Mingxin Hou

Guangdong Ocean University, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Harbin Institute of Technology

Papers

Total Citations

H-Index

About

Mingxin Hou is a researcher at the forefront of marine robotics and intelligent automation, with a focus on solving critical challenges in underwater and deep-sea environments. Their work bridges deep learning, robotic manipulation, and autonomous systems to enhance marine ecological monitoring and aquaculture efficiency. Hou’s most cited paper, “A deep learning approach for object detection of rockfish in challenging underwater environments” (2023, 11 citations), introduces a novel deep learning framework for detecting rockfish in low-visibility, complex underwater settings—a key tool for combating overfishing and preserving marine biodiversity. In “Design of water surface collection robot based on deep sea cage culture” (2022, 8 citations), Hou addresses the dangerous and inefficient manual collection of floating debris and dead fish in deep-sea aquaculture by designing an autonomous surface robot, significantly improving safety and operational efficiency. Earlier foundational work, “Analysis of the multi-finger dynamics for robot hand system based on EtherCAT” (2014, 7 citations), developed a multi-finger dynamics model with Lagrangian multiplier control, validated on an FPGA-based EtherCAT platform, advancing dexterous manipulation for robotic hands. With a cumulative impact of 26 citations across these key studies, Hou’s research is instrumental in integrating AI and robotics for sustainable marine resource management, offering practical solutions for environmental conservation and industrial automation.