My research project aims to address the critical issue of illegal and unsustainable deforestation in Indonesia, driven by timber logging and palm oil cultivation. By leveraging fine-grained remotely sensed data and geospatial analysis, I will infer the network structure of strategic interactions between concession owners. I will then use game-theoretic models and random network simulations to analyze the impact of economic factors and network topologies on deforestation practices. Finally, machine learning models will be developed to design intervention policies, promoting sustainable forestry and penalizing illegal activities. The project’s ultimate goal is to contribute to more effective data-driven decision-making for sustainable forestry.

I’m participating in SuperUROP to apply and expand my skills in data analysis, machine learning, and geospatial modeling to tackle environmental challenges. I have previous background in programming in Python and R. I am beyond excited to delve deeper into sustainable forestry practices and see how these tools can be leveraged to make a real-world impact and to contribute to innovative solutions that protect our planet’s forests.