Julian Alberto Equihua Benitez

Julián Equihua is a doctoral candidate at the Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research (UFZ). He focuses on developing tools to apply reinforcement learning to landscape ecology challenges, particularly ecosystem service modeling and sustainable land use. Previously, he worked as a data scientist at CONABIO (Mexican Commission for the Knowledge and Use of Biodiversity) from 2014 to 2021.

• Education:
  • Master's in Geomatics, CentroGeo, Mexico
  • Diploma in Applied Statistics, ITAM, Mexico
  • Bachelor's in Applied Mathematics, ITAM, Mexico

Research Interests center on integrating machine learning with ecological modeling, emphasizing sustainable land management and the interplay between biodiversity and ecosystem services. His work aligns with UFZ's focus on computational landscape ecology and environmental sustainability.

Scientific Awards include CONACyT scholarships and DAAD grants for research projects. He contributes to interdisciplinary initiatives like the GLUES project and collaborates with institutions such as the German Centre for Integrative Biodiversity Research (iDiv).