Fundamental understanding of brewing phenomena and shelf-life extension of single-serve coffee – Year two

Brewing of premium coffee in single-serve capsule is challenging due to many design and machine constraints. Moreover, parameters that affect the brew quality are not fully understood. By collaborating with Mother Parkers Tea and Coffee Inc., this project will systematically evaluate the brewing parameters on the physical and sensorial properties of drip and espresso coffees. […]

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ML-Enhanced SOAR Framework for Proactive Threat Response in Managed Security Operations

Security Operations Centers today grapple with overwhelming alert volumes, fragmented toolchains, and manual response processes that impede timely threat containment. Analysts must pivot between multiple SIEM and EDR consoles, manually enrich indicators, and open tickets one by one, introducing delays that adversaries exploit to dwell undetected. Moreover, static severity tags lack the nuance to prioritize […]

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Advances in sensor fusion and gap-filling for satellite based analysis ready surface reflectance data

This project aims to develop a physics-guided deep learning framework that can be used to further enhance the robustness of surface reflectance forecasting in Planet Fusion. We want to improve and refine existing temporal-driven gap-filling techniques in handling extensive cloud cover and dynamic land changes to avoid delays and reduced reliability of delivered insights to […]

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Community Benefits Network in Prince Edward County

This project, in partnership with The County Foundation (TFC), supports the work of the Community Benefits Network (CBN), a coalition of 23 local organizations working to ensure that new development in Prince Edward County delivers lasting, positive outcomes for the community. With major public and private development projects on the horizon—including housing developments, a new […]

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Detecting Vulnerabilities in Generative AI

This project, a collaboration between 3Tenets Consulting Inc. and Dr. Wenjing Zhang from the University of Guelph, seeks to address emerging security and privacy vulnerabilities associated with the use of Large Language Models (LLMs) in enterprise environments. The initiative will focus on developing a prototype Privacy Leakage Assessment (PLA) Toolkit to evaluate and mitigate risks […]

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Scaling USA-NPN Sampling Design using LLM Agents

This project, part of the Global AI Alliance for Climate Action, aims to improve how the USA National Phenology Network (USA-NPN) collects and balances seasonal plant and animal data. By using large language models (LLMs) and AI-driven workflows, the project will help guide citizen scientists toward underrepresented species and locations, addressing gaps in the current […]

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Enhancing the Accuracy and Interpretability of Canadian Macro-Financial Tail Risk Forecasts via Multi-Quantile Deep Learning with Feature Engineering to Monitor Systemic Risks at the Bank of Canada

Crises risks are notoriously hard to quantify. Yet, when systemic crises materialize, for instance the Global Financial Crisis (GFC), the cost for the economy and the society can be huge, with protracted recessions and financial hardships for firms and households. Thus, it is essential for public authorities to monitor and proactively address systemic risks, thereby […]

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Assessing the Risks of Self-Reinforcing Attacks on Generative AI Systems

(1) the main activities of the partner ServiceNow develops a platform for client organizations to manage and automate large-scale processes across various industries. In 2020, ServiceNow acquired Element AI to strengthen its presence in the Artificial Intelligence (AI) research landscape and the Canadian AI ecosystem. This acquisition enabled the development of AI-driven products that improve […]

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