PhD Candidate Mofan Zhang Wins 2nd Best Student Presentation at Sustainability Data Science Conference

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PhD candidate Mofan Zhang presented her research, “Adaptive energy planning unlocks diverse decarbonization pathways and mitigates lock-in risks,” at the fourth Sustainability Data Science Conference. Her work introduces a reinforcement learning–based framework for adaptive energy capacity expansion that accounts for endogenous technological learning, showing that adaptive planning can reduce catastrophic lock-in risks compared to traditional static approaches. Her presentation was recognized with the 2nd Best Student Presentation Award—congratulations!

Hosted by Stanford Data Science and the Stanford Doerr School of Sustainability, the conference (April 17) brings together researchers working at the intersection of data science and sustainability to address pressing environmental challenges through innovative datasets, methods, and AI-driven approaches.