Discover a unique summer learning experience at our academies on the UT campus. Tailored for high school students entering grades 10–12, each program is taught by UT faculty and focuses on a ...

Dr. Adam Klivans, UT Computer Science professor and director of the Institute for Foundations of Machine Learning, joined KXAN Austin to discuss the impact of DeepSeek’s latest AI model. He explained ...

For each course in the UT’s course schedule catalog, students can find valuable information such as eCIS evaluations, past ...

Sumaya M Al-Bedaiwi, [email protected], Office hours: Mon 12:30 PM - 1:30 PM, Wed 3:30 PM - 4:30 PM in the GDC Basement.

Traditional methods of collecting translation and paraphrase data can be prohibitively expensive, making construction of large, new corpora difficult. While crowdsourcing offers a cheap alternative, ...

I'm an assistant professor in the Computer Science Department and the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin. I was a PhD student at the ...

This is a section from the last essay written by Isaiah Berlin, published in the New York Review of Books, Vol. XLV, Number 8 (1998). Copyright: The Isaiah Berlin ...

Our students and faculty are changing the world through their contributions to computing education, research, and industry. These awards received by members of the UT Computer Science community make ...

We introduce a new entity typing task: given a sentence with an entity mention, the goal is to predict a set of free-form phrases (e.g. skyscraper, songwriter, or criminal) that describe appropriate ...

Assistant, Associate, Full Professor of Instruction/Lecturer (Non-Tenure Track Instructional) Assistant, Associate, Full Professor in Foundational AI/ML (Tenured/Tenure-Track Cluster Hire) Robotics ...

It is a misnomer. As Edsger Dijkstra used to say "Computer Science is no more about computers than astronomy is about telescopes". Computer Science is closely related to mathematics. It is the study ...

My research focuses on biologically-inspired computation such as neural networks and evolutionary computation. On one hand, the goal is to understand biological information processing, and on the ...