Papers
3
Total Citations
72
H-Index
3
About
Nianhua Wang’s research lies at the dynamic intersection of computational fluid dynamics, bio-inspired robotics, and artificial intelligence. His primary contributions center on developing sophisticated numerical simulation methods that enable bionic fish to achieve self-propelled swimming and intelligent maneuvering. In his landmark 2020 paper (36 citations), Wang pioneered a coupling method integrating hydrodynamics, kinematics, and motion control, solving Navier-Stokes equations in an arbitrary Lagrangian-Eulerian framework to simulate deep-reinforcement-learning-driven swimming. He extended this work in 2021 (21 citations) by demonstrating how self-propelled fish models can learn to autonomously avoid obstacles in complex environments, using NACA0012 airfoil models as testbeds. These studies have significantly advanced the field of autonomous underwater vehicle design, providing a computational foundation for intelligent, adaptive locomotion. More recently, Wang has expanded into biomedical applications, contributing to a 2025 paper (15 citations) on precision surgical therapies for drug-resistant epilepsy. His work exemplifies how computational modeling and reinforcement learning can bridge engineering and medicine, offering transformative tools for both robotics and healthcare.
Research Focus
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