Innovative Projects Realized

Interaction Concepts for Remote Robot Exploration in Crisis Scenarios using Virtual Reality

Building Information Modeling (BIM) for Energy-Efficient Building Operations

Internship at the University of Münster in a research project on intentional forgetting and trust

Optical characterization of flexible neural implants

Internship “Nutrition and Microbiota”

Using Cryo-EM to Determine Macromolecular Complexes

QDoc – Online Medical Platform

QDOC designs and builds cutting edge medical software. Our premier product connects patients seeking either immediate or appointment-based encounters with Canadian licensed Physicians.
Building on the rideshare model of matching clients with transportation, QDOC implements custom algorithms, along with secure PHIA/HIPAA compliant technology to create a seamless, streamlined experience for both patient and physician.
By allowing QDOC physicians to work anywhere, anytime, leveraging NLP and AI we can create a seamless on demand offering for patient visits. We provide advanced tools to document the patient encounter, follow up on tests, and order prescriptions all from within the application.
Our system can be used by patients who require a physician immediately, as well as providing a central portal to allow for referrals to specialists, and other medical professionals that might be part of a comprehensive patient care approach.

Evaluation of LTD 3.0 Framework Adoption and Implementation

The Long-Term Development (LTD) 3.0 framework and its previous versions have been distributed by Sport Canada to national sport organizations since 2005 to improve participation and physical activity levels across the country, although the LTD’s acceptance and rollout has not been evaluated. Therefore, the purpose of this study will be to speak with national and provincial/territorial sport organization directors and community leaders as well as review relevant documents (e.g., athlete development policies) to understand how each side has put the framework into action and how it has impacted their members, funding, and international medal success. Our partner organization, Sport for Life, will benefit from this study by gaining a greater understanding of where sport organizations from the national to local level stand on the framework and how future versions can be changed to better serve these communities.

Speculative Sensory Interfaces: Opening a dialogue between differently-abled bodies through sensory interventions

This project will use speculative design methodologies to create wearable technologies (wearables mounted with sensors that can be worn), capable of sending, receiving, and sharing sensory information across differently-abled human bodies. As the participants with different body structures, mobility, and agility move in space wearing aforementioned wearable technologies, proprioceptive information (sense of balance and body gestures) from one participant’s body will be strategically mapped using machine learning algorithms to tactile senses (such as pressure on the skin through shape changing interfaces) – acting as a stimulus on another person’s body. Overall, the aim of this project is to question the normative perception of sensory-motor disability (often seen as a impairment in the body) through a confusing and playful bi-directional flow of sensory information across differently-challenged human bodies.

AI model building accelerator

The candidate will be working with Modellicity to participating in the development and bringing-to-market of the company’s proprietary end-to-end AI model building platform that will enable users to quickly build, validate, and deploy AI models.

Vision-based 3D object localization for manufacturing applications

The industrial scale manufacturing automation largely works because of robotic systems which are preprogrammed to reliably carry out the same sequence of steps over and over again. As a result, when scenarios change, or become more complex, robotic systems need to be re-programmed. Moreover, in high value added manufacturing applications, it is impractical to program every single motion of a robot manually. The project aims to develop fully autonomous robotic manufacturing and inspection systems that do not require extensive programming by end-users. In particular, a key step in automation of manufacturing is the ability to accurately detect and localize parts so that a robot gripper can accordingly adjust. This project will capitalize on recent developments in modern AI to develop automated methods for accurate localization of objects through images captured by a camera.

Assessing the suitability of Kernza® as a dual-purpose crop for Atlantic Canadian agriculture and climate action plans

With very few of the plant species used in agriculture supplying 90% of global food production, this lack of diversity exposes vulnerability to changes in climate (Kang and Banga, 2013; Labeyrie et al, 2021). Recent recognition has been given to perennial plants for agricultural use because of their resilience to dynamic conditions and contribution to ecosystem services (Sanford et al, 2021; Zhang et al, 2011). In comparison to annuals, perennials provide more continual ground cover, reduced soil disturbance, and have been suggested to require fewer synthetic inputs that are linked to negative environmental impacts (Crews et al, 2018; Pimentel et al, 2012). This project will assess the suitability of a novel perennial wheat, Kernza®, as a crop in Atlantic Canada by utilizing diversified research test plots, field trials, and developing applicable crop rotations. Identifying a perennial crop for local agriculture has the potential to significantly impact industry climate action plans.