This project uses AI and smart thermostats to predict heatwaves in Canada, helping protect public health. By analyzing indoor and outdoor temperature data, we aim to improve heatwave forecasting and understand how extreme heat affects indoor spaces. Using machine learning, we develop models to predict future indoor temperatures, supporting better planning and response strategies. The […]

Despite advancements in women’s health diagnostics, cervical cancer screening rates remain critically low due to the invasive nature of traditional collection methods like Pap smears and self-swabs. CELLECT is pioneering a non-invasive, nanotechnology-enabled collection device—the CELLECTPad—that passively captures high-quality cervical and epithelial cells during menstruation. By removing the discomfort and accessibility barriers of existing methods, […]

This project explores how people from different cultures make important life decisions, such as career choices or relationships. It focuses on understanding how cultural norms, social values, and religious beliefs influence decision-making. The research will use advanced text analysis (Natural Language Processing) and surveys to identify patterns in how people from different backgrounds approach decisions. […]

This project aims to develop advanced machine learning models to analyze arterial blood pressure (ABP) waveforms from patients in intensive care units (ICUs). By using a large dataset and cutting-edge techniques like transformer architectures and contrastive learning, the goal is to create models that can accurately predict patient outcomes, such as ICU mortality and hospital […]

The goal of this project is to develop a software system to collect, store, organize and query Twitter messages, and to develop algorithms that can process the Twitter data to extract value-added information, in particular, the geolocation of Tweets. First, we will design and implement a processing and analytics system for Twitter data using the […]

This research project pioneers the development of novel molybdenum disulfide (MoS2)/copper hybrid materials through electrochemical intercalation and exfoliation techniques. By transforming readily available powdered molybdenite—a byproduct of Canadian mining operations—into atomically thin layers with enhanced properties, the work creates a sustainable pathway for producing high-performance two-dimensional materials without organic additives that typically compromise conductivity. The […]

This project aims to enhance the safety, precision, and efficiency of robotic surgical assistants — collaborative robots designed to work alongside surgeons — by developing a computer vision-based system that prevents collisions in real time. Using cameras and advanced image processing techniques, the system will monitor the operating room, detecting people and other obstacles. It […]

This research project is situated within the broader scientific context of international relations, security studies, and European foreign policy. In recent years, the geopolitical landscape has been significantly shaped by China’s increasing global influence and its complex relationships with both Russia and the West, and it changed even more drastically when the Russia has started […]

The goal of this project is to improve the management of electric community microgrids. In contrast to traditional power grids with large centralized power plants that provide energy in a top down fashion to consumers, the introduction of renewable energy such as solar has given rise to bottom-up electric microgrids of prosumers (i.e., consumers that […]

AltaML builds artificial intelligence (AI)-enabled solutions to business problems. We work with organisations, bringing together their data and domain expertise with our AI expertise, to develop AI solutions that are deployed in their operations. We also commercialize AI-enabled products business via industry-specific ventures, yielding scalability from our investment in the first solution. AltaML’s AI Lab […]

This project aims to improve the monitoring and management of soil erosion in agricultural landscapes using advanced technologies like combinations of optical and LiDAR data from remotely piloted aircraft with machine learning. By creating detailed, high-resolution models of soil erosion and deposition, the project will help quantify erosion processes more efficiently than traditional methods. The […]

The objective of the proposed research is to design and implement an innovative IBI scheme capable of minimizing basis risk. Forage insurance will be used as an example to empirically examine the effective implementation of the IBI, through establishing an adequate relationship between the weather index and forage yield. Therefore, a second objective of the […]