Hongli Li

Hongli Li's work centers on the mathematical theory of neural networks and complex dynamical systems, particularly analyzing when and how such networks reach synchronized or stable behavior, including systems with fractional-order dynamics (a generalization of ordinary calculus used to model memory and delay effects) and time delays. Recent output also includes applied prediction and classification projects, such as forecasting renewable energy trends and applying machine learning to biological, agricultural, and oceanographic data. This suggests a primary focus on control theory and dynamical systems analysis, with some collaborative work extending these methods into applied domains.

Publication output has grown substantially over the last decade, rising from roughly 12 papers per year in 2017 to 57 in 2025, indicating strong and increasing research activity.

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