Learning Generative Models of Images and Patterns

This Project is an continuation of our SIGGRAPH Asia 2017 paper on “Learning to Group Graphical Patterns”. The paper introduced a novel deep learning approach for grouping discrete patterns common in graphical designs. The approach was based on a convolutional neural network architecture that learns a grouping measure defined over a pair of pattern elements. […]

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Metabolic networks and applications to M. tuberculosis

The project involves the modeling of the metabolism of TB. I developed an algorithmic pipeline called MetaMerge, which allowed me to reconcile differences in format, nomenclature, and annotation, between two models of TB metabolism. MONGOOSE, another doctoral project of mine, is a tool for analyzing metabolic network models in exact arithmetic, resulting in consistent, reproducible […]

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Extending and Deploying the Social CheatSheet Plugin

This project will expose the intern to key design, implementation, and evaluation research activities in human-computer interaction (HCI). We have recently started exploring the concept of social curation of software help content by developing a novel web-based platform, Social CheatSheet, that overlays relevant community-curated instructions and multi-step tutorials atop any web application and offers an […]

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A novel cost-effective skin-tone detector for consumer devices

Skin-tone detection has received considerable attention in recent years and applied in wide range of image processing and computer vision applications. The objective of this research project is to develop a real-time skin-tone detection solution optimized for consumer devices, allows for a deliverance of high detection performance at minimal computational costs. The proposed solution will […]

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Mobile Transaction Initialization, Authentication and Cooperation

The intern and organizational partner are looking for unique and interesting ways of using mobile devices to help authenticate users and methods of cooperation between a mobile device and another device, a PC for example. The intern will research and implement different authentication techniques on mobile devices. Additionally, it is prudent to study and develop […]

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Regression Models for Credit Card Strategies

ATB Financial is a large Alberta based full service financial institution. The Card Services department was formed 5 years ago and is growing rapidly. The Card Strategy team within Card Services is developing models and processes to manage marketing campaigns, credit risk management, collections and fraud effectively. The intern will support the team by providing […]

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Machine Learning for categorizing women’s health risks

This research project deals with categorizing women belonging to different developing countries into different health risk segments and sub segments and subsequently analyze patterns of diseases/infections in various geographical regions accordingly by using Optimized machine learning approach. XgBoost algorithm would be implemented to achieve this goal among other existing algorithms as this offers better model […]

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Modeling foreign exchange

The proposed project addresses the main challenge in modeling long-dated (maturities of 30 years or more) foreign exchange (FX) interest rate (IR) hybrid derivatives, namely the strong sensitivity of the products to the skew of the FX volatility smiles via the use of a stochastic process, such as the Heston model. Numerical methods based on […]

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Securitized Tokens as a Service (STaaS)

This research study aims to investigate the potential and performance of a novel Securitized Tokens as a Service platform. Blockchain is the distributed ledger of verified transactions, and smart contract is the programmable part of the blockchain which can automate more complex transactions. We can define the tokens on top of the blockchain platform; and […]

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Investigating the effect of a novel regularization technique for neural networks

Despite the fact that neural networks have been widely applied in practice, training such networks can suffer from slow convergence, poor local minima and some other difficulties such as catastrophic forgetting. Such shortcomings severely undermine the applicability and usefulness of neural networks. The objective of this project is to identify the reasons behind such difficulties […]

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