Non Linear Dynamic

Nonlinear dynamics research focuses on understanding and modeling systems whose behavior doesn't scale linearly with input changes, encompassing diverse fields from physics and engineering to neuroscience and finance. Current research emphasizes developing accurate and efficient models using machine learning techniques, including deep learning architectures like Koopman-based models, neural ordinary differential equations (NODEs), and physics-informed neural networks, often leveraging data-driven approaches to capture complex system behaviors. These advancements are improving the prediction and control of nonlinear systems in various applications, such as robotics, gravitational-wave detection, and anomaly detection in power grids, leading to more robust and efficient technologies.