Prediction of preterm birth in twin pregnancies using machine learning

Preterm birth (PTB) is the leading cause of death in twin pregnancies. A variety of parameters, such as cervical length, maternal medical history, demographics, and obstetric characteristics all have been shown to affect the risk of PTB. However, the relationship is not obvious. Early prediction of PTB in these pregnancies can assist physicians in identifying those patients who may benefit from preventive interventions and closer monitoring. This project aims to use machine learning to create an algorithm that predicts which twin pregnancy is at a risk of PTB.

Developing the design system for a new generation of Green Fan Abradable Materials

The abradable rub strip (ARS) material’s main function is to minimize the clearance between blade tips and the fan case, thereby increasing the overall engine efficiency. Under tensile and compressive loading, the abradable material behaves different, and has a significant post-failure compaction under compressive loading. Therefore, its characterization is complex and requires a wide range of testing. The intern will help develop the test plan for standard and non-standard mechanical tests per standards.

Identifying local factors and sources affecting stream chloride concentrations in the Toronto Region

The proposed research will identify the dominant drivers of rising chloride concentrations in streams within the Toronto and Region Conservation Authority (TRCA) jurisdiction. The TRCA monitors stream water quality at 47 stations and data suggest that chloride concentrations are increasing. Previous research has identified urban growth and the subsequent application of road salt in wintertime as a dominant driver of these trends.

Cancer treatment using drug-loaded thermosensitive liposomes with non-invasive ultrasound thermal therapy and temperature monitoring and control in an in vivo animal model

Chemotherapy is the most commonly used method for treating different cancer types that involves the delivery of chemotherapeutic drugs, leading to the death of cancer cells. However, the non-uniform distribution of chemotherapeutic drugs within the tumor and systemic toxicity has multiple side effects, and the delivery problem remains unsolved. Drug delivery carriers such as liposomes are used to deliver the drug to the targeted regions. To this end, a controlled and reliable release of the loaded chemotherapeutic drugs from a liposome core has remained a problem to overcome.

Development of a tele-health rehabilitation system to provide automatic assessment of patients’ performance, improve patients’ adherence and enable remote rehabilitation-(market and competitor analysis, regulatory & software design)

Poor physical recovery, especially in remote rehabilitation, is the problem that will be addressed in this project.This project is Phase I of development of Fun-exercise module. Fun-exercise system uses gamification to boost patients’ adherence to their prescribed home-exercises. To achieve this goal, Fun-exercise will use mentally stimulating and customizable games paired with a set of wearable sensors to provide feedback to ensure activities are being done correctly. In phase I, patient study and conceptual design of the Fun-exercise module will be undertaken.

Novel Artificial Intelligence (AI) driven wearable device for continuous vital sign monitoring

Wearable medical devices (SWDs) are emerging as powerful patient monitoring and data collections tools. These smart, multiplexed devices allow us to quantify dynamic biological signals in real time through highly sensitive and miniaturized biosensors. SWDs can enable monitoring at risk patients at home, diagnosing early disease progression, and reducing healthcare expenditures by means of prediction and prevention of disease.

Multi-sensor fusion for continuous vitals monitoring, sleep characterization and fall detection

The proposed research project focuses on multi-sensor such as heart rate, body temperature, oxygen saturation level, and inertial sensor data-based sleep stage classification, and tremor detection in real-time for preventive health devices. The goal of the proposed research is to build robust and energy-efficient machine learning and deep learning-based approaches that extract and analyze the significant information from the multisensor data coming from wrist-based health devices to help Parkinson's patients with tremors and an individual with sleep quality tracking.

Waste Heat Recovery from Container Farm on Greenhouse

The aim of the proposed project is to analyze and develop a conceptual design of a greenhouse that’ll be able to repurpose the waste heat expelled from Growcer’s container farms. As there is a lot of research on related topics such as hydroponic container farming and greenhouse farming, there is still a lack of research conducted on merging the two systems into one.

Long Duration Flight Using Wireless Power Transmission and Solar Power

The proposed research project will demonstrate the feasibility to fly a small uninhabited aircraft for very long, multiday missions by providing it with power using a mix of wireless power transmission and solar-power. The wireless power transmission will be sent as a directed microwave beam from a ground-based transmitter and received using rectennas that are attached to the lower surface of the aircraft wing. Solar-cells on the upper wing surface and batteries will complement the power needs.

A Social Tool for Depolarizing Science Communication

A study found that “Science Curiosity” might make us less polarized. When we’re polarized, ideas that feel threatening to our group turn on the fear centers in our brains. The more afraid we are, the more polarized we become. For some reason though, fear doesn’t seem to affect curious people nearly as much. One reason might be that curious people are more playful. Play probably evolved so we could learn to explore dangerous places (and ideas) safely by helping us see threats the same way we see challenges in a game.