INNOVATIVE
ARTIFICIAL INTELLIGENCE AND MODELLING PREDICTIONS
Water Institute researchers are using artificial intelligence (AI) and machine learning to improve the efficiency, flexibility and predictive capability of models.
Juliane Mai (Earth and Environmental Sciences) led an award-winning model intercomparison project that consistently compared simulated outputs of a wide variety of models, including machine learning models, in the Great Lakes region. Claude Duguay (Geography and Environmental Management) is pioneering the use of machine learning models to process satellite radar altimetry data to identify between open water, thin ice, growing ice or melting ice with an unprecedented level of accuracy. Nandita Basu (Earth and Environmental Science and Civil and Environmental Engineering) was awarded funding to develop a new AI-powered models to predict nutrient loads entering the Great Lakes without daily monitoring data. Andrea Scott (Mechanical and Mechatronics Engineering) and David Clausi (Systems Design Engineering) are using advanced machine learning and AI techniques with remote sensing to forecast sea ice conditions and identify beluga whales. Marek Stastna (Applied Mathematics) developed high resolution numerical simulations to understand how the fluid dynamics of “cabbeling” in Canadian lakes – where two masses of freshwater mix to form a denser mass which leads to more mixing as it sinks – may inform turbulence parametrizations, including AI-based parametrizations.
RESEARCHERS
INNOVATIVE
ARTIFICIAL INTELLIGENCE AND MODELLING PREDICTIONS
Water Institute researchers are using artificial intelligence (AI) and machine learning to improve the efficiency, flexibility and predictive capability of models.
Juliane Mai (Earth and Environmental Sciences) led an award-winning model intercomparison project that consistently compared simulated outputs of a wide variety of models, including machine learning models, in the Great Lakes region. Claude Duguay (Geography and Environmental Management) is pioneering the use of machine learning models to process satellite radar altimetry data to identify between open water, thin ice, growing ice or melting ice with an unprecedented level of accuracy. Nandita Basu (Earth and Environmental Science and Civil and Environmental Engineering) was awarded funding to develop a new AI-powered models to predict nutrient loads entering the Great Lakes without daily monitoring data. Andrea Scott (Mechanical and Mechatronics Engineering) and David Clausi (Systems Design Engineering) are using advanced machine learning and AI techniques with remote sensing to forecast sea ice conditions and identify beluga whales. Marek Stastna (Applied Mathematics) developed high resolution numerical simulations to understand how the fluid dynamics of “cabbeling” in Canadian lakes – where two masses of freshwater mix to form a denser mass which leads to more mixing as it sinks – may inform turbulence parametrizations, including AI-based parametrizations.
RESEARCHERS
Supporting United Nations SDGs:
NOVEL DISCOVERY ON ANCIENT PHOTOSYNTHESIS
A “failed” experiment by Josh Neufeld (Biology) and his former student Jackson Tsuji led to a novel discovery that could change how scientists understand photosynthesis and its origins. While searching for unique bacteria from northern Canadian lakes, the researchers, after much coaxing, found a novel clade of protein believed to be a new branch of photosynthetic life and a key piece of the puzzle for resolving how photosynthesis developed on Earth.
RESEARCHER
NOVEL DISCOVERY ON ANCIENT PHOTOSYNTHESIS
A “failed” experiment by Josh Neufeld (Biology) and his former student Jackson Tsuji led to a novel discovery that could change how scientists understand photosynthesis and its origins. While searching for unique bacteria from northern Canadian lakes, the researchers, after much coaxing, found a novel clade of protein believed to be a new branch of photosynthetic life and a key piece of the puzzle for resolving how photosynthesis developed on Earth.
RESEARCHER
NOVEL RADAR-BASED TECHNOLOGY PROVIDES INSIGHT INTO SNOWPACKS
Richard Kelly (Geography and Environmental Management) developed a novel radar-based technology to provide more insight into snowpacks and their relationship to climate change, water resource management and hazard prediction. This new technology will provide scalable coverage and accurate measurements of not only the area of snowpacks, but also their mass or “snow water equivalent”.
RESEARCHER
NOVEL RADAR-BASED TECHNOLOGY PROVIDES INSIGHT INTO SNOWPACKS
Richard Kelly (Geography and Environmental Management) developed a novel radar-based technology to provide more insight into snowpacks and their relationship to climate change, water resource management and hazard prediction. This new technology will provide scalable coverage and accurate measurements of not only the area of snowpacks, but also their mass or “snow water equivalent”.
RESEARCHER
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