Papers

4

Total Citations

115

H-Index

3

About

Pourya Pourhejazy is a leading researcher at the intersection of industrial robotics, smart manufacturing, and autonomous logistics. His work centers on optimizing complex, cyber-physical systems—from dual-arm assembly robots to drone-and-truck delivery fleets—using deep learning and multi-objective optimization. His most cited paper, “Deep learning-based optimization for motion planning of dual-arm assembly robots” (50 citations), introduces a novel framework that significantly improves coordination and efficiency in robotic assembly. He extended this line of inquiry with “Cyber-physical assembly system-based optimization for robotic assembly sequence planning” (47 citations), advancing real-time, data-driven production control. Pourhejazy’s forward-looking research on last-mile logistics, published in 2025 (16 citations), addresses the pressing challenge of e-commerce-driven supply chain transformation by integrating drones and robots with traditional truck operations. He has also contributed to sustainable manufacturing, comparing additive manufacturing alternatives for steel parts. Through his work, Pourhejazy is shaping the future of autonomous, responsive, and environmentally conscious production and distribution systems.

Research Focus

Key Achievements

3
H-Index
4
Papers
115
Total Citations
29
Avg Citations/Paper
🏆 Most Cited Paper
Deep learning-based optimization for motion planning of dual-arm assembly robots
50 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: National Taipei University of Technology, UiT The Arctic University of Norway

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago