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 […]

During the internship, the selected candidate will focus on developing edge computing solutions that can recognize and alert the relevant personnel in real-time in case of potential security threats (e.g. theft, robbery) and safety issues (e.g. employee accidental falls). This would help retailers to prevent or respond quickly to incidents, reducing losses and improving safety […]

This research project, backed by Unity Health Toronto and the Centre for Global Health Research (CGHR), aims to explore the use of machine learning in predicting causes of death using verbal autopsy data from low-to-middle-income countries. Verbal autopsy is a cost-effective and efficient method for documenting deaths in regions with limited resources. By employing advanced […]

Robotic manipulation involving contact-rich tasks continues to be a challenging, yet critically important, research problem with many potential applications, including domestic assistance, automated agriculture, and advanced manufacturing. Many of these tasks involve both unstructured environments and complicated dexterous manipulation. Existing approaches that rely on purely visual sensors and predefined models are brittle and prone to […]

The proposed research project aims to develop a machine learning model that can draft preliminary radiology reports for x-rays. The project will use a large language model based on transformer neural networks to analyze x-rays and generate reports that are personalized to the reporting radiologist and based on the patient’s x-ray images. The goal is […]

Brain tumors are the leading cause of cancer-related death in childhood and are generally categorized as low-grade or high-grade. More granularly however, there can be over 100 types of brain tumors which can vary widely in both prognosis and treatment. Machine learning has increasingly been applied to classify brain tumors and other cancer types but […]

Picard-Lefchetz theory is a powerful tool for evaluating highly oscillatory integrals that are difficult or impossible to solve using other integration methods. This theory has numerous applications to lensing, quantum mechanics, and high energy physics. In this project, I will investigate using Picad-Lefchetz theory to solve simple lensing problems with the goal of applying these […]

We focus on building the systems that allow for the storage and analysis of big data for preventing cybersecurity attacks. This telemetry data is collected from customers by leveraging endpoint, network, and cloud data sources both inside and outside our customers’ networks. Our team then builds products that allows our customers as well as our […]

Thin-film polymer substrate that have piezoelectric layers are promising for a variety of applications, including micro-electro-mechanical systems, mechanical energy harvesting, and flexible electronics with security features. This study proposes a detailed approach for understanding how these flexible structures behave under different mechanical loads, using a comprehensive experimentation. This research mainly focuses on characterizing the electromechanical […]

Biomedical research, particularly preclinical research, is a complex and challenging field with a high failure rate of 98% in pharmaceutical research investment. Extracting relevant information from preclinical research papers involves synthesizing information from various sources, which is a demanding task that requires domain-specific knowledge. Natural language processing, specifically Large Language Models (LLMs), has demonstrated tremendous […]

The ability to quickly check if robot poses are not in collision with environment geometry is critical for robot applications that rely on forward kinematics, inverse kinematics, and path planning. It has been shown that during path planning 99% of the time is spent performing collision checks between the robot & its environment. Improving collision […]

Resistance exercise training and the provision of dietary protein is known to bring about beneficial adaptations for muscle mass and strength. Substantial research has been conducted to identify the optimal protein supplements that permit the greatest anabolic response following an exercise stimulus. This research project will examine if a novel protein supplement can increase anabolism […]