Summary
Nelson Salinas is a data analyst and botanist with 13 years of experience applying statistical modeling and deep learning to plant biodiversity and conservation challenges. Trained as a PhD in Botany/Plant Biology, he has moved from field-focused systematics in the tropical Andes and NW Amazon to engineering reproducible biodiversity data pipelines and predictive models. His work spans academia and applied research at institutions like The New York Botanical Garden, American Museum of Natural History, and national research institutes in Colombia, where he supported national forest inventories and spatial modeling programs. Proficient in R, Python and C++, and experienced with MySQL and MongoDB, he combines ecological domain expertise with production-oriented data engineering and Monte Carlo/Markov simulation frameworks. Recently focused on bioinformatics and protein property prediction with neural networks, he brings a rare blend of deep ecological knowledge and modern machine learning applied to real-world conservation decisions. Based in Bogotá, he often translates complex biodiversity data into actionable insights for governments, scientists and local communities.
13 years of coding experience
9 years of employment as a software developer
Bachelor's Degree, Biology, Bachelor's Degree, Biology at Universidad Nacional de Colombia
Doctor of Philosophy (Ph.D.), Botany/Plant Biology, Doctor of Philosophy (Ph.D.), Botany/Plant Biology at The Graduate Center, City University of New York
English, Spanish