Philippe Roberge

TomKat Graduate Fellow for Translational Research

Research Lab: Rob Jackson Lab, Earth System Science 

Year Awarded: 2025

Born in Canada, raised in the Middle East, Philippe Roberge is an aspiring scientist and filmmaker currently based in Stanford, California. Through a combination of technical science, communication and creativity, he hopes to change the way we fight to protect the natural world. Philippe is a Ph.D. candidate in the department of Earth System Science at Stanford University. Phil’s research focus is on large scale wildfire impacts on forest ecosystems, both in California and beyond. Through the use of new imaging techniques, AI and fieldwork, Phil’s work focuses on scalable solutions. His work in coastal redwood forests investigates how these unique ecosystems recover after unprecedented fires. Phil’s collaboration with the US Forest Service will help prioritize which species have the best statistical probability of surviving in which sites after large scale fires. Through a combination of both aerial and satellite imagery, he is investigating how forests survive and recover large scale wildfires.

Website:www.philroberge.com
LinkedIn

Megafire Resilience: Scaling California’s Fire Solutions with  Imagery, AI, and Targeted Re-Planting

California is experiencing an unprecedented increase in the size, severity and frequency of large scale wildfires. Often surpassing over 100,000 acres in size, these aptly named Megafires have outsized impacts on forest ecosystems, critical habitats for biodiversity, carbon storage, and countless socio-economic resources. Now more than ever, it is critical to better understand how forests are being affected at different timescales, and how we might increase our resilience to Megafires. Using a 3 pronged approach, Philippe’s research investigates 1) How many trees are killed by Megafires 2) How Coastal Redwoods survive Megafires and 3)Which trees regenerate best after Megafires. These projects are leveraging advancements in aerial and satellite imaging technology, as well as artificial intelligence and tradition fieldwork to devise highly scalable, low-cost solutions. These projects are supported through collaborations with the US Forest Service.