Group and individual problem-solving play important roles in industrial innovation, product development, strategy formulation, and many other applications. Prof. Duimering’s lab at the University of Waterloo has conducted experiments investigating the behaviour of individuals and groups solving problems under various conditions. Studies have investigated the effects of problem complexity, individual vs. group incentives, and the […]

The proposed project aims to advance computational neuroscience by enhancing the MouseNet model, a Convolutional Neural Network (CNN) designed to emulate the structure and function of the mouse visual cortex. By incorporating 3D convolutions and realistic temporal dynamics, the project seeks to model the lateral geniculate nucleus (LGN) dynamics more accurately. This enhancement will provide […]

The project aims to enhance our understanding and ability to predict the dynamics of cognitive and sensorimotor functions in skilled behaviors. Through the integration of non-invasive brain stimulation (like TMS) and machine learning algorithms, this research seeks to develop models that can foresee cognitive-sensorimotor interaction outcomes both in individuals with neurological conditions and healthy subjects. […]

This project focuses on creating interdisciplinary educational program within the energy field. The goal is to address the challenge of engineers struggling to collaborate effectively with colleagues from different backgrounds – both within and outside of engineering. By integrating energy principles with business, political, and environmental considerations, this project aims to equip future engineers with […]

QiiQ Healthcare is building solutions to positively impact the speed, efficiency, and efficacy of clinical workflow – starting in the emergency department. This pursuit requires rapid innovation cycles that respect the constraints of regulatory compliance. This places an unfair disadvantage on small vendors who do not have large compliance and IP teams. As a small […]

The objective of the “rTMS for post-covid-19 condition: A sham-controlled case series involving iTBS-300 and iTBS-600” project is to determine the efficacy, feasibility, and tolerability of several iTBS variants (iTBS-300, iTBS-600) and sham stimulation in PCC patients. Secondarily, the aim is to examine signs of improvement in cognitive, affective, and functional symptoms following each iTBS […]

Feeling belonging is important for all people, including children. Many organizations want to help children feel they belonging in their communities and the programs they attend (such as recreation or education programs). But to do this, organizations need a way to measure belonging and see how it changes over time. This project addresses this need […]

Transforming Architecture: Pluripotent and Quasigeostrophic Space is an interdisciplinary research program investigating new materials, tools, methods and frameworks in the field of living responsive architecture, an emerging sub-discipline of architecture that focuses on how buildings respond to their occupants. Part of that work involves creating and disseminating kits and publications to help individuals access and […]

This project “Multimodal RAG Explainability (MRAGE)” aims to develop an interactive tool for explaining Large Multimodal Models (LMMs) augmented with retrieval capabilities. LMMs represent a significant advancement in AI, capable of understanding and generating content across multiple modalities like text and images. By employing the retrieval-augmented generation (RAG) methodology, this project queries external knowledge sources […]

It is shown that the rapid administration of treatment in acute stroke patients improves clinical outcomes. In particular, the time it takes to administer treatment once the patient has arrived at the Emergency Department with stroke symptoms is called Door to Needle Time (DTN). The median DTN time at the Grand River Hospital (GRH) currently […]

This project aims to develop a method for delivering reprogramming transcription factor genes to astrocytes in the central nervous system using Intelligent Phagemid-Assembled Gene Expression (iPhAGE) technology. By constructing specific gene blocks and fusion helper plasmids, synthesizing iPhAGE DNA, and purifying iPhAGE preparations, the project seeks to enhance transfection efficiency and assess immune responses and […]

The project “Developing Data Strategies to Enable Healthcare Machine Learning” aims to develop effective strategies to collect, curate, and maintain data in healthcare. A data strategy which enables Artificial Intelligence (AI)/Machine Learning (ML) models plays a pivotal role in building response healthcare solutions. The project is focused on understanding the fairness aspects of care quality […]