Aditya Akella

09/24/2024 - The job of building computer networks that train and run large AI models is becoming increasingly complicated because traditional network designs can’t operate at the higher speeds that the AI workloads require and need to be tuned to a variety of communication endpoints (such as CPUs, graphics processing units and AI accelerators) that have widely different characteristics, including data generation speeds. Moreover, AI workloads require advanced network monitoring capabilities to quickly diagnose and resolve performance bottlenecks.

05/23/2024 - Aditya Akella leads the project that aims to boost performance of OSes and help enable assistant robots, autonomous vehicles and smart cities.

01/24/2024 - Computer Scientists Aditya Akella and Emmett Witchel have been named 2023 Fellows of the Association for Computing Machinery.

08/04/2022 - It's hard to make changes to the software running on a computer network while it's in use—and that can make it harder to respond quickly to a cyberattack. The National Science Foundation has awarded a grant to computer scientists from Rice University, The University of Texas at Austin and the University of Washington to develop runtime programmable networks that can respond to real-time changes rapidly and without interruption of service.

06/29/2022 - The ACM Internet Measurement Conference 2010 research paper “Network Traffic Characteristics of Data Centers in the Wild”, written by UT Computer Science Professor Aditya Akella, along with collaborators Theophilus Benson and David A.