactive artistic installation;
2- data collection from the target audience in response to the installation using sensor-based software application;
3- public visualisation of such data in the form of computer-assisted art in order to present the results back to the community for further discussion.
This three-tier project further develops the existing interactive art models as it creates a clear one-on-one experience, proposes an anonymous and seamless method of data collection and utilizes artistic data visualization methodology.
The initial artwork consists of a mirror reflecting visual and textual elements concerning race, ethnicity and religious discrimination which then the audience respond to using the interactive controls that appear on the mirror. TO BE CONT’D

Towards Parameter Robust Hierarchical Clustering

Density-based clustering is a statistical learning technique that aims at finding high density regions in the data separated by low density regions, finding applications in virtually all fields of knowledge. Hierarchical density-based clustering goes one step beyond and finds a hierarchy of density-based clusters at different density levels according to a user-defined density smoothing parameter. In this project, we intend to investigate how a set of density-based clustering hierarchies with regard to different values of the density smoothing parameter can be used to build a single and easy-to-analyze hierarchical organization of a dataset. Our main motivation comes from the observation that, in some cases, using one single parameter value is not enough to find all the cluster structures in the data. TO BE CONT’D

Modeling Mentorship

I will be working with Associate Professor Dr. Sasha Dall from Exeter University, who is a well-known Mathematical Ecologist. He and his lab are using game theory modeling to describe evolutionary outcomes.
Although I often interact with mathematicians and economist at the U of C, I have been missing direct interactions with specialists in my field of study (behavioural ecology modeling), A couple of months in Exeter with Dr. Dall, would be very beneficial for my professional development and my training as a modeler. I have been working on my own evolutionary game theory model and it would help to have inputs on topics such as approaches to optimality and game theory modeling and when a model is completed. TO BE CONT’D

The EU in contemporary global environmental governance: a complementary outside-in and inside-out approach

The research conducted in Montreal focuses on studying the role of the European Union (EU) in the Convention on Biological Diversity (CBD) through an innovative outside-in mapping. Three dimensions of the EU’s role are examined: its environmental ambition, leadership and diplomatic activity. The project is innovative because of a twofold reason. First, counterbalancing the literature’s dominant focus on climate change, it focuses on the EU’s role in less politicized, yet important, international environmental treaty regimes. Second, the project evaluates the EU’s role based on non-EU centric evaluations by observers of the EU’s role, i.e. the outside-in approach. Original empirical data is collected through interviews with officials working at the secretariats of the Convention on Biological Diversity who witnessed the EU’s role. TO BE CONT’D

Analyse et mise en place d’un processus de gestion et d’optimisation de campagnes publicitaires sur les médias sociaux dans le cadre de petites moyennes entreprises

Le projet consiste à optimiser les pratiques de gestion de la publicité sur les médias sociaux (SMM) pour plusieurs clients de l’agence de Marketing Numérique Click & Mortar. Le SMM inclut plusieurs pratiques d’optimisation de la présence sur les réseaux sociaux tels que Facebook ou Instagram. Les algorithmes sophistiqués utilisés pour filtrer le contenu publié sur les réseaux sociaux oblige de plus en plus les entreprises à se tourner vers les placements publicitaires. Ceux-ci permettent aux entreprises de bénéficier d’une plus grande portée et d’un ciblage plus précis. La valeur ajoutée d’une plus grande portée est la notoriété de la publicité qui va ensuite influencer les utilisateurs à interagir avec la marque et augmenter les bénéfices d’un client. TO BE CONT’D

Development and application of physiological markers of Grizzly Bear health

Grizzly bears reside on changing landscapes across Alberta, Canada. The goal of this study is to determine how disturbances in the landscape affect the health of grizzly bears. This will be monitored by analyzing the (1) expression of proteins in skin that are associated with energetics, reproduction, and stress and (2) concentrations of hormones in hair that are associated with reproductive status and long-term stress. In collaboration with the Foothills Research Institute (FRI), skin and hair samples will be collected from free-ranging grizzly bears in Alberta, Canada. Laboratory techniques have been developed at the University of Saskatchewan (UofS) to isolate protein from skin biopsies and measure hormone concentrations in hair. FRI’s expert knowledge of landscape changes and bear behavior will be combined with the physiological assessments by UofS to create a tool to detect compromised health in individuals and identify drivers of stress in threatened species managed by FRI.

Quality and degradation assessments of polymer-lined thrust bearings by indentation and tribological testing

Current needs for renewable and emission-free technologies imposes hydroelectric power plants to generate power in a predictable and reliable fashion. Replacing metallic to polymeric coatings in thrust bearings allows hydroelectric turbines to operate at a wider range of operation parameters. However, the sensibility of polymeric materials to the manufacturing method imposes important uncertainties on the performance and longevity these materials can have in service conditions. In this project lab-bench tests will be used to critically evaluate the results of portable non-destructive tools that can be used to assess the quality of polymeric coatings used in thrust bearings. High-pressure and high-temperature immersion tests will force the material into an accelerated aging process. The effects of aging on the polymer performance will be tested into an environment simulating the turbine operation conditions. The research outcomes will enable Hydro-Québec to determine whether a polymer lining is suitable for continuous operation or not.