Dr. Dianhao Zhang | Robot Collaboration Awards | Best Scholar Award

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Dr. Dianhao Zhang | Robot Collaboration Awards | Best Scholar Award

Dr. Dianhao Zhang | Robot Collaboration Awards | Nantong University | China

Dr. Zhang Dianhao is a robotics researcher and lecturer at the School of Electrical and Automation Engineering, Nantong University, recognized for his contributions to robot safety control, human–robot collaboration, autonomous navigation, and intelligent manufacturing. He holds a PhD in Robotics from Queen’s University Belfast, where he developed advanced safety–critical control mechanisms and motion-planning frameworks that integrate sensing, perception, and adaptive behavior modeling in human–robot interactive environments. His academic training, strengthened by earlier degrees in electrical engineering, forms a strong foundation for cross-disciplinary research in sensing-driven autonomous systems. Dr. Zhang has accumulated valuable professional experience as a lecturer, postdoctoral researcher, and collaborator in international programs, including participation in a major European research initiative focusing on intelligent and connected mobility. His research interests span human–machine collaboration, safety-critical control using NMPC and ECBF, multi-sensor fusion, deep learning, graph neural networks, autonomous navigation of underwater and aerial robots, intelligent perception, and digital-twin-enabled industrial automation. His technical skills include advanced control algorithm design, deep learning, behavior prediction, multi-robot coordination, digital-twin modeling, and software expertise in C++, Python, MATLAB, ROS, and other development frameworks essential for modern intelligent systems. Dr. Zhang’s academic output includes high-quality publications in IEEE Transactions on Automation Science and Engineering, Machines, the World Electric Vehicle Journal, and Measurement Science and Technology, supported by Scopus-indexed articles and an ORCID-verified portfolio. His achievements also include multiple patents as first inventor, conference presentations at leading robotics and engineering venues, and contributions to international collaborations that bridge advanced sensing, industrial automation, and robotics. His growing scholarly influence and leadership potential are reflected in his ability to integrate sensing technologies with decision-making architectures for complex robotic environments. Dr. Zhang’s awards, recognitions, and invited presentations further demonstrate his emerging standing within the robotics research community. He continues to expand his research scope through intelligent manufacturing applications, deep-sea robotics, safety-aware autonomy, and human-robot collaborative systems.

Professional Profiles: ORCID

Featured Publications 

  1. Zhang, D., Van, M., Sopasakis, P., & McLoone, S. (). Adaptive safety-critical control with uncertainty estimation for human–robot collaboration. IEEE Transactions on Automation Science and Engineering. Published 2024.

  2. Xu, Y., Yan, S., Qi, Y., Ding, Z., & Zhang, D. (). CDIF-Net: Cross-dimensional interactive fusion network with dual-branch attention for pavement crack segmentation. Measurement Science and Technology. Published 2025.

  3. Zhang, D., Van, M., Sopasakis, P., & McLoone, S. (). An NMPC-ECBF framework for dynamic motion planning and execution in vision-based human–robot collaboration. Machines. Published 2025.

  4. Xu, Y., Zhu, S., Zhang, D., Fang, Y., & Van, M. (). Safety–efficiency balanced navigation for unmanned tracked vehicles in uneven terrain using prior-based ensemble deep reinforcement learning. World Electric Vehicle Journal. Published 2025.