About
Welcome to my portfolio. I'm a researcher exploring how AI and digital twins can transform the way we manage construction environments.
I'm a research associate at the Technical University of Munich (TUM), working at the intersection of computer vision, knowledge graphs, and digital twin technologies for construction. My research focuses on combining vision-based sensing, deep learning, and graph-based representations to turn raw site data into meaningful insights for productivity, progress tracking, and automated reporting.
My work has been published in leading journals such as Automation in Construction and presented at international conferences, earning several recognitions, including the Charles M. Eastman Top PhD Paper Award (2024).
I'm passionate about translating research into practical, real-world solutions through industry collaboration and open, reproducible work.
Spatial analysis and complexity evaluation for predicting rebar installation duration
Fabian Pfitzner, Alexander Braun, André Borrmann, Frédéric Bosché. Automation in Construction, 2025, https://doi.org/10.1016/j.autcon.2025.106462.
Monitoring concrete pouring progress using knowledge graph-enhanced computer vision
Fabian Pfitzner, Songbo Hu, Alexander Braun, André Borrmann, Yihai Fang. Automation in Construction, 2025, https://doi.org/10.1016/j.autcon.2025.106117.
From data to knowledge: Construction process analysis through continuous image capturing, object detection, and knowledge graph creation
Fabian Pfitzner, Alexander Braun, André Borrmann. Automation in Construction, 2024, https://doi.org/10.1016/j.autcon.2024.105451.
- 2025
Best Paper of the Year Award: Applications Category | MDSI
Munich Data Science Institute, November 2025
- 2024
Charles M. Eastman Top PhD Paper Award | cibW78 Conference
International Council for Research and Innovation in Building and Construction, October 2024
- 2024
Best Paper Award | EC3 Conference
European Council for Computing in Construction, June 2024