Flavia Khatounian

CEA Paris-Saclay - Etablissement de Fontenay-aux-roses, Saint Joseph University

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About

Flavia Khatounian is a researcher whose work bridges robust system identification and autonomous robotics. Her foundational research focuses on parametric identification techniques, critically comparing methods like least squares with more robust alternatives. In her 2007 work, she demonstrated that while least squares methods are popular for their simplicity, they lack intrinsic robustness, and she provided rigorous analysis of alternative identification strategies that require deeper analytical know-how. This contribution, with over a decade of citations, established her expertise in control and estimation theory. More recently, Khatounian has advanced into autonomous mobile robotics, tackling the challenge of intuitive human-robot interaction. Her 2025 paper introduces an end-to-end sketch-guided path planning framework that uses imitation learning to translate human-drawn sketches directly into robot navigation plans. This approach eliminates the need for complex reward engineering or additional hardware, making human-guided autonomy more accessible. By combining classical control theory with modern machine learning, Khatounian’s work demonstrates a versatile trajectory from foundational identification methods to cutting-edge, user-friendly robotic systems. Her research continues to influence both theoretical understanding and practical deployment in autonomous navigation.