Combining expertise in ecology, remote sensing, and AI
Project Leader & Aerobotany Lead
Dr. Swamy is a Research Fellow at the San Diego Zoo Institute for Conservation Research and holds a Ph.D. in tropical forest ecology from Duke University. For over 20 years, he has conducted field research in the lowland Amazon rainforests of Madre de Dios, Peru, studying plant-animal interactions, forest regeneration, and the impacts of human activity on forest diversity and structure.
He founded and leads the Aerobotany project, using drone imagery and citizen science to monitor rainforest canopy trees. Through this work, Varun demonstrates that data gathered by volunteers online can contribute to long-term ecological research and inform sustainable forest management strategies.
Varun is deeply committed to conservation education and participatory science. He has published extensively on tropical forest dynamics and biodiversity, and regularly engages with students and the public to share his insights. His long-term vision is to protect Amazonian forests by combining rigorous field research, innovative technology, and community participation.
AI/ML Engineer & Pipeline Developer
Chris is an AI/ML engineer with experience building end-to-end machine learning systems, computer vision models, and geospatial pipelines. He specializes in Python, PyTorch, scikit-learn, and GIS, with a strong track record delivering production-ready models and actionable insights for conservation projects.
Chris has worked extensively with drone imagery, training YOLO models to detect Brazil nut fruits (cocos) and linking them to per-tree harvest data. His work supports sustainable forest management by providing precise, traceable data for concession owners and conservation stakeholders.
Beyond conservation, Chris has developed AI tools for diverse real-world applications, including document scanning for visually impaired users, ranking models for candidate matching, and predictive targeting systems. His passion lies in applying advanced AI and computer vision to real-world problems and translating complex data into actionable workflows for non-technical users.