News Category
Machine Learning
The Cornell Agricultural Systems Testbed and Demonstration Site is working with the Weatherspoon lab in computer science to create a data pipeline and analytics platform that will allow farmers to aggregate their data for informed decision-making. At the same time, the researchers are ensuring that every farmer’s data will be kept private.
Four Cornell faculty members are among 99 researchers across the U.S. who have been awarded grants by the U.S. Department of Energy as part of its Office of Science Early Career Research Program.
A research group led by Matthew Wilkens, associate professor of information science in the Cornell Ann S. Bowers College of Computing and Information Science, is the recent recipient of a Schmidt Sciences award to leverage AI in the humanities to unlock new insights in human history and culture.
In new research that puts the latest models to test in a 3D environment, Cornell scholars found that AI fares well with untangling basic knots but can’t quite tie knots from simple loops nor convert one knot to another.
Cornell Tech faculty made a strong showing at the 2025 Conference on Neural Information Processing Systems (NeurIPS), held Dec. 2–7 in San Diego, presenting 23 research papers at one of the world’s premier gatherings for artificial intelligence and machine learning.
Vitaly Shmatikov, professor of computer science at Cornell Tech and the Cornell Ann S. Bowers College of Computing and Information Science, has received the Association for Computing Machinery Conference on Computer and Communications Security (ACM CCS) Test of Time Award for his influential 2015 paper, “Privacy-Preserving Deep Learning.”
Michael Macy, Distinguished Professor of Arts and Sciences in Sociology in the College of Arts and Sciences, with a joint appointment in the Department of Information Science in the Cornell Ann S. Bowers College of Computing and Information Science, is a recent recipient of an AWS [Amazon Web Services] Agentic AI Amazon Research Award.
Every day, millions of people are discharged after extended hospital stays, but matching these patients with appropriate care facilities can be arduous, often reliant on months-old, inaccurate data.
Now, a text message-based, hybrid computer-human system that regularly updates both patients’ and care facilities’ availability statuses, developed by a Cornell doctoral student, is smoothing that time-consuming process. The system was tested at a hospital in Hawaii for 14 months, beginning in early 2022, and helped place nearly 50 patients in care facilities.
