An artificial intelligence system developed by a Cornell-led team has identified a promising material for creating more efficient fuel cells – a potential breakthrough in both materials science and machine learning.
Cornell researchers have released a free, open-source software to help make potentially subjective and time-consuming plant breeding decisions more consistent and efficient.
The new Shen Fund for Social Impact will enable students to pursue engineering projects that could benefit society by using technology in innovative ways.
A predictive model combining information about plant physiology, real-time soil conditions and weather forecasts can save 40% of the water consumed by traditional irrigation strategies, according to new Cornell research.
Professors Michael Heise and Marty Wells discuss how they collaborate on empirical legal research, applying advanced data science and statistical analyses to look at legal issues that affect people’s lives as well as examining the judiciary system and how it operates.
Now in its ninth year, Cornell’s SoNIC summer workshop has exposed hundreds of minority students from across the country to the frontiers of computer science, as well as the prerequisites and rewards of advanced degrees.
Mathematical and computational models can make power grids, financial institutions and other networks less vulnerable to collapse, Jon Kleinberg, the Tisch University Professor of Computer Science, said at a June 13 presentation on Capitol Hill.
A Cornell-led team has developed a way to use machine learning to analyze data generated by scanning tunneling microscopy, yielding new insights into how electrons interact and showing how machine learning can be used to further discovery in experimental quantum physics.
In a new collaboration, students from Dairy Herd Management teamed up with students in Topics in Cloud Computing to learn how to work together to develop the kinds of digital tools that could reshape farming.
