Leveraging Large Language Models for Sales & Customer Success Automation

Mash helps revenue teams at technical B2B companies streamline pre- and post-sales activities by automating knowledge-intensive tasks such as answering product questions, managing bug reports and feature requests, and prepping for meetings. Its AI platform leverages data buried in messaging platforms, wikis, CRMs, and other internal tools to deliver timely, context-aware assistance to individuals in […]

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Optimizing Lightstage Capture for High Fidelity 3D Facial Reconstruction

Ubisoft is one of the world’s largest video game studios, specializing in 3D open-world games that require precise 3D character representations. In particular, achieving high-quality facial features is crucial, as humans are highly sensitive to small details in facial expressions. Currently, creating 3D facial representations first requires a Lightstage capture pipeline. This process begins with […]

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A Risk-Based Continuous Authentication Engine Using a Probabilistic Model around Behavioral Biometrics

Traditional static authentication systems have a fundamental deficiency; it assumes the presence of the validated user through the length of the session. Continuous authentication algorithms periodically validate the identity of a user during the entire session. It relies on information that can be automatically extracted from the user such as biometrics and behavior patterns. A […]

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Increasing dairy intake for the reduction of obesity and diabetes in adolescents

Dairy consumption has decreased in the last 30 years. Canada’s Food Guide no longer recommends three servings of dairy and emphasizes plant-based diets and dairy alternatives. Associated with this decrease is an increase in overweight and the risk of obesity and Type 2 Diabetes (T2D) in adolescents. Consistent with this advice, many adolescents have increased […]

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Development of Natural Language Queries Embedded Within a School Data Hub to Support Data-Informed Decision-Making by School-Based Practitioners

The University of Toronto Schools (UTS), through the Eureka Research Institute, is committed to advancing data-driven decision-making in K-12 education. This aligns with the growing recognition of the importance of data literacy in education, where students and teachers need to “read the world with data” and “write the world with data” (Louie, 2022). Recent research […]

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ESROP – KMUTT – Hybrid LSTM-GRU Architecture with Adaptive Attention for Financial Data

This research project focuses on using advanced machine learning techniques to better predict stock prices, specifically targeting stocks from the S&P 500. By combining powerful deep learning methods—such as LSTM and GRU networks—with adaptive attention mechanisms inspired by Transformer models, the project aims to create forecasting systems that can dynamically adapt to changing market conditions, […]

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Expanding and Enhancing Awesense’s Digital Twin Sandbox to Support the Clean Energy Transition

Awesense is a clean tech company on a mission to accelerate the transition to clean energy by simplifying the creation of data-driven applications for a decarbonized, decentralized grid. To enable the complex planning and operational decisions required by distributed energy resources (e.g., solar, wind, batteries, EVs), Awesense developed its Digital Energy Platform. This platform allows […]

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Quantum algorithms for non-adiabatic dynamics

Xanadu’s mission is to make quantum computing useful, through development of quantum hardware, software, and algorithms. One important direction in achieving this goal is identifying problems that can be solved on quantum hardware that are not tractable on classical computers, and then building quantum algorithms for those problems. We expect that eventually we will have […]

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ESROP – NUS – Predicting Complete IV Curves for Perovskite Solar Cells with AI

Predicting Complete IV Curves for Perovskite Solar Cells with AI. Perovskite solar cells are a groundbreaking technology, offering high efficiency and low manufacturing costs, making them a promising candidate for the future of renewable energy. Their tunable properties and rapid development have captured significant interest in both academic and industrial sectors. This project focuses on […]

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ESROP – NUS – PIML for reconstructing IV curves of PSC

Perovskite solar cells stand out due to their rapid advancements and high efficiency, combined with the promise of cost-effective production. These attributes have placed them at the forefront of next-generation renewable energy solutions. This project integrates physics-based principles into AI models to reconstruct IV curves, reducing reliance on extensive input parameters. By incorporating optoelectronic governing […]

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