木瓜福利影视

I am a guest researcher at Utrecht 木瓜福利影视 and a postdoctoral researcher at Wageningen 木瓜福利影视 & Research. As a quantitative ecologist, I integrate geospatial data science, artificial intelligence (AI), and ecological analysis to explore how global environmental changes affect biodiversity patterns and species interactions across spatial and temporal scales. For instance, by linking biodiversity observations to environmental variables from multiple sources, from satellite imagery and camera traps to citizen science and open-source databases, I explore and analyze the structure, dynamics, and trends of ecological communities at a multi-species level. My research activities aim to uncover how communities are organized globally and to disentangle the role of biotic/abiotic interactions in shaping large-scale biodiversity distributions. I am also interested in evaluating the effectiveness of protected areas under global change, contributing to the design of more adaptive and resilient conservation strategies. 

I am passionate about building an interdisciplinary foundation for ecological research and conservation actions. My approach brings together three key dimensions: theoretical ecology and strategic conservation planning; geospatial data science (e.g., AI, machine learning, deep learning, remote sensing, spatio-temporal modelling, as well as essential biodiversity variables-EBVs); and biodiversity observation data. Supported by advances in AI, these pillars provide a robust foundation for understanding and addressing grand multifaceted challenges of biodiversity loss in the Anthropocene. I believe that synthesizing insights across these domains is essential for developing effective, evidence-based solutions. I actively pursue collaborations across scientific disciplines to advance integrative, evidence-based solutions that strengthen global conservation efforts.

Currently, I am involved in the international , which is developing a Europe-wide repository and AI-driven pipeline to harmonize millions of professional and citizen-science images for continental-scale assessments of wildlife status and trends. Within this project, I contribute to multiple work packages focused on AI applications, characterizing multi-species community assemblage, and the development of analytical tools for biodiversity monitoring.