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 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) […]

This collaborative research project between McMaster University’s Materials Science and Engineering department and Grenoble INP Phelma’s SIMaP laboratory aims to investigate the development of accurate strain measurement techniques using transmission electron microscopy (TEM).

This project aims to accelerate the discovery of efficient high-entropy alloy (HEA) catalytic materials for CO2 electrolysis by integrating advanced quantum AI-based optimization techniques with quantum mechanics computation. By combining these cutting-edge methods, the project seeks to identify novel, efficient, and costeffective catalysts that can convert CO2 into valuable products, contributing to the achievement of […]

We are building GradFinder, an online platform that connects students with professors who are actively recruiting for thesis-based graduate programs. Many students struggle to find available positions, and professors are overwhelmed by unqualified inquiries. Our platform streamlines this process, improving access and efficiency on both sides. Through this project, we aim to refine our business […]

This project will provide a marketing intern with hands-on experience supporting Acuity Insights’ business growth and expansion into new markets. The intern will conduct market research, analyze engagement data, assist with event marketing, and optimize marketing processes to help Acuity improve its outreach and impact in the education technology sector. Their work will contribute to […]

“Green shipping corridors” are being established globally, including interest in new cargos of hydrogen (H2) and carbon dioxide (CO2). The former is challenging to transport in neat form, making liquid organic carriers (LOCs) and ammonia (NH3) attractive forms for transport. Carbon sequestration sites are also being established for CO2 disposal, however many are located far […]

La région du Haouz (Maroc), abrite l’un des aquifères les plus importants du pays et joue un rôle essentiel dans l’agriculture, le tourisme et l’industrie. Cependant, les sécheresses récurrentes, aggravées par les changements climatiques, entraînent une surexploitation des eaux souterraines. La pression croissante exercée par les activités humaines met en péril l’équilibre hydrique de l’aquifère, […]

This proposal aims to integrate mathematical analysis with numerical simulations using Physics-Informed Neural Network (PINN) schemes to investigate the primitive equations, a fundamental model for atmospheric and geophysical flows. The primary focus is on achieving a precise characterization of singularity formation in these models.