Our mission is to enable excellence in data science research and applications across the Laboratory's core missions.
Data science has become an essential discipline paving the path of LLNL's key program areas, and the Laboratory is home to some of the largest, most unique, and most interesting data and supercomputers in the world. The Data Science Institute acts as the central hub for all data science activity at LLNL working to help lead, build, and strengthen the data science workforce, research, and outreach to advance the state-of-the-art of our nation's data science capabilities.
Kailkhura thrives on solving challenging problems in data science, focusing on improving the reliability and the safety of machine learning systems. “Reliability and safety in AI should not be an option but a design principle,” he states. “The better we can address these challenges, the more successful we will be in developing useful, relevant, and important ML systems.” Kailkhura also pursues mathematical solutions to open optimization problems, including a novel sphere-packing theory. He is building provably safe, explainable deep neural networks to enable reliable learning in applications for materials science, autonomous drones, and inertial confinement fusion. Thanks to his efforts with gradient-free algorithms and experiment designs, LLNL is the only national lab with research accepted at two high-profile venues—NIPS and JMLR—in 2018. Prior to joining LLNL’s Center for Applied Scientific Computing, Kailkhura attended Syracuse University where his PhD dissertation won an all-university prize. Recently, he co-authored the book Secure Networked Inference with Unreliable Data Sources.