Summary
Dongping Zhang is a research scientist and PhD candidate at the National Renewable Energy Laboratory, contributing to the AI, Learning, and Intelligent Systems group as well as the Data, Analysis, and Visualization group within the Computational Science Center. His work centers on quantifying and visualizing uncertainty in ML models for renewable energy, energy efficiency, and transportation, with a focus on decision-support interfaces that enhance data-driven decision-making. He is pursuing a PhD at Northwestern University, pairing this with a solid foundation from UC Berkeley (BA in Economics and Statistics) and the University of Chicago (MA in Computational Social Science) to fuse quantitative rigor with social computing insights. Based in Chicago, he brings roughly a decade of experience in research and tool development that bridges analytics, visualization, and practical energy applications. He translates complex ML uncertainty into accessible visualizations and practical decision-support solutions for engineers and policymakers in the energy sector.
10 years of coding experience