Stanford University
Showing 1-10 of 13 Results
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Jiechao Gao
Postdoctoral Scholar, Civil and Environmental Engineering
BioJiechao Gao is a Postdoctoral Research Associate at Stanford University's Center for Sustainable Development and Global Competitiveness. He received his Ph.D. in Computer Science from the University of Virginia, his M.S. in Electrical Engineering from Columbia University, and dual B.S. degrees in Applied Physics and Financial Engineering from Jilin University. Prior to joining Stanford, he served as an Associate Research Scientist at Columbia University.
His research spans federated learning, large language model (LLM) interpretability and efficiency, reinforcement learning, and privacy-preserving AI, with applications in healthcare, smart buildings, IoV, and finance. He has published extensively at top venues including ICLR, NeurIPS, ICML, AAAI, EMNLP, KDD, CVPR, ACL, etc. He serves as Area Chair or Senior Program Committee member for conferences such as ICLR, NeurIPS, ICML, AAAI, EMNLP, KDD, IJCAI, IJCNN, ICASSP, and reviews for journals such as JMLR, IEEE IoT-J, and IEEE TITS. His recognitions include the Google HE Faculty AI Fellowship (2026), Stanford/Elsevier Global Top 2% Scientists (2024 & 2025), and multiple Best Paper Nominations. -
Catherine Gorle
Associate Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering
Current Research and Scholarly InterestsGorle's research focuses on the development of predictive flow simulations to support the design of sustainable buildings and cities. Specific topics of interest are the coupling of large- and small-scale models and experiments to quantify uncertainties related to the variability of boundary conditions, the development of uncertainty quantification methods for low-fidelity models using high-fidelity data, and the use of field measurements to validate and improve computational predictions.
