Papers

2

Total Citations

7

H-Index

1

About

Baixiang Zhao is a rising interdisciplinary researcher whose work bridges orthopaedic biomechanics and human-robot interaction. His primary research areas include artificial intelligence in orthopaedic surgery, spinopelvic biomechanics, and human-robot collaboration (HRC) in industrial settings. Zhao’s most notable contribution is his pioneering application of supervised learning algorithms to predict impingement risk in total hip arthroplasty (THA) patients by incorporating individual spinopelvic mobility and phenotype—a novel approach that addresses a critical gap in personalized implant positioning. This work, published in 2024 and already garnering 6 citations, demonstrates the potential of AI to enhance surgical precision and reduce instability complications. In parallel, Zhao has advanced the field of HRC by developing a non-intrusive mental workload evaluation concept, aiming to optimize human acceptance and productivity when working alongside collaborative robots. Though early in his career, his dual focus on data-driven surgical planning and human-centered robotics reflects a forward-thinking approach to engineering challenges. With growing citation impact and a clear trajectory toward translational applications, Zhao is establishing himself as a researcher to watch at the intersection of biomechanics, AI, and human factors engineering.

Research Focus

Key Achievements

1
H-Index
2
Papers
7
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Is it feasible to develop a supervised learning algorithm incorporating spinopelvic mobility to predict impingement in patients undergoing total hip arthroplasty?
6 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University of Strathclyde

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago