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From the College of Natural Sciences
Alumna Lisa Piccirillo Solves Famous 50-year-old Math Problem

Alumna Lisa Piccirillo Solves Famous 50-year-old Math Problem

Image courtesy of Ian MacLellan.

During her graduate studies at The University of Texas at Austin, Lisa Piccirillo solved a problem that had bedeviled mathematicians for five decades. Her discovery, published in the Annals of Mathematics, excited the math world and drew coverage from The Boston Globe, The Washington Post, Quanta, Popular Mechanics and more.

Randomized Sampling Could Help Solve Billions of Equations Simultaneously

Randomized Sampling Could Help Solve Billions of Equations Simultaneously

Credit: Oden Institute for Computational Engineering and Sciences

Algebra. Mention the word in public and anyone in earshot is likely to run screaming as far from you as possible. Society's mental block when it comes to mathematics is frequently based on a misconception that the kinds of mathematical principles we learn at school - such as algebra – are of little use to us in the real world.

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A Commitment to Inclusion in Texas Mathematics and Science

A Commitment to Inclusion in Texas Mathematics and Science

​Dean Goldbart sent a message to the community after Interim President Jay Hartzell announced that the building once named for R.L. Moore would be renamed and that Painter Hall would soon have a new Heman M. Sweatt entrance.

Natural Sciences Faculty Receive Prestigious NSF CAREER Awards

Natural Sciences Faculty Receive Prestigious NSF CAREER Awards

Two faculty members from the College of Natural Sciences have received distinguished Faculty Early Career Development (CAREER) Awards totaling $1,075,000 over 5 years from the National Science Foundation.

Meet the 30 Dean's Honored Graduates for this Year

Meet the 30 Dean's Honored Graduates for this Year

Each year, the College of Natural Sciences bestows its highest honors for graduating seniors on a select group of students. These students, known as Dean's Honored Graduates demonstrate excellence across multiple domains, achieving not only academically but in scientific research, independent intellectual pursuits, leadership, service, entrepreneurship and community building. Below are biographies of the 30 outstanding students selected by a committee of College of Natural Sciences faculty for this distinction in 2020.

Mathematician and Neuroscientist Chosen for Texas Ten Recognition

Mathematician and Neuroscientist Chosen for Texas Ten Recognition

Every year, the Alcalde by the Texas Exes flips the script and gives alumni the chance to give their favorite professors an A+. Through nominations from former students, the Texas Ten honors professors who have made a difference in the lives of Longhorns.​ This year, two of the Texas Ten were chosen from the College of Natural Sciences.
12 Ways Texas Science Innovators Made the Most of this Year

12 Ways Texas Science Innovators Made the Most of this Year

Out of the lab and into the marketplace. That could be the catch phrase for a growing number of UT Austin science students and faculty. They are pouring creativity and hard work into new efforts to bring UT science into new realms.

Top Texas Science Stories and Discoveries of 2019

Top Texas Science Stories and Discoveries of 2019

As we look back on 2019, it's been a year filled with fascinating discoveries and big developments in the College of Natural Sciences and beyond. Read on to see some of the highlights from this year in Texas Science.

Meet the New Faculty Members in Natural Sciences

Meet the New Faculty Members in Natural Sciences

As the year draws to a close, we're looking back on highlights of 2019, including the arrival and hiring of dozens of new tenured and tenure-track faculty members in the College of Natural Sciences. Below are some of the stellar scientists and mathematicians new to our college community.

UT Austin Launches Institute to Harness the Data Revolution

UT Austin Launches Institute to Harness the Data Revolution

Research from UT Austin professors and TRIPODS members Alex Dimakis and Eric Price shows that it is possible to learn a deep generative model that dreams images of human faces (right panel), trained by observing only occluded images (left panel). The middle panel shows a previous approach for solving this problem, that fails. [Figure from: AmbientGAN: Generative models from lossy measurements, by A. Bora, E. Price and A.G. Dimakis, ICLR 2018.]

Advances in machine learning are announced every day, but efforts to fundamentally rethink the core algorithms of AI are rare.