Improving road safety has a direct impact on the lives of drivers as well as the costs incurred by companies operating commercial vehicles. One important aspect of road safety is timely and effective vehicle maintenance. By forecasting vehicle maintenance needs and predicting breakdowns before they occur, valuable insights can be provided to drivers and fleet […]

Many real life decision consider a multitude of criteria, one such example is in healthcare where the patient’s condition, available resources, chance of recovery, cost etc all need to be consider when administrating care. An analytic hierarchy process makes the multi-criteria decisions by first converting the problem into a set of mathematical constraints by pair-wise […]

Machine Learning (ML) approaches generally consist of training an algorithm on a given dataset containing data which has to be analyzed or otherwise understood. For an ML application to be successful, careful thought must be given to ensuring that the architecture of the algorithm chosen is fit for the task at hand: some architectures are […]

Japan is a leading example of a nation with a rapidly ageing society and currently consists of the highest proportion of elderly adults worldwide. Among others, this has led to a series of downstream concerns, including labour shortage issues and reduced ability of working individuals to finance those who are retired. As one of the […]

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 […]

Road safety affects everyone, not just Geotab customers. With several years of driving and environmental data from over 2 million connected vehicles we have an opportunity to make our customers safer, as well as our communities and cities. In an effort to reduce accidents, we need to understand both the driving behavioural patterns that are […]

This research project aims to develop a robot pick and place model that can be used in Kindred AI’s robotic arms to improve efficiency and reduce production costs. The intern will work closely with the partner organization’s experts in computer vision and MLOp to design and build new models, modify existing ones, and experiment with […]

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 […]