Zahra Farahzadi
Doctoral Student
Anomaly detection and diagnosis in smart greenhouses
Develops a probabilistic framework for detecting and diagnosing anomalies in greenhouses, combining physics-informed modelling, uncertainty quantification and causal reasoning — so that sensor drift can be told apart from an actual equipment failure.
Research project
Anomaly detection and diagnosis in smart greenhouses
Uncertainty-aware probabilistic AI framework for detecting and diagnosing anomalies in smart greenhouse energy systems.
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