Projets novateurs réalisés

Systemic and local role of complement component 3 (C3) in an experimental model of autoimmunity

Building Trust in AI-Generated Content: Innovative Strategies for Quality and Integrity Verification

In an era where AI can write articles, create reports, and even craft stories, ensuring this content is accurate, free from errors, and trustworthy is crucial. Our project, “Building Trust in AI-Generated Content: Innovative Strategies for Quality and Integrity Verification,” aims to tackle this important challenge and to measure and increase the reliability and trustworthiness of the content generated by artificial intelligence (AI).
We plan to develop new methods to check the quality and truthfulness of AI-generated text, making sure it meets high standards. For our partner organization, this means their AI platforms can produce better, more reliable content that users can trust. This will not only improve the organization’s reputation but also pave the way for safer, more effective use of AI in various sectors. Through this project, we’re trying to make AI a more dependable tool for generating high-quality content.

Sea Ice thickness distribution modeling

The aim of this internship is to carry out an analysis of the equations modelling the distribution function of sea ice thickness, particularly in the case of large deformations such as ridges. Among other things, we will be interested in the numerical solutions of these equations, their stability and their consistency.

Two-Stage BIM-Enabled Decision Support System for Selection of a Suitable Industrialized Building System

This study aims to promote and advance the application of Offsite Construction Manufacturing (OSCM) by
developing a BIM-enabled Decision Support System (BeDSS) to select and execute a suitable Industrial Building
System (IBS) for a given construction project.
The specific objectives of this research are as follows:
– To perform an OSC feasibility study of a building project by assessing the key decision-making factors
impacting the successful completion of the project.
– To assist decision-makers to select and execute a suitable IBS using the proposed Decision Support
System based on BIM data and decision-making factors which are associated with successful OSCM
project indicators.
Design Science Research is adopted as methodology for this project. Fuzzy AHP will be used to rank the different
types of Industrial Building System (IBS) alternatives.

Enhancing Autonomous Driving using Multiple Large Language Models (MLLMs)

Nowadays, leveraging advanced technologies like Generative Artificial Intelligence (AI), particularly Large Language Models (LLMs) such as GPT, holds promise in revolutionizing safety measures and resource optimization. However, while these general-purpose LLMs excel in various tasks, they may lack context specificity. Domain-specific LLMs, such as those tailored for biomedicine and transportation, are emerging to address this issue. For instance, in transportation, Multimodal Large Language Models (MLLMs) show the potential to enhance autonomous driving and traffic safety decision-making. Efforts also focus on using LLMs for accident prediction and prevention, with lightweight models proposed for real-time interventions. Despite advancements, there’s still a need for versatile AI agents capable of adapting to diverse scenarios. LLMs offer a foundation for such agents, with ongoing research exploring their potential. This project aims to integrate multiple LLM-based Intelligent agents into a framework for autonomous driving, enhancing decision-making and public safety by reducing accident risks. This initiative seeks to explore the use of MLLMs and AI agents in developing a novel autonomous driving framework.

Detecting atopic dermatitis with impedance measurements

This research improves atopic dermatitis (AD) detection, a common type of eczema, which affects about 20% of Canadians. AD causes dry and inflamed skin due to a lack of a key protein, making the skin barrier less effective against moisture loss and allergens. Current treatments like moisturizers and steroids can have side effects, and diagnosing AD accurately can be challenging, delaying treatment.

Traditional diagnosis involves a healthcare provider examining the skin and considering medical history, but this can be prone to errors. To improve this process, electrical impedance spectroscopy (EIS) can be used, which involves passing small electrical currents through the skin to detect abnormalities in cell structure. While this method has been used to detect skin cancer, its potential for AD diagnosis hasn’t been widely explored.

Our research will develop a mathematical model and simulate a device using computer programming. This device will be run through both healthy and affected skin areas, measuring changes in current strength and phase. The data will be used to create a graph, providing an overview of the skin’s condition.

The goal is to create a reliable and easy-to-use device that can accurately diagnose AD, leading to earlier treatment and improved outcomes for patients.

Quantum super-resolving lenses

Super-resolving lenses are able to beat the standard diffraction limit in optics and image objects smaller that the wavelength of light. Such devices are already important in areas such as the bio-medical sciences, and but could also find application in the emerging field of quantum technology by providing a way of coupling qubits with high fidelity. However, the operation and capabilities of some super-resolving lenses such as the Maxwell fisheye lens, which give perfect imaging in the limit of geometric optics, remains controversial in the more accurate wave theory of light. This theory project proposes to examine these issues by mapping to well-studied problems in quantum mechanics (such as the inverse square potential) that share similar properties, including non-hermitian features. This project would combine the expertise of two groups: one at the University of Birmingham which specializes in optics and topological techniques, and one at McMaster University that specializes in the quantum mechanics of singular and non-hermitian potentials. This project will benefit the larger optics and quantum information communities in both countries.

Laser Annealing is Full-Scale Electron Detectors

The primary objective of the Globalink research project is to develop and implement advanced techniques for the detection of energetic electrons in silicon detectors, with a focus on overcoming the limitations of traditional detection methods and mitigating radiation damage. We will try to investigate whether laser annealing and pixel migration techniques can effectively mitigate radiation damage in silicon detectors, restoring their functionality. The second question we are trying to answer is if optimization of detector design parameters will enhance the performance of silicon detectors in detecting energetic electrons and minimize radiation-induced damage. Max Planck Institute is at the forefront of physics and matter research and I would learn methods that would aid in Canada’s development in electronics and the technology sector.

Max Planck Institute for the Structure and Dynamics of Matter – Ultrafast Electron Diffraction Experiments and Software for Experimental Control

Ultrafast electron diffraction (UED) is an established tool to record atomic motion on very short timescales well below one picosecond. The sample, typically less than 100 nanometers thick, is first excited with an optical pump-pulse leading to the rearrangement of its atomic or molecular constituents. Subsequently, the structural changes are probed by a short electron pulse which scatters off the sample to form an interpretable diffraction pattern on a distant detector. By setting a time delay between the pump-pulse and the probe-pulse, different time points of the dynamical rearrangements of the excited sample can be recorded allowing the creation of animated molecular movements. This project utilizes UED to investigate fast dynamics in organic crystals, semiconductors, and high-temperature superconductors. However, these experiments require precise and accurate control of its hardware components. Inspired by existing software systems employed at leading accelerators and synchrotron facilities, a smaller-scale communication protocol needs to be developed to remotely control the hardware components to perform the experiment and analyze the data. This project strives to create a robust and intuitive UED system to tackle challenges in understanding fast dynamics and their implications for the functioning of future engineering materials.

Understanding crystallization mechanisms of Covalent Organic Frameworks

Explainable Artificial Intelligence for Remote Sensing

Mermaid: A PET Prototype for Adult Zebrafish – Practical Applications and Optimization