Shuo Xu

Anhui University, Shanghai University, Cardiff University, Shanghai Jiao Tong University

Papers

Total Citations

410

H-Index

About

Shuo Xu is a pioneering researcher at the intersection of computer vision, human-robot interaction, and bio-inspired optimization. His most impactful work centers on three-dimensional human pose estimation, where his comprehensive 2021 review has garnered 383 citations, establishing itself as a foundational resource for researchers working on articulated 3D joint localization from images and video. This work has profound implications for human motion analysis, human-computer interaction, and robotics. In healthcare robotics, Xu proposed a multimodal "human-robot integration" collaboration system designed to enable natural interaction between service robots and elderly or disabled individuals, addressing critical needs in assistive technology. Earlier in his career, Xu developed the Binary Bees Algorithm (BBA), a population-based metaheuristic inspired by honeybee foraging behavior, to solve complex NP-hard optimization problems including multiobjective multidimensional assignment for hospital service robots. This bio-inspired approach demonstrates his versatility in applying nature-inspired computation to real-world logistical challenges. Xu's research trajectory—from algorithmic optimization to human pose estimation and assistive robotics—reflects a sustained commitment to advancing autonomous systems that can perceive, interact with, and assist humans in meaningful ways.