As Director of the Scientific Data Division at Lawrence Berkeley National Laboratory, Ana Kupresanin leads scientists and engineers who develop the methods, software, workflows, and infrastructure needed to make scientific data usable, reliable, and reusable for science and AI. The division works across the scientific data lifecycle, helping researchers organize, curate, manage, access, analyze, and reuse data, while also developing machine learning methods, high-performance computing workflows, and partnerships with domain scientists across disciplines.
Kupresanin is a statistician and a Fellow of the American Statistical Association. Before joining Berkeley Lab in 2023, she spent more than a decade at Lawrence Livermore National Laboratory, where she held scientific and leadership roles and worked with researchers across fields to develop statistical methods, analyze complex data, and address uncertainty quantification problems.
That background shapes how she thinks about AI for science. Scientific data are not generic inputs to a model. They come from experiments, simulations, instruments, and observations, each with its own assumptions, limitations, uncertainties, and context. Kupresanin’s work focuses on bringing statistical thinking, machine learning, and data infrastructure together so that AI systems can be more reliable, interpretable, and useful for scientific discovery.
