The research project aims to develop a portable, wireless interface for implantable medical devices that monitor brain activity in patients with conditions such as epilepsy and motor disorders. This new software will allow for continuous, unrestricted measurement of brain activity, enabling doctors to collect high-quality data in patients’ natural environments. The interface will wirelessly transmit […]

Continuous integration (CI) and continuous delivery (CD) are practices that help software development teams deliver code changes more often and with fewer issues. To ensure that code changes are working as they should, developers use Behavior Driven Development (BDD) tests. But running all these tests against every code change can be time-consuming and costly. This […]

The proposed research project will focus on analyzing and optimizing the cloud infrastructure used by SOTI to manage mobile devices globally. The intern will analyze the current cloud architecture and hosting costs, identify areas for improvement, and propose and implement optimizations to reduce system requirements and minimize costs. The expected benefit to SOTI is a […]

Mobile devices have become a crucial tool for businesses, and SOTI MobiControl is a leading mobile device management solution that provides remote control capabilities. However, to ensure proper product functionality and scalability of SOTI MobiControl, the company is looking to research the simulation of remote controlling a mobile device for automation testing. By testing the […]

The proposed project seeks to develop a Machine Learning-based software solution that accurately measures the capacity, State of Health (SoH), State of Charge (SoC), and cycle count of non-smart batteries utilized in mobile fleets. The project’s primary objective is to bridge the gap between smart and non-smart batteries by monitoring non-smart battery capacity and other […]

The goal is to develop a system that can rapidly detect and report emerging disease outbreaks worldwide by analyzing clusters of news articles using Large Language Models. The objective is to create an efficient and effective way of identifying “disease events” that can alert public health officials to take prompt action.

Streaming Cameras have become ubiquitous in the urban and industrial landscape. This research project aims to improve the AI-based action recognition capability of consumer-class home camera streams, which often have limited bandwidth and degraded video quality. The project proposes to develop a network-aware, video-action recognition AI pipeline that pushes key operations of traditional action recognition […]

Layer 6 powers the AI use cases for a variety of banking and financial applications at TD Bank. The goal of the research project is to improve the AI engine by having the training more efficient and distributed among a variety of clusters. The AI engine will allow models to be trained faster and with […]

Facial landmark detection is a computer vision problem where the goal is to predict the location of specific points on a face, like the eyes, nose, and mouth. This is useful for things like facial recognition and 3D modeling. To train a model to do this, we need a lot of images with those points […]

High-fidelity 3D face reconstruction from monocular images aims to obtain a 3D representation of the subject from a single or multiple input image. Recently, self-supervised deep-based methods have demonstrated impressive performance in 3D face reconstruction. These methods are efficient and produce plausible face reconstruction. However, for AAA production (games and movies), they do not yet […]

Geotab‘s dash cams deliver a clear and complete picture of harsh driving events and provide crucial video evidence in the case of collisions and insurance disputes. It is essential to ensure the dashcams work well and capture high quality footage. The object of this project is to automatically detect dash cam installation faulty and monitor […]

SpassMed’s ShockRanger is a primary product that utilizes vital signs from patient monitors to provide healthcare providers with meaningful signals for clinical decision-making. SpassMed is seeking one or more methods that can accurately forecast shocks, particularly Septic shock, among patients in ICUs. In addition, SpassMed aims to develop models for effectively classifying patients into their […]