The Scientific Artificial Intelligence (SciAI) Center
Abstract
The SciAI Center#s research focus is on developing pioneering AI methods and approaches that facilitate human-machine partnerships:to push the frontiers of scientific discovery and enable the development of unprecedented technological advancements. Mathematics has been identified as the common language underpinning the envisioned partnership, but this choice has deeper motivations. Mathematics is the language of the natural laws that, with great precision, describe our universe. The associated governing equations are then the syntax for our predictive theories. By creating novel AI architectures, that reason in terms of sophisticated mathematics, wefacilitate both the machine#s ability to learn about the world, and also its ability to communicate back to us what it has discovered; while at the same time opening the door to theoretical understanding of how and why the machine is able to learn what it does from data that are too complex for human interpretation. The SciAI Center is also a community of researchers who share a common interest in carefully studying the scientific questions that emanate from a consideration of the foregoing. The community members that wehave assembled are select mathematicians, computer scientists, and engineers; all having a deep interest in how applied mathematicscan facilitate our theoretical and practical understanding of novel SciAI systems and architectures. Our community is also deeply curious about the interplay between scientific data and learning: a topic at the heart of SciAI. As a community, we are committed to helping underrepresented student groups gain access to our leading-edge discoveries and emerging tools. We see this access as pivotal to increasing interest in STEM fields, and enhancing retention. Additionally, we believe that by exposing our student cohorts to new methods and techniques, we will instill skills that create avenues to future, professional opportunities.[APPROVED FOR PUBLIC RELEASE]
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 11, 2023
- Source ID
- N000142312729
Entities
People
- Christopher Earls
Organizations
- Cornell University
- Office of Naval Research
- United States Navy