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From the College of Natural Sciences
Three Natural Sciences Faculty Receive NSF CAREER Awards

Three Natural Sciences Faculty Receive NSF CAREER Awards

Three faculty members from the College of Natural Sciences have received distinguished Faculty Early Career Development (CAREER) Awards from the National Science Foundation.

Kristen Grauman Named Finalist in 2021 Blavatnik National Awards for Young Scientists

Kristen Grauman Named Finalist in 2021 Blavatnik National Awards for Young Scientists

University of Texas at Austin computer science researcher Kristen Grauman was selected as a finalist for the 2021 Blavatnik National Awards for Young Scientists.

Xue-Xin Wei Asks Basic Questions about the Nature of Intelligence

Xue-Xin Wei Asks Basic Questions about the Nature of Intelligence

Image by Vivian Abagiu.

Xue-Xin Wei, a computational and theoretical neuroscientist, recently joined the Department of Neuroscience as an assistant professor. Wei grew up in Qingdao, China, before obtaining his undergraduate degree in mathematics at Peking University. His lab works at the intersection of computational/theoretical neuroscience, statistics, artificial intelligence and deep learning. He and his team work closely with experimental scientists to test predictions of computational models to form theory-experiment loops.

New Study Shows How Deep-learning Technology Can Improve Brain Imaging

New Study Shows How Deep-learning Technology Can Improve Brain Imaging

Compare these two images of a slice of brain tissue from a rat. The PSSR method applies deep learning to a low resolution image from a scanning electron microscope (left) to yield a higher resolution image (right).

Neuroscience researchers often face challenges when using high-powered microscopes to capture clear images of brain tissue. Microscopes suffer from what researchers call the "eternal triangle of compromise" — image resolution, the intensity of the illumination the sample is subjected to, and speed compete with each other. For example, taking an image of the sample very quickly can result in a dark image, but subjecting a biological sample to more intense light can damage it.

UT Austin Professors Named ACM Fellows by the Association for Computing Machinery

UT Austin Professors Named ACM Fellows by the Association for Computing Machinery

The Association for Computing Machinery, the primary professional organization in the field of computer science, has named two University of Texas at Austin professors — Peter Stone and Lizy Kurian John — as ACM Fellows. The award goes only to highly distinguished computer scientists representing the top 1% of ACM members.

The Hearts and Minds Behind AI

The Hearts and Minds Behind AI

Austin tech entrepreneurs and devoted Longhorns Amir and Zaib Husain. Photo: Sloan Breeden

​“Zaib and I chose to make this gift because we believe artificial intelligence will one day help elevate the human condition.”

— ​​​Amir Husain

At the age of four Amir Husain fell in love with computers — in his words, he "became obsessed" with them. In his teens he began writing to his heroes, computer scientists like Niklaus Wirth, who created the Pascal programming language, and Nicholas Negroponte, a pioneer in the study of how humans interact with computers. They all wrote back. Amir left his home of Lahore, Pakistan to attend The University of Texas at Austin 8,000 miles away, drawn by the work of one of UT's computer science labs. While at UT, he found a kindred spirit in his wife Zaib, who was also from Lahore and a student at the McCombs School of Business.

Mission Accomplished: Army Futures Command Teams with Texas Robotics

Mission Accomplished: Army Futures Command Teams with Texas Robotics

A methodical voice tells the watching crowd, "I am going to remove the lid." Everyone is quiet as a robot using artificial intelligence (AI) opens a trash can and lifts out a bag. Students and researchers hold their breath as it navigates across the floor of a mock house, avoiding obstacles to its destination. "Mission accomplished," it says. The trash has been taken out and the audience applauds. This is a huge achievement for the robot designed by a Texas Robotics team for the 2019 RoboCup competition.

UT Scientists Use AI to Find Tourist Movement Patterns in Cuzco, Peru

UT Scientists Use AI to Find Tourist Movement Patterns in Cuzco, Peru

We live in an increasingly digital era. Research shows that the average American checks their phone about 58 times daily, and spends an average of 4.5 hours a day on their phone. Without a doubt the amount of time the modern-day person spends on their phones has changed many aspects of how our society functions. For example, in the past decade we have seen a dramatic shift in forms of advertising. Companies are able to take note of people's patterns online and create personalized ads through the use of artificial intelligence (AI).

Artificial Intelligence Revs Up Evolution’s Clock (Audio)

Artificial Intelligence Revs Up Evolution’s Clock (Audio)

Evolutionary biologists never have enough time. Some of the most mysterious behaviors in the animal kingdom—like parenting—evolved over thousands of years, if not longer. Human lifespans are just too short to sit and observe such complex behaviors evolve. But computer scientists are beginning to offer clues by using artificial intelligence to simulate the life and death of thousands of generations of animals in a matter of hours or days. It's called computational evolution.

UT Austin Selected as Home of National AI Institute Focused on Machine Learning

UT Austin Selected as Home of National AI Institute Focused on Machine Learning

The NSF AI Institute for Foundations of Machine Learning and the Machine Learning Laboratory will be administratively housed in the Gates-Dell Complex at The University of Texas at Austin. Photo credit: Vivian Abagiu/University of Texas at Austin.

The National Science Foundation has selected The University of Texas at Austin to lead the NSF AI Institute for Foundations of Machine Learning, bolstering the university's existing strengths in this emerging field. Machine learning is the technology that drives AI systems, enabling them to acquire knowledge and make predictions in complex environments. This technology has the potential to transform everything from transportation to entertainment to health care.