Innovative Projects Realized

Real-Time Single-Photon Correlation Detection

This project develops specialized computer hardware to process data from advanced quantum cameras in real-time, enabling breakthrough applications in medical imaging, biological research, and astronomy. The work addresses a critical limitation in current quantum imaging systems, which must record data during experiments and analyze it later. This is a time-consuming process that prevents researchers from adjusting experiments on-the-fly. By implementing real-time photon correlation on reconfigurable hardware (FPGA), the project will enable immediate feedback for applications like non-invasive stroke monitoring, ultra-low-light microscopy of delicate biological specimens, and astronomical observations. The collaboration strengthens ties between Canadian computational imaging research and Switzerland’s world-leading sensor development capabilities, bringing cutting-edge expertise in high-speed data processing and multi-sensor systems back to Canadian institutions.

Empirical Validation of CXL Memory System Behaviour Against a Formal Model

Modern computer systems increasingly rely on shared memory technologies that allow multiple components, such as processors and accelerators, to access the same data. Compute Express Link (CXL) is a new industry standard designed to enable this kind of shared memory while preserving important correctness guarantees. While formal models describe how CXL systems are expected to behave, it remains unclear how well real implementations match these expectations in practice. This project will empirically test the behavior of CXL enabled systems against an existing formal model by designing and running targeted experiments. The results will improve understanding of emerging memory technologies and help ensure that future systems are reliable, correct, and performant. The collaboration will strengthen research ties between McMaster University and Imperial College London while providing advanced training in systems validation and experimental research methods.

Penning Plasma Oscillations

Accel-Link Ltd is associated with D-Pace (mutual ownership). It acts as an R&D innovation arm for DPace. D-Pace develops, manufactures and sells ion sources to market segments that utilize particle accelerators. D-Pace’s strategy is to use R&D products that solve customer’s nextgeneration accelerator needs that can result from initial R&D explorations undertaken by Accel-Link Ltd.
It is necessary to review the ion source applications landscape to uncover next generation precommercialization issues to be solved. This shall be limited to negative ion sources for this project.
The Penning Ion Source Test Stand or other future SIRC ion source test stands will ultimately be used for Masters/PhD projects and Technologist Interns projects which will be generated from the application survey research in this project. The market segments explored in this project will be in such areas as acceleratorbased medical therapy, medical diagnostic imaging, ion implantation, archeology (carbon-dating), AMS (used to determine air quality), surface science, metrology, discovery science, fusion etc.. All of these areas have significant social and economic benefits to society.

Electrical characterization of memristors for neural networks (AI)

Resistive memories have emerged as a pivotal advancement in modern electronics, offering remarkable advantages in energy efficiency, scalability, and non volatile operation. However, TiO2 based OxRAM devices still face key challenges, particularly regarding circuit level variability and the limited number of demonstrations in realistic application settings. This project addresses these gaps by thoroughly characterizing OxRAM switching dynamics, assessing their integration within analog and digital circuits, and developing automated Python based testing tools on the LOTUS neuromorphic platform. Together, these efforts will help establish the viability of OxRAM based analog modules for neuromorphic processing and next generation embedded AI systems.

Investigation of gut microbiome shift in Japanese dairy calves in response to heat stress

This project will expand on a previous project on heat stress on calf microbiome with the prevalence of climate change. Young calves are particularly vulnerable because their immune and temperature regulation systems are not fully developed, and their gut microbiome—the community of bacteria, archaea, and viruses that support digestion and health—is still forming. In Japan, temperature–humidity index levels regularly exceed calf comfort thresholds during the summer months, potentially leading to reduced growth, greater disease incidence, and reduced long-term performance. Similar threats are emerging in Canada, highlighted by increased frequency of “heat domes,” which cause unprecedented losses in dairy herds. This project will study how heat stress affects the developing gut microbiome communities of pre-weaned calves, focusing on the colon. Using novel “omics” technologies, the research will explore the disruption of early life microbiome development under heat stress and how these changes may affect calf growth, immunity, and resilience. The results will inform management strategies for heat-stressed calves, such as probiotics, microbial modulation, or tryptophan metabolite-based strategies. Outcomes will support improvements in calf management in Japan, provide critical information for the Canadian dairy industry, and contribute to building climate-resilient dairy production systems worldwide.

ESROP – Global + Max Planck Institute, University of Hamburg

Laser-driven plume formation is a process relevant to fluid dynamics, laser surgery, and materials processing. In photomechanical spallation, high-intensity laser pulses rapidly deposit energy into a liquid, triggering shock waves, phase transitions, and bubble formation. Although much is known about these phenomena, significant gaps remain in understanding how Newtonian fluids (e.g., glycerol and water) behave under ultrafast, high-strain-rate conditions. Traditionally, Newtonian fluids have been assumed to lack elasticity because they quickly dissipate deformation energy through viscous flow, at least at large time scales. However, research by Kayanattil et al. has challenged this view by demonstrating “rubber-like” elasticity in liquid glycerol during laser-driven free-surface flow under vacuum. In these experiments, the elastic response persists for microseconds—four orders of magnitude (ten thousand times) longer than the typical molecular relaxation time (t?)—and strongly influences bubble expansion and rupture. This metastable state suggests that collective molecular interactions can temporarily suppress energy dissipation, yielding solid-like behavior in a simple liquid. [4] While earlier studies noted shear elasticity at high frequencies or low strains, the large-strain, long-duration elastic responses observed at extreme strain rates (~106 s?¹) are unprecedented.[4] These results challenge conventional fluid mechanics and suggest that long-range molecular correlations are critical under such conditions.

Monitoring the Effectiveness of Wildlife Passages in Built Environments

The City of Edmonton’s River Valley and Ravine system is a vital natural asset, supported by policies like the City Plan, Natural Connections and Breathe: Edmonton’s Green Network Strategy. To foster connectivity, the City uses wildlife passages to ensure safe animal movement and reduce human-wildlife conflict. This project will build on past research efforts to improve understanding of how to effectively monitor wildlife passages specifically within tableland areas or within existing or proposed neighbourhoods. Some monitoring has been collected for the River Valley and Ravine areas, but more limited data has been collected within tableland areas. The need for monitoring wildlife passages is crucial for ensuring their long-term success and effectiveness. This work will further help to establish a baseline for wildlife passage design, monitoring and process renewal.

Automated Formalisation of Quantum Mathematical Proofs Using Machine Learning

This project aims to build an AI system that can turn regular, human-written math problems and solutions into fully checked, error-free formal proofs, with a special focus on quantum mathematics. The project will collect open-source quantum math problems, train a machine-learning model to translate them into formal proofs using the Lean proof assistant, and create an open dataset and simple converter tool that others can use.

The greatest benefit for the institutions participating in the research partnership will be the sharing of access to new toolkits, data, and approaches to trustworthy AI reasoning. Both University of Calgary and Technical University of Munich will benefit from the up-to-date knowledge and sharing of resources in the field of AI, formal verification, and quantum math. Valuable resources such as the dataset and the coverter system will contribute to their work in the fields of ML and mathematical reasoning. The work will result in a publication in an academic journal, which will improve both universities’ academic reputation.

Designing Responsible and Efficient AI Systems for IoT Threat Detection and Retrieval-Augmented Educational Assistance

This project explores two critical areas of AI research: cybersecurity for Internet of Things (IoT) systems and responsible AI assistants for education and research. IoT devices, widely used in healthcare, smart cities, and industry, are highly vulnerable to cyberattacks due to limited resources and large-scale connectivity. We propose AI-based intrusion detection systems that are lightweight, scalable, and capable of identifying both known and unknown threats in real time, balancing accuracy with computational efficiency.

Simultaneously, the project develops AI assistants using Retrieval-Augmented Generation (RAG) to support education and research. These assistants combine generative models with external knowledge retrieval to provide accurate, traceable, and ethically responsible guidance. They address common challenges such as hallucinations, biases, and lack of transparency, embedding safeguards for privacy, fairness, and user trust.

By integrating secure IoT monitoring with responsible AI applications, this project advances both technology and society. It strengthens the protection of critical digital infrastructures while providing reliable, transparent AI tools that enhance learning, research, and knowledge management. The outcomes aim to foster innovation in digital health, education, and cybersecurity, demonstrating AI that is both effective and responsible.

Equity meets efficiency: HIV treatment distribution

What’s the best way to distribute HIV treatment equitably? In developing countries, the major challenges are a lack of resources and infrastructure. In large developed countries like Australia and Canada, a major challenge is the geography and the clustering of populations. However, everyone deserves to have access to treatment, no matter where they live. This project will investigate the best way to distribute treatments so that patients have equal chance of reaching them, no matter where they are, thus satisfying both medical and ethical requirements.

Generation and Characterization of Camelid Nanobodies for Applications in Biomedical Research

Proteins control nearly all biological processes in animals, including growth, metabolism, immunity, and responses to stress or disease. To understand how proteins work, scientists often need tools that can bind to them very specifically and stabilize them for study. Nanobodies are a new type of antibody fragment derived from camelids such as alpacas. Unlike traditional antibodies, nanobodies are very small, highly stable, and able to bind tightly to regions of proteins that are otherwise difficult to study. Two nanobodies have been approved as drugs and many more are in clinical trials, and this is a growing field due to the advantages of nanobodies compared to mammalian antibodies.
In this project, the student will participate in the generation and characterization of nanobodies that bind to a target protein relevant to animal health and biological regulation. The work will involve selecting nanobodies from large libraries using phage display, testing their binding using biochemical assays, and producing selected nanobodies in bacterial systems. These nanobodies can then be used as research tools to help determine protein structure and function, which ultimately contributes to understanding disease mechanisms and identifying new therapeutic strategies.

Qualification des équipements de mesure géospatiale pour le suivi et la documentation des structures patrimoniales

Ce projet vise à améliorer la documentation et le suivi des bâtiments historiques à l’aide de technologies géospatiales avancées. Dans la dernière décenie, une émergence de nombreuses nouvelles technologies a vue le jour, mais une analyse sérieuse de la qualité des données reste indispensable. Le stagiaire contribuera en évaluant empiriquement différentes technologies de mesure géospatiale, telles que LiDAR statique et mobile, drones photogrammétriques, photogrammétrie terrestre et systèmes GNSS. Le projet comprend trois étapes principales : l’acquisition et la préparation de données géospatiales sur des bâtiments représentatifs, l’analyse comparative de la précision, de la cohérence spatiale et de la stabilité temporelle des mesures, et la synthèse des résultats pour produire des recommandations opérationnelles. L’objectif est de déterminer quels équipements et protocoles offrent les données les plus fiables et répétables pour le suivi des structures patrimoniales, en tenant compte des défis liés aux géométries complexes et aux contraintes d’accessibilité. Les résultats permettront de renforcer la conservation durable du patrimoine bâti en fournissant des modèles 3D détaillés, des évaluations précises de l’état des structures et des protocoles reproductibles pour d’autres sites patrimoniaux. Ce projet contribue ainsi à la modernisation des pratiques de surveillance et à l’amélioration de la gestion scientifique des bâtiments historiques.