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.
Data Scientist Spotlight
Machine learning (ML) and data analytics tools are rapidly proving necessary for materials discovery, optimization, characterization, property prediction, and accelerated deployment. Yong Han is at the forefront of LLNL’s efforts to integrate data science techniques into materials science research and development. For example, he leads a team that uses ML to analyze multimodal data for optimizing feedstock materials. Han explains, “We’re addressing important questions in data sparsity, explainability, reliability, uncertainty, and domain-aware model development.” His recent work in this area includes an njp Computational Materials paper, a Science & Technology Review research highlight, and a DSI research spotlight. “Not all data are created equal. We need to evaluate what data we’re collecting and how we’re collecting them,” Han states. He emphasizes that domain scientists and data scientists will benefit from working closely together, adding, “I envision permeation of data science tools in all of our projects at the Lab.” Han holds a PhD in Chemistry from UC Santa Barbara and joined LLNL in 2005.