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Research Philosophy
At DISARVI, we believe that decision systems must do more than calculate outputs. Our research focuses on assessing uncertainty and recognizing the limits of available evidence to support human judgment in complex environments.
By integrating uncertain data with expert industrial knowledge, we develop adaptive and explainable cognitive systems. We prioritize Human-in-the-Loop reasoning to ensure technology enhances rather than replaces professional expertise.
Biography
Narges Moghaddasi is a lead researcher and system architect specializing in Decision Intelligence systems for high-stakes industrial environments. Her work bridges the gap between raw uncertain data and actionable evidence through the application of Bayesian reasoning, knowledge representation, and cognitive modeling.
She focuses on designing Human-in-the-Loop engines that empower experts to maintain control while navigating complexity. Her approach integrates computational intelligence with human judgment, ensuring that decision systems recognize the limits of their own knowledge and provide explainable pathways for critical actions.
Research Interests
Uncertainty-Aware Decision Intelligence
Human-in-the-Loop (HITL) Systems
Bayesian Reasoning & Uncertainty Quantification
Cognitive Modelling & Risk Intelligence
Computational Decision Optimization