Ron Fisher ’16, founded Avina with partners Michael Wang ’16 and Vivek Sudarsan ’16, all three of whom are graduates of Cornell Tech.
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New statistical method powers research on health, climate, financial data
Machine learning and artificial intelligence wouldn’t be possible without the statistical models that underpin their analytic capabilities. A Cornell statistician and his colleague have developed a revolutionary new method to analyze complex datasets that’s more flexible, accurate and easy to use.
Rising star Ben Laufer: Improving accountability and trustworthiness in AI
With artificial intelligence increasingly integrated into our daily lives, one of the most pressing concerns about this emerging technology is ensuring that the new innovations being developed consider their impact on individuals from different backgrounds and communities. The work of researchers like Cornell Tech PhD student Ben Laufer is critical for understanding the social and ethical implications of algorithmic decision-making.
Diagnostic tool identifies puzzling inflammatory diseases in kids
A Cornell-led collaboration developed machine-learning models that use these cell-free molecular RNA dregs to diagnose pediatric inflammatory conditions that are difficult to differentiate. The diagnostic tool can accurately determine if a patient has Kawasaki disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), a viral infection or a bacterial infection, while simultaneously monitoring the patient’s organ health.
AI boosts indoor food production’s energy sustainability
Integrating artificial intelligence into today’s environmental control systems could reduce energy consumption for indoor agriculture by 25% – potentially helping to feed the world as its population rises, Cornell engineers have found.
AI modeling delivers more benefits, less risk for water partnerships
Researchers found that cooperative partnerships seeking to spread the cost burden of water infrastructure projects often end up forcing local partners to bear the brunt of supply and financial risks.
Machine learning explains material’s thermal conductivity
Using a combination of machine learning and powerful X-rays, Cornell researchers have solved a mystery behind the unusual behavior seen in a class of materials with potential for thermoelectric energy conversion and other applications.
Study finds potential link between DNA markers and aging
Researchers have uncovered DNA markers associated with retroelements, remnants of ancient viral genetic material, in our genes that act as highly accurate epigenetic clocks predicting chronological age.