Hadi Yazdi's research focuses on using computational methods as well as machine learning in target-driven tree planning in cities. He is interested in data-driven approaches in Urban Green Infrastructure for tree growth prediction and developing DSS (decision support systems) for tree planting suggestions.

Hadi Yazdi studied architecture and completed his Master of Science double degree from Brandenburg Technical University, Germany, and Poznan University of Technology, Poland. His master thesis was entitled “Central Courtyard Feature Extraction in Remote Sensing Aerial Images Using Deep Learning: A case-Study of Iran”. He applied object detection and image segmentation methods on aerial images in 9 different cities in Iran to collect big data on the central courtyard features for further studies and analysis. The result of his thesis was the first big dataset of more than 26,000 central courtyards and the final report is published in the "Remote Sensing" journal, special issue "Photogrammetry and Remote Sensing for Survey and 3D Reconstruction of Historical Built Landscapes".

Hadi Yazdi is now carrying the research project  Urban Green Infrustructure  funded by DFG GRK 2678/1, AOBJ:68242 Urbane Grüne Infrastruktur for his PhD study at GTLA and cooperate in the research project  Urban Green System 4.0 .