Research keywords:
State estimation, Inertial navigation, Kalman filtering, Cyber-physical security, Active defense, Artificial intelligence in navigation and mobility, Navigation under cosmic radiation, Traffic state estimation, Large scale multimodal mobility networks.
Summary of Research Work
Key challenges in navigation and their solutions
My research centers on advancing the field of navigation and estimation, with a particular focus on addressing the fundamental challenges that arise in real-world applications. I investigate attitude estimation, exploring both the theoretical frameworks and practical solutions that improve the accuracy and reliability of orientation measurements. In addition, my work on velocity and position estimation seeks to overcome the inherent difficulties in tracking motion in dynamic and uncertain environments. Another core area of my research is magneto-inertial navigation in the presence of unknown inputs, where I develop methods to maintain navigation accuracy even under unpredictable disturbances. Beyond these specific topics, I actively contribute to broader research related to navigation, integrating insights from multiple approaches to design robust, high-performance systems. Through this work, I aim to bridge the gap between theory and application, advancing navigation technologies that can operate reliably across diverse and challenging conditions.
Modeling, Estimation, and Classification in Urban and Multimodal Mobility Systems
My research further encompasses the modeling, estimation, and control aspects of intelligent transportation systems, with the aim of improving the efficiency, safety, and sustainability of modern mobility networks. A key area of focus is traffic state estimation in road transportation systems, where I design algorithms capable of fusing heterogeneous data sources — such as loop detectors, GPS trajectories, and connected vehicle data — to provide accurate, real-time assessments of traffic conditions. This work supports predictive traffic management and adaptive control strategies for mitigating congestion and enhancing urban mobility. In parallel, I explore the reliable classification of soft urban mobility modes, including walking, cycling, and emerging micro-mobility forms such as e-scooters. This research addresses the challenges of sensor uncertainty, behavioral variability, and environmental complexity to achieve robust mode detection and promote the integration of sustainable transport options. Another major strand of my research concerns modeling and estimation for large-scale multimodal mobility networks. Here, I develop methods that capture the interactions between various transportation layers — private vehicles, public transit, and soft mobility — within a unified estimation framework. This holistic approach enables better understanding and management of network dynamics in complex urban environments. Ultimately, my goal is to advance data-driven and model-based methodologies that enable the design of adaptive, resilient, and human-centered mobility systems, contributing to the future of smart cities and sustainable transportation.”
Cyber-Physical Security in Navigation and Active Defense Strategies
4.4.1 Cyber-Physical Security: Robust Estimation and Protection Against Attacks
4.4.2 Active Defense Strategies in Cyber-Physical SystemsControl Problems in Physical Systems
4.5.1 Modeling and Control of the Phosphorite Sintering Process Using Grey System Theory
4.5.2 Adaptive and Robust Approaches for Space Vehicle Trajectory Control
4.5.3 Decentralized and Robust Approaches for the Control of Switched Systems
4.5.4 Fuzzy Control for Autonomous Navigation of Mobile Robots