Dongping Zhang

Dongping Zhang is a Research Scientist at the National Renewable Energy Laboratory (NREL), specializing in AI and data visualization. He works within the Computational Science Center's Data, Analysis, and Visualization group and AI, Learning, and Intelligent Systems group.

Education:

• Ph.D. and M.S. in Technology and Social Behavior from Northwestern University
• M.A. in Computational Social Science from University of Chicago
• B.A. in Economics and Statistics from University of California, Berkeley

His research focuses on quantifying and visualizing uncertainty in machine learning models for renewable energy, energy efficiency, and transportation. This includes developing decision-support systems, explainable AI interfaces for black-box models, and tools for strategic decision-making in competitive multi-agent environments.

Recent publications highlight his work on conformal prediction sets for AI-advised tasks, probabilistic graph visualization (NetHOPs), and predictive interfaces for strategic environments. His methods bridge machine learning, human-computer interaction, and behavioral economics.

Scientific Awards:

• Best Paper Honorable Mention at CHI Conference (Top 5% of 4,028 submissions)
• Segal Design Institute Research Cluster Fellowship
• Regents' and Chancellor's Scholarship (UC Berkeley, top 2%)
• Berkeley Club of Hong Kong Undergraduate Scholarship

He has contributed to open-source tools like the NetLogo Taxi Cabs Model and collaborates with interdisciplinary teams including Jessica Hullman (Northwestern), Eytan Adar (University of Michigan), and Jason Hartline (Northwestern).