Computer Science
Sam Kumar
Blaise-Pascal Tine
I am a Professor in Computer Science Department at University of California, Los Angeles. I am a recent PhD Student graduate in the school of Computer Science at Georgia Institute of Technology. My research interests are in the area of hardware accelerators and software co-design, focusing in the architecture design, programming languages and compiler tools to support heterogenous computing. I’m also interested in domain-specific applications of accelerators such as 3D graphics, graphs analytics, and machine learning.
Yuan Tian
Yuan Tian is an Associate Professor of Electrical and Computer Engineering, Computer Science and of the Institute of Law, Technology, and Public Policy at University of California, Los Angeles. Before joining UCLA, She was an Assistant Professor of Computer Science at University of Virginia, and she obtained her Ph.D from Carnegie Mellon University in 2017, and interned at Microsoft Research, Facebook, and Samsung Research. Her research interests involve security and privacy and its interactions with computer systems, machine learning, and human-computer interaction. Her current research focuses on developing new technologies for protecting user privacy, particularly in the areas of the Internet of Things and machine learning. Her work has generated real-world impact as countermeasures and design changes have been integrated into popular platforms, and also impacted the security recommendations of standard organizations. She is a recipient of Okawa Foundation Award 2022, Google Research Scholar Award 2021, Facebook Faculty Award 2021, NSF CAREER Award 2020, NSF CRII award 2019, Amazon AI Faculty Fellowship 2019. Her research has appeared in top-tier venues in Security, and System. Her projects have been covered by media outlets such as IEEE Spectrum, Forbes, Fortune, Wired, and Telegraph.
Harold Pimentel
Bolei Zhou
Aditya Grover
Jiaqi Ma
Omid Abari
Nanyun (Violet) Peng
Baharan Mirzasoleiman
Lin Yang
Dr. Lin Yang is an assistant professor in the Electrical and Computer Engineering Department at the University of California, Los Angeles. His research focuses on developing and applying fast algorithms for machine learning and data science. His current research focus is on reinforcement learning theory and applications, learning for control, non-convex optimization, and streaming algorithms. Previously, he was a postdoc at Princeton University. He obtained two Ph.D. degrees (in Computer Science and in Physics & Astronomy) from Johns Hopkins University. He was a recipient of the Simons’ Research Fellowship and Dean Robert H. Roy Fellowship.