ESROP – Osaka – Systems Optimization and Decision Making

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 […]

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The development of self-powered wearable biosensors

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 […]

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Investigating brain blood flow control in pre- and post-menopausal women

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 […]

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Strain Measurement after Martensitic Transformation

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).

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AI-Assisted Decision Support Tools to Accelerate Catalytic Materials Design/Discovery: Towards Net-Zero Emissions

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 […]

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L2M – GradFinder

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 […]

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Acuity Insights – McMaster Summer Internship Program 2025

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 […]

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CO2/NH3 Bi-Direction Shipping between Canada and Asia

“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 […]

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Évolution des conditions hydrologiques de la plaine du Haouz (Maroc) en lien avec le climat, l’anthropisation et les séismes

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, […]

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Singularity formation for the hydrostatic Euler Equations

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.

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Advancing Soft Robotics Fabrication via Multi-Material Additive Manufacturing for Enhanced Sensing and Actuation

Whether conforming safely with the movements of humans, executing adaptable motion to navigate unpredictable terrain, or handling delicate objects with precision, soft robots are revolutionizing the way machines interact with the world. Soft robots take inspiration from biological systems, incorporating soft and stretchable materials to achieve lifelike motion. However, the fabrication of these advanced systems […]

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