Aiming to build robust and scalable autonomous vehicle and robotic systems through advancedmulti-sensor fusion, real-time perception, and control within ROS frameworks.Main interests include probabilistic SLAM,policy optimization, and deep reinforcement learning for adaptive decision-making under uncertainty.Focused on designing algorithmic frameworks for resilient autonomy in GPS-denied and dynamically complex environments, emphasizing transferablepolicy learning, uncertainty-aware sensor fusion, and optimization-based motion planning for sim-to-real generalization.