Mining Event Tracing for Windows (ETW)

As cyber adversaries are becoming more creative, analysts are required to figure out more innovative ways to detect them to be able to respond before it’s too late. To detect any underlying threat inside a system, data logs are collected showing events and activities occurring inside the system. Adversaries nowadays are capable of evading detection […]

Read More
Out of Distribution Detection in Deep Generative Models

As generative models become increasingly prominent in machine learning, the need for accurately detecting out-of-distribution data has become crucial. The primary objective of this research is to develop an approach that can identify when the program encounters data that is vastly different from what it was trained on. In machine learning, programs may make errors […]

Read More
Feature Search using Automatic Machine Learning

This research project focuses on developing an automated system to search and analyze time-series tabular features in the financial institution’s machine learning pipeline. The goal is to identify relevant features and improve efficiency in the decision-making process. The project will begin by prototyping a system to support automated feature search patterns and researching feature search […]

Read More
Adapting Not-for-Profit Arts Publishing to the Post-Digital Paradigm

PUBLIC (est. 1988) is a not-for-profit print periodical exploring the intersection of art, design, technology, and culture. This research project advances that history by looking at the future of print culture as today’s artists are increasingly making and exhibiting work in online spaces. How can PUBLIC promote engaging and accessible conversations around artists working exclusively […]

Read More
Exploring an interactive multisensory physical movements model during and beyond COVID-19: a case study of children with special needs

The COVID-19 pandemic has forced children to quickly adapt to home-based or virtual learning; however, a number of researchers have identified challenges and difficulties with applying and using technology. More importantly, there has been a significant rise in the rates of mental illness occurring as a result of COVID-19 and children are now experiencing increased […]

Read More
Two-step personalized federated learning algorithm in reality

Machine learning attempts to model high-level abstractions in data using multiple processing layers with complex structures or non-linear transformations. Federated learning is a distributed machine learning approach that allows multiple parties to collaborate on training while preserving user data privacy. However, the data from each party is typically non-independent and identically distributed (Non-IID), which can […]

Read More
Determing the value of delivering light >500nm to dental resins

A new curing light, PinkWave (Apex, Racine, WI) was introduced last year (https://vistaapex.com/pinkwave). This light is unique because it has four distinct wavelength bands that deliver red (625 – 750 nm), infrared (800 – 900 nm), blue, and violet light. The manufacturer also claims that this ‘quad-wave’ light can reduce polymerization shrinkage stress.[13] Initial reports […]

Read More
Object Tracking for High-Speed Pick-and-Place Robot

The demand for eCommerce and online orders has risen rapidly in recent years, this drives the need for highly efficient and automated item sortation systems. Kindred AI is a technology company with the objective to bring artificial intelligence and robotic technologies into the workforce of eCommerce, parcel and order fulfillment. As a part of the […]

Read More
Representation Learning with Time Series Data

The proposed research aims at learning better representations for multivariate time series (MTS) data, which can be applied to various important real-life applications such as weather, traffic, and electricity forecasting. Better forecasting accuracies for these tasks could help with efficient risk aversion and decision making, and save costs for decision makers. The proposed research will […]

Read More
Novel imaging approaches to understand heart function

The most common sustained cardiac arrhythmia is atrial fibrillation (AF), affecting 2-3% of the general population. If left untreated, arrhythmias can lead to heart failure, stroke, or sudden death. A better understanding of AF mechanisms is needed to improve our understanding of disease pathogenesis and create new therapeutic tools. We have developed a zebrafish model […]

Read More
Wearable Digital Technology for Continuous Monitoring of Vital Signs – part A

SFU will be collaborating with partners of a supercluster on the Continuous Connected Patient Care (CCPC) Platform, which is being developed to provide safe, responsive, and high-quality outpatient care at home. We will be working directly with our partner, Medtronic Canada. SFU’s will focus on the research, development, and testing of medical grade wearable sensor […]

Read More
Norsat International Inc. – Supply Chain Intern – Huong and Chidinma

Founded in 1977, Norsat International is a leading provider of innovative communication solutions that enable the transmission of data, audio and video for remote and challenging applications. Our products and services include customizable satellite components, portable satellite terminals, maritime solutions and satellite networks. Norsat International is consistently ranked among the top technology companies in Canada […]

Read More