Daren Ho

Papers

1

Total Citations

1

H-Index

1

About

Daren Ho is a researcher at the intersection of robotics, computer vision, and advanced manufacturing, whose work focuses on developing intelligent sensing systems for quality control in industrial production. His most-cited paper, "RoboCam: Model-Based Robotic Visual Sensing for Precise Inspection of Mesh Screens" (2025), addresses a critical challenge in the emerging field of 3D-printed molded pulp packaging—a sustainable alternative to plastics. Ho’s key contribution is a model-based robotic vision framework that autonomously detects clogged pores in mesh screens, a defect that compromises the structural integrity of pulp packages. By integrating precise robotic manipulation with adaptive visual algorithms, his system achieves high-accuracy inspection where traditional methods fail. Though early in his career, this work has already garnered attention (1 citation) for its practical impact on scalable, defect-free manufacturing. Ho’s research bridges the gap between automation and material science, offering a pathway to more reliable, eco-friendly packaging production. His innovative approach to robotic sensing marks him as a promising voice in sustainable manufacturing and industrial automation.

Research Focus

Key Achievements

1
H-Index
1
Papers
1
Total Citations
1
Avg Citations/Paper
🏆 Most Cited Paper
RoboCam: Model-Based Robotic Visual Sensing for Precise Inspection of Mesh Screens
1 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 7

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago