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 […]

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 […]

Professor Kim’s team is advancing AIST’s initiative to develop a Foundation Model for Computer Vision, a transformative AI system designed to address diverse tasks through large-scale pre-training. These models are vital for computer vision, which focuses on enabling machines to interpret visual data like images and 3D point clouds. Professor Kim’s work centers on 3D […]

This project will investigate new methods for improving decision-making tools that help organizations make better choices when faced with uncertainty. Specifically, we will study how to more accurately estimate weights in the Analytic Hierarchy Process (AHP), a common tool used for Multi-Criteria Decision Making (MCDM). By focusing on interval and fuzzy weight estimation, the project […]

The proposed project aims to develop a wearable biosensor for real-time monitoring of critical cardiovascular disease (CVD) biomarkers, such as C-reactive protein, Troponin I, and Myoglobin, along with physiological parameters like heart rate. The biosensor will achieve high selectivity and durability by utilizing molecularly imprinted polymer (MIP) technology. The intern will collaborate with Professor Joseph […]

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 […]

The project’s goal is to investigate the use of a 2D reduced graphene oxide (rGO) based microfluidic channel driven electrochemical biosensor to detect AMI biomarkers. The device could be able to identify heart attacks before they happen. Therefore, it may be beneficial to reduce the enormous number of deaths brought on by this illness worldwide. […]

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 […]

This project investigates how menopause influences brain function by comparing blood flow in pre- and post-menopausal women. Estrogen plays a crucial role in protecting the vascular system; however, as women transition through menopause and estrogen levels decline, the risk of diseases such as stroke and vascular dementia increases significantly. I will conduct research at Bangor […]

This project aims to characterize and analyze the Community Health Dataset using AI techniques. This dataset, sourced from the Cambridge Community Services Trust, contains electronic health records (EHRs) of 111,317 children and young people aged 0–18 years, covering the period from 2007 to 2021. The significance of this project lies in several key aspects: (1) […]