Graduate Students

11/02/2023 - Smriti Singh spends a lot of time on social media. But, not in the way most students do.

09/27/2023 - The work of researchers from The University of Texas at Austin’s Department of Computer Science in crash consistency has yielded a breakthrough innovation—the Chipmunk system. At its core, Chipmunk zeroes in on a crucial mission—meticulously testing file systems to identify and tackle crash consistency bugs that can significantly impact data integrity and system reliability. The UT Austin team has produced a promising solution that could pave the way for a new era in data storage and stability.

05/01/2023 - The work relies in part on a transformer model, similar to the ones that power ChatGPTA new artificial intelligence system called a semantic decoder can translate a person’s brain activity — while listening to a story or silently imagining telling a story — into a continuous stream of text. The system developed by researchers at The University of Texas at Austin might help people who are mentally conscious yet unable to physically speak, such as those debilitated by strokes, to communicate intelligibly again.

04/21/2023 - UT Computer Science Ph.D. Garrett Bingham’s research under Professor Risto Miikkulainen in smart automated machine learning has made significant steps toward more efficient neural network systems.

05/24/2022 - As chips become larger and more complex, their routing algorithms must also be improved and optimized to face the challenge. Recent UT Computer Science PhD graduate Michael Jiayuan He’s research in computer chip design has made a notable step forward towards more efficient and successful chip design in the academic arena.

02/10/2022 - In his recent paper, “Faster Coherent Quantum Algorithms for Faster Phase, Energy, and Amplitude Estimation”, UTCS PhD graduate Patrick Rall puts forth novel quantum algorithms for estimating important fundamental qualities of our complex world. Patrick’s approach simplifies the necessary computations compared to the current standard method. Estimation of these properties has applications in condensed matter physics and quantum chemistry as well as machine learning and finance.

10/14/2020 - 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.

10/06/2020 - A group of Texas Computer Science (TXCS) researchers from the Autonomous Mobile Robotics Laboratory (AMRL) comprising Joydeep Biswas, Sadegh Rabiee, Jarrett Holtz, Kavan Sikand, Max Svetlik, and John Bachman (UMass Amherst) have reached an incredible milestone in their research: deploying an autonomous robot that autonomously navigates on the campus-scale, resilient to everyday changes and varying conditions.

08/31/2020 - A team comprising Texas Computer Science (TXCS) Ph.D. student Santhosh Ramakrishnan, postdoctoral researcher Ziad Al-Halah, and TXCS Professor Kristen Grauman recently won first place in the 2020 Habitat visual navigation challenge held at the Conference on Computer Vision and Pattern Recognition (CVPR).

08/24/2020 - As students, faculty, and staff prepare to return to campus for the fall semester, a key concern is making the university as safe as possible and properly tracking health data to prevent outbreaks. An interdisciplinary team of researchers and students, including Texas Computer Science (TXCS) undergraduate students Rohit Neppali, Anshul Modh, Viren Velacheri, and Ph.D. student Anibal Heinsfeld, developed the Protect Texas Together app to help track and mitigate the spread of COVID-19 on the Forty Acres.