Gianfranco Villamonte

Designed decision-support logic for biochar-based carbon removal in Brazilian agriculture, structuring carbon removal claim assumptions around permanence, monitoring, registries, and deployment constraints. Compared biochar with alternative pathways and engaged farmers and market actors to identify feasibility gaps and scaling requirements.

Scaled LCA-based product assessment infrastructure from ~83 to ~10,000 datasets/month by developing LCI modeling workflows, covering 70,000+ material datasets total. Translated 500,000+ product assessments into client-facing insights, led ISO 14040/44/67 and GHG Product Standard validation with SGS, and built traceability, data-quality, and anomaly-detection workflows (including embedding/LLM-assi

Led biodiversity, ecosystem services, land-use, and environmental monitoring for large-scale mining and gas projects and renewable energy developments, building geospatial workflows to assess land-use change and 10+ year NDVI/EVI vegetation dynamics. Developed biodiversity management, monitoring, and offset strategies aligned with IFC Performance Standard 6, managed 5-person technical teams, and p

Co-developed a circularity framework linking agroforestry and food waste management in Peru, estimating ~92,000 tCO2e mitigation potential using IPCC factors with GIS and R-based analysis. Reviewed 400+ studies to identify five-decade research trends and gaps across coffee, cacao, and Brazil nut systems and presented findings at the 5th World Congress on Agroforestry.

MSc-level coursework in Data Science & Decision Analysis (90 ECTS), covering data science, decision-support systems, risk analysis, quantitative modelling, and scientific communication with applied LLM use.

MSc in Forest and Nature Conservation. Thesis focused on drivers of forest regeneration in Amazonian mine lands using field, spatial, and ecological data, supported by a FONA fieldwork grant.

Grade: 15.5/20 (graduated 2nd in class)

BSc in Biology covering ecology, biostatistics, ecosystem modelling, environmental impact assessment, plant physiology, and soil science. Thesis used MaxEnt and GIS for niche modelling of Peruvian podocarp species under climate-change scenarios.