I build AI systems that turn climate evidence into policy intelligence.
My research connects two challenges: using AI to assess complex climate scenarios transparently, and combining remote sensing with machine learning to build automated, dynamic and intelligent greenhouse gas inventories.
I am a postdoctoral researcher at the Institute of Energy, Environment and Economy at Tsinghua University, supported by the Shuimu Tsinghua Scholarship. I develop AI methods that connect satellite observations, mathematical modelling and policy analysis.
Previously, I worked as a consultant with the United Nations Environment Programme on methane and climate intelligence. I earned a PhD in Mathematics and Computer Science from École Polytechnique and ISEP.
I develop analytical systems for settings where scientific complexity, institutional accountability and real-world action meet.
AI as a transparent analytical layer for exploring underexamined pathways, vetting scenario plausibility and coherence, and synthesizing large ensembles for climate assessment processes such as the Intergovernmental Panel on Climate Change (IPCC).
Remote sensing and computer vision for identifying infrastructure, attributing emission signals and updating inventories as emitting behaviour changes over time.
AI designed around the evidence standards, transparency and review processes that public institutions need to use new analytical capabilities responsibly.
Postdoctoral Researcher, Institute of Energy, Environment and Economy
Consultant, Climate & Energy Branch
PhD in Mathematics and Computer Science