Stay updated on recent achievements, research highlights, and news within the SSE Research community.
Tulane's research team is using AI to accelerate the discovery of next-generation superconductors, receiving DOE Genesis Mission funding.
Tulane researchers received $1.5M from ARPA-H to develop fetal monitoring technology capable of directly measuring fetal tissue oxygen levels during pregnancy and labor.
Malai Harrington found ecohydrology research via a flyer. She studies climate, water, and carbon in Dr. Molini's lab, including field work at LUMCON.
Tulane's Social Memory Lab uses awake infant fMRI to study how baby brains process social information, aiming to understand early social cognition.
Shuaihua Gao, an assistant professor in the Department of Chemical and Biomolecular Engineering at Tulane University, has received a National Science Foundation CAREER Award for a five-year research project that could change how scientists approach enzyme design. The award, one of NSF's most prestigious recognitions for early-career faculty, will fund her project, "From Energy Flow to Function: A Biophysical Framework for Rational Enzyme Evolution," through May 2031.
YiPing Chen, a professor of Cell and Molecular Biology in the Tulane School of Science and Engineering, has been elected a Fellow of the American Association for the Advancement of Science (AAAS) in the Section of Biological Sciences. The honor recognizes individuals for distinguished contributions to science and its applications.
For Chen, who has spent almost three decades as an independent researcher, the recognition carries personal weight. "This is a nice honor for me and recognition of my contribution to the science," he said.
Gold has been prized for thousands of years for its enduring shine, but Tulane University researchers have discovered that gold’s resistance to tarnishing depends on more than its chemistry.
In a field dominated by ever-larger GPUs and rising energy demands, a team of researchers is looking in a different direction. Instead of electrons, they are using light.
In a new study published in Machine Learning: Science and Technology, researchers Manon P. Bart, a recent Tulane PhD graduate, along with Nick Sparks and Ryan T. Glasser, introduce a method that dramatically improves how optical neural networks are trained, bringing this emerging technology closer to real-world use.