Fadi Al Machot
Assoc. Prof. PD. Dr. techn. habil. · Norwegian University of Life Sciences (NMBU)
Faculty of Science and Technology (REALTEK) · Ås, Norway
Machine Learning Zero/Few-Shot Learning Neural-Symbolic AI Explainable AI Temporal Data & Forecasting Lightweight Models
About
I am Assoc. Prof. PD. Dr. techn. habil. Fadi Al Machot, specializing in Zero/Few-Shot Learning, Explainable AI, Temporal Data Analysis, and Neural-Symbolic Learning with Knowledge Representation. My research translates into impactful applications in healthcare and assisted living, automotive and ADAS, smart agriculture, and bioinformatics — developing lightweight and context-aware AI solutions that bridge logic, learning, and real-world needs.
🔬 Research Group Leader — TETRA AI
Trustworthy and Efficient Transfer Learning AI (TETRA AI) — a research group at NMBU dedicated to advancing methods that make AI models both trustworthy and highly efficient. Research focuses on zero/few-shot learning, neural-symbolic reasoning, and lightweight architectures for real-world deployment.
Patent · European Research Patent No. EP2790165 — Quality Determination in Data Acquisition (2013), in collaboration with Swarco Traffic Systems, Germany. Award · Best Practice Project Award 2013 — Smart Resource-Aware Multi-Sensor Network (SRSnet).
Academic Timeline
Norwegian University of Life Sciences (NMBU), Department of Data Science (REALTEK)
Research Center Borstel – Leibniz Lung Center, Germany
University of Lübeck, Germany
University of Klagenfurt, Austria
University of Potsdam, Germany