Uploaded March 2026 | Updated September 2026, 3 days ago
Meet the Grad Student | Sina Jarahizadeh
Meet Sina Jarahizadeh, a PhD student at SUNY ESF whose research brings together drones, AI, and environmental problem‑solving.
Sina’s work focuses on using drone‑collected lidar and multispectral data to detect individual trees and estimate key forest parameters like tree height, crown diameter, volume, biomass, and more. By combining advanced sensors with artificial intelligence and machine learning, he helps make forest inventories faster, more accurate, and more accessible.
At ESF, Sina works with state‑of‑the‑art drone technology equipped with multiple sensors—an opportunity he says is rare at many institutions. Under the guidance of his advisor, Dr. Bahram Salehi, he has helped develop an AI‑based method called TreeNet, which can automatically detect individual trees from drone point clouds and extract detailed measurements. The method has already been implemented in Fayetteville, NY, with plans to expand to other towns and cities—and eventually become user‑friendly software that anyone can use, even without drone expertise.
Outside of research, Sina finds balance through community and staying active, including playing volleyball and keeping up with the latest scientific literature—both of which help inspire new ideas and solutions.
🎓 Research focus: Remote sensing, photogrammetry, drones, AI & machine learning
🌲 Applications: Tree detection, forest inventory, urban forestry
🛰 Tools: Lidar, multispectral & hyperspectral sensors
🏐 Beyond the lab: Volleyball, collaboration, continuous learning
Subscribe to learn more about the graduate students at SUNY ESF who are using cutting‑edge science and technology to address real‑world environmental challenges.
_____
Keep up with us 🌱
Instagram: @suny.esf
Facebook: @sunyesf
TikTok: @sunyesf
Esf.edu
Meet the Grad Student | Sina Jarahizadeh
Meet Sina Jarahizadeh, a PhD student at SUNY ESF whose research brings together drones, AI, and environmental problem‑solving.
Sina’s work focuses on using drone‑collected lidar and multispectral data to detect individual trees and estimate key forest parameters like tree height, crown diameter, volume, biomass, and more. By combining advanced sensors with artificial intelligence and machine learning, he helps make forest inventories faster, more accurate, and more accessible.
At ESF, Sina works with state‑of‑the‑art drone technology equipped with multiple sensors—an opportunity he says is rare at many institutions. Under the guidance of his advisor, Dr. Bahram Salehi, he has helped develop an AI‑based method called TreeNet, which can automatically detect individual trees from drone point clouds and extract detailed measurements. The method has already been implemented in Fayetteville, NY, with plans to expand to other towns and cities—and eventually become user‑friendly software that anyone can use, even without drone expertise.
Outside of research, Sina finds balance through community and staying active, including playing volleyball and keeping up with the latest scientific literature—both of which help inspire new ideas and solutions.
🎓 Research focus: Remote sensing, photogrammetry, drones, AI & machine learning
🌲 Applications: Tree detection, forest inventory, urban forestry
🛰 Tools: Lidar, multispectral & hyperspectral sensors
🏐 Beyond the lab: Volleyball, collaboration, continuous learning
Subscribe to learn more about the graduate students at SUNY ESF who are using cutting‑edge science and technology to address real‑world environmental challenges.
_____
Keep up with us 🌱
Instagram: @suny.esf
Facebook: @sunyesf
TikTok: @sunyesf
Esf.edu
