Bio

Stefano Mingolla is a Postdoctoral Research Fellow at Carnegie Institution for Science at Stanford University. His research leverages interdisciplinary modeling and simulation to explore trade-offs, unintended consequences, and bottlenecks in large-scale technology deployment and policy interventions. By integrating insights from environmental science, engineering, data science, economics, and policy, Stefano develops data-driven frameworks that support industry leaders and policymakers in navigating uncertainty, optimizing strategies, and accelerating the transition to a sustainable energy future.

His recent work investigates pathways to achieve a net-zero and resilient agriculture system, with a particular focus on the techno-economic potential and impacts on the water-energy-land nexus of small-scale distributed ammonia production. His research methodology includes macro-scale energy system modeling and optimization, geospatial analysis, and machine learning.

Stefano holds a Ph.D. in Environmental Science, Policy, and Management from the Hong Kong University of Science and Technology and has been a Visiting Research Scholar at ETH Zurich.