Clinical Pilot Evaluation & Commercial Launch of ARISE: augmented reality training for chronic neck pain

ARISE is an augmented reality, AI-enabled therapy platform developed by Neuro-Mod to improve chronic neck pain care through engaging, mechanism-informed exercises delivered via lightweight AR glasses and a smartphone. This project combines two goals: (1) clinical pilot evaluation and product refinement, and (2) market launch preparation. During the internship, ARISE will be implemented across up […]

Read More
ESROP – Osaka Summer 2026

This summer project supports a research exchange between Engineering Science programs at Osaka University and the University of Toronto by creating a shared foundation for future biomedical engineering collaboration. At a high level, the project focuses on how modern engineering can better connect advanced measurement technologies with real medical needs—turning complex biomedical signals into knowledge […]

Read More
ESROP Physics-Informed Neural Network Engine for Perovskite Solar Cells

Perovskite solar cells are a promising new solar technology that could enable cheaper and more efficient renewable energy. However, their performance can vary widely because even small changes during manufacturing can strongly affect how well the devices work. This project uses advanced artificial intelligence techniques, combined with known physical principles, to analyze a large collection […]

Read More
Coherent Elastic Neutrino-Nucleus Scattering Measurement with the Ricochet Experiment

This Mitacs Globalink Project will place a University of Toronto undergraduate physics student at the experimental site of a high-flux reactor-based neutrino experiment called RICOCHET in Grenoble, France. The intern will be hosted at Université Grenoble Alpes and will work closely with the local research team to support experiment operations and to develop a quantitative […]

Read More
ESROP – Time-Series Data Modelling and Analysis with a Focus on Pattern Analysis

The research addresses the fundamental trade-off in financial econometrics between computational efficiency and predictive accuracy under varying market conditions. While existing literature has established hybrid models with high predictive capabilities, these often incur high computational costs that may not be necessary during stable market regimes. Conversely, traditional regime-switching models like the MS-GARCH utilize a Markov […]

Read More
Optical Polarization Observations of Blazars and Tidal Disruption Events

This project aims to understand the processes of accretion disk and jet formation around supermassive black hole systems. It will be performed within the Black hOle Optical-polarization TimE-domain Survey (BOOTES, https://www.ia.forth.gr/index.php/project/1055), designed to study the polarized light coming from persistent and transient black hole systems called blazars and Tidal Disruption Events (TDEs), respectively. Within the […]

Read More
ESROP – Physics-Informed Neural Network Engine for Perovskite Solar Cells

Perovskite solar cells are a promising next-generation energy technology, yet their widespread commercial adoption is hindered by extreme sensitivity to manufacturing conditions, leading to unpredictable performance. This project aims to overcome this reliability challenge by developing a “smart” predictive engine that integrates artificial intelligence with fundamental physics. By leveraging a massive dataset of nearly 500,000 […]

Read More
ESROP – Exploring Metallization of Tandem Solar Cells through Machine Learning and Simulations

Tandem solar cells represent the future of renewable solar energy, offering efficiencies beyond traditional single-junction silicon cells. However, their current commercial viability is limited by their metallization pattern, which is the silver contacts on the surface that collect electricity. Current design processes are manual and computationally expensive; therefore, this project aims to integrate machine learning […]

Read More
ESI Imaging Novel Breast Cancer Screening Data Driven Research Study

ESI’s current focus is product research and development (R&D), and commercialization activities. The R&D pipeline furthers the technology (hardware, software), systems, and collects/analyzes the data required to ensure device operations and regulatory compliance. Device R&D will refine and miniaturize the metasurface, enhance antennae, and complete software integration (signal and image processing, hardware integration, AI-driven decision-making). […]

Read More
Vehicle Mounted Remora Edge Sensor Platform Building the Urban Nervous System

Livesens is building the Urban Nervous System: a vehicle-mounted sensing layer that turns everyday fleet movement into real-time street visibility. As vehicles drive their normal routes, we capture basic mobility signals (where movement slows, where stops cluster, how travel time changes by time of day) and convert them into clear corridor outputs like travel time […]

Read More