Yuting Chen is a Staff Data Scientist in the Energy Efficiency Studies Department at Lawrence Berkeley National Laboratory. Yuting's research focuses on data-driven modeling of emerging technological approaches that can support the more efficient and flexible use of energy. Yuting leads several analysis and data collection efforts supporting the U.S. Department of Energy's Energy Efficiency and Renewable Energy program.

Yuting's work also has touched on emerging technologies across a range of sectors. She conducts research and analysis into the potential for reducing energy consumption of U.S. commercial and industrial motor system market and proposes frameworks as decision-making tools to evaluate potential impact of water conservation programs for U.S. Environmental Protection Agency.

Additionally, Yuting helped develop BioC2G, a platform for life‑cycle assessment (LCA) and techno‑economic analysis (TEA) of biofuel and bioproduct pathways, with built‑in and custom models to evaluate cost, water use, and greenhouse gas emissions, supporting U.S. Department of Defense DARPA program priorities. She also uses large language models (LLMs) to extract and standardize bioprocess flowsheets from scientific papers, enabling reliable and transferable TEA for emerging biotechnologies.

Yuting holds a Ph.D. in Applied Mathematics from Ecole Centrale Paris, France, and a M.S. in Biostatistics, Bioinformatics and Modeling from INSA de Lyon, France.