Join to learn from Zhecheng Wang about how he developed domain-tailored machine learning models and leveraged multi-modal geospatial data to construct "Energy Atlas". Energy Atlas is a large-scale map overlay for distributed energy resources (DERs) and electricity infrastructures. This can address challenges in renewable energy adoption and climate change mitigation.

The seminar is open to the public. Stanford students enrolled in CEE 272T/EE 292T: SmartGrids and Advanced Power Systems Seminar must attend in person. All others, please register to attend on Zoom via the RSVP link.

Bio: Zhecheng Wang is PhD student in Civil and Environmental Engineering with a minor in Computer Science at Stanford University. He is co-advised by Professors Ram Rajagopal and Arun Majumdar. His research is aimed at the developments of AI-driven methods to provide closed-loop solutions for building sustainable urban and energy systems.