An automated explainable bioinformatics and AI workflow for multi-omic, climate and environmental data, applied to sustainability problems e.g., nature-based carbon capture.
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43 results for Science
AutoML for incremental machine learning algorithms for big time-series data.
Developing AI and analytics to understand the drivers of study or clinical trial efficiency.
We're developing technological solutions to assist subject matter experts with their scientific workflows by enabling the Human-AI co-creation process.
Performing pattern recognition and solving complex optimization problems with coupled oscillator networks.
An enterprise-scale initiative to measure, track, and reduce carbon emissions
Neuro-inspired AI to optimize learning and computing efficiency of next generation AI.
Enhance scientific discovery with multimmodal knowledge
Analyzing and visualizing differences in blood flow patterns, made visible with fluorescent dyes and multispectral imaging.
