There will be significant investment in providing the intern with a strong foundation to make an impact across a couple different areas of the company during this internship. This will include job shadowing of the Client Partner during service delivery tasks, inclusion on company tieger teams, and participation in weekly team meetings. Once the intern […]

FirstHx wishes to validate the French component of its’ in-person patient facing digital medical interview solution, which could be offered to clinicians and practitioners as a means of empowering patients, reducing time of clinical documentation, improve efficiency while increasing quality of care. Researchers from the UMoncton have the expertise and resources to validate our AI […]

In agriculture, header losses, indicating the loss of grains at the combine harvester’s header, usually contribute the most of harvesting losses. While not entirely avoidable, their impact can be significantly reduced through careful monitoring of the harvesting process. In this proposed project, the intern aims to explore microwave-based object detection technology as a solution to […]

Careful operational planning is essential for making agriculture autonomous and sustainable. The movements of agricultural equipment in the farm can be optimized to increase productivity and reduce costs and greenhouse gas (GHG) emissions. The aim of this project is to develop and productize advanced optimization algorithms to determine the best end-to-end machine routes, positions of […]

This research project is mainly concerned with maximizing distributed multiteam performance in the context of “extreme” work conditions. These conditions are those in which the human workforce is faced with safety-critical decisions, work overload, stress, complex peer interactions, uncertainty, and the prospect of serious consequences for error or delay. Fulfillment of project’s objectives will be […]

Autonomous vehicles (AVs) promise to enhance safety, reduce emissions, and improve transportation system efficiency and reliability. The growing demand for AVs is shaping the future of the automotive industry by transforming the in-vehicle experience and paving the way for large-scale implementation of autonomous driving. AV technology requires onboard intelligence relying on sensors and systems such […]

Anessa is developing software that assesses the feasibility of an anaerobic digestion facility at the earliest stages when trying to determine if a facility should be constructed. The challenge is that little information is fully known and there are a lot of factors that can affect the outcome to be positive or negative in the […]

The demand for higher bandwidth and ultra-lower latency has increased due to the rise of wireless devices. To meet these challenges, fifth generation (5G) new radio (NR) offers enhanced bandwidths with higher data rates and ultra-lower latency for real-time applications. The ultra-dense networks in 5G NR can improve the coverage. However, it can cause problem […]

Earthquakes are very common in Canada as more than 4000 seismic activities get recorded every year. Apart from all the seismic activities, over 1200 earthquakes get recorded in B.C. Natural Resources Canada report indicates that, there is 30% possibility that B.C. will experience a very high risk earthquake in next 50 years. Ottawa, Montreal and […]

Le génie cognitique allie des connaissances provenant de divers champs dont l’informatique, la robotique et les sciences humaines au sens large. Il s’intéresse particulièrement à l’interface et l’intégration entre l’humain et les diverses technologies qui peuvent améliorer son accès à l’information ou ses capacités. Le programme de psychiatrie neurodéveloppementale (PPNA) offre du support aux personnes […]

This project in collaboration with Oxford University focuses on improving how robots work together through coarse Collaborative Simultaneous Localization and Mapping (SLAM). SLAM technology is crucial for autonomous navigation, allowing robots to map and understand their surroundings while providing real-time localization estimates. The coarse approach we aim to develop would simplify how robots map their […]

We propose a semi-automated brain lesions segmentation method utilizing deep learning techniques and point prompting such as foundation models (SAM). This developed approach aims to assist physicians in the follow-up of multiple sclerosis disease at different stages, enhancing the likelihood of successful treatment for patients. The key contribution of this research lies in the advancement […]