The Empathetic Spaces Partnership is an interdisciplinary research program investigating new materials, tools, methods and frameworks in the field of living responsive architecture, a new sub-discipline of architecture that focuses on how buildings respond to their occupants. The proposed research project supports this by having the intern document and be involved in developing concepts, tools […]

The project consist of an exploration of molecules simulation with the help of high power computation and quantum computer. Specifically for this project, one of the following will be simulated: CO2, CH4, H2, N2, and O2 or small organic molecules or Metal-Organic Frameworks

The proposed research project aims to develop a method for estimating sound speed profiles in underwater environments. By utilizing pulse-echo acoustic techniques, we can accurately determine the sound speed, which is crucial for various applications such as ocean acoustic studies. The expected benefits to our partner organization include improved underwater acoustic measurements, enhanced mapping of […]

CT angiograms (CTA) are used to detect vessel occlusions in the brain in stroke patients and are a diagnostic criteria of acute stroke. Current standards of care require that an additional CT perfusion scan to be taken in order to accurately locate large and medium-vessel occlusions, allowing for the administering of endovascular therapy (EVT) to […]

The proposed research project will assess the efficacy and effectiveness of a generalized Sports Vision Training (SVT) program on varsity athletes through comparing the effects of a 10-week program to a 5-week program. The SVT program consists of training methods aimed at improving visual perception and efficiency of visual processing. Varsity athletes of hockey, basketball, […]

Vaccines are essential in protecting individuals from infectious diseases by preparing their immune systems to recognize and combat pathogens. The tremendous impact of vaccines on public health cannot be emphasized enough, as they have saved countless lives since their inception. However, the adaptability of viruses and other infectious agents has necessitated the development of new […]

La maladie corticale du hêtre les arbres matures en diminuant graduellement leur vigueur. La mort de ces arbres favorise un afflux de lumière qui contribue à accentuer l’envahissement par les gaules de hêtre (EGH). Cet envahissement est problématique puisque le hêtre n’est pas une essence prisée par l’industrie et il interfère avec la régénération d’autres […]

The Intern will do research to identify possible existing and new gases to replace harmful gases used in refrigeration, automotive air conditioning and other similar industrial and consumer uses that are known to deplete the ozone layer or are ‘super-greenhouse gases’. Through literature searches and primary interviews with manufacturers, the student will prepare an analysis […]

In this project, Dr. Fung and her students will work with Trustcore Technology to design and develop anomaly detection functions in the trusted execution environment (TEE) of Internet of Things devices. The goal is to provide a robust solution to detect malfunctions and/or intrusions in IoT systems. The project is divided into two parts. Part […]

This research project aims to address the challenge of improving customer experience and satisfaction by providing quick, accurate, and efficient answers to their questions about Avid products and services. Avid’s extensive knowledge base (KB) serves as a valuable resource for customers; however, finding relevant information can be time-consuming and challenging. The proposed AI-powered virtual assistant […]

Triumvira, a Canadian-US post series A biotech company, is working on development of new targeted cancer therapies. Our core technology is focused on the genetic engineering of immune cells isolated from patients. This process then enables these engineered immune cells to recognise cancer cells that otherwise are invisible to the immune system. These therapies are […]

The goal of this project is to develop a machine learning tool based on quadratic neural networks to perform automated telemetry analysis and detection of known anomalies faster than the current state-of-the-art, and to produce indicators to possible new and unknown anomalies in satellite data.