In the quest to miniaturize camera lenses and other optical systems, Cornell researchers have, for the first time, defined the fundamental and practical limits of spaceplates.
Cornell scientists have created an evolutionary model that connects organisms living in today’s oxygen-rich atmosphere back billions of years – to a time when Earth’s atmosphere had little oxygen.
A new study calculated renewable energy projects' potential to profit from bitcoin mining during the precommercial development phase, when a wind or solar farm is generating electricity, but has not yet been integrated into the grid.
After battling three robots in the Norwalk Havoc Robot League’s March of the Bots competition, Cornell Combat Robotics looks to make upgrades with a $10,000 grant.
The research-sharing platform is a free resource for scholars around the world in fields including physics, math and computer science, who use the service to share their own cutting-edge research and read work submitted by others.
An interdisciplinary research team led by Carla Gomes, professor of computing and information science, has developed Deep Reasoning Networks, which combine deep learning with an understanding of the subject’s boundaries and rules.
In 2022-2023, the Center for Teaching Innovation awarded five Innovative Teaching & Learning Awards to Cornell faculty. With a goal of facilitating vibrant, challenging, and reflective learning experiences at Cornell, these awards sponsor projects across the colleges that explore new tools and emerging technologies, approaches, and teaching strategies. CTI is now accepting pre-applications for the 2023-2024 Innovative Teaching and Learning Awards – the deadline is April 17.
Cornell Engineering has announced the winners of its seventh annual Engineering Innovation Competition, which recognizes innovative product concepts and prototypes from students.
A Cornell-led collaboration harnessed chemical reactions to make microscale origami machines self-fold – freeing them from the liquids in which they usually function, so they can operate in dry environments and at room temperature.
Using a Packard Fellowship for Science and Engineering from the David and Lucile Packard Foundation, Peter McMahon, assistant professor of applied and engineering physics, aims to harness the power of photonics to build processors for neural networks that are more than 1,000 times more energy efficient.