Qingyun Yang | Robotics and Automation | Best Researcher Award

Assoc. Prof. Dr. Qingyun Yang | Robotics and Automation | Best Researcher Award

Qingyun Yang | Zaozhuang University | China

Assoc. Prof. Dr. Qingyun Yang is a distinguished academic and researcher at the College of Mechanical and Electrical Engineering, Zaozhuang University, China, where he has served as Lecturer and Associate Professor since 2016. He earned his B.S. degree in Electrical Engineering and Automation from Nanjing Normal University in 2008, followed by an M.S. degree in Pattern Recognition and Intelligent Systems in 2011 and a Ph.D. in Control Theory and Control Engineering in 2016, both from the Nanjing University of Aeronautics and Astronautics. His professional experience is marked by a steady trajectory of excellence in teaching, research, and project leadership, especially in the fields of nonlinear systems and control, constrained control, and advanced flight control systems for near-space vehicles and UAVs. Dr. Yang’s primary research interests include robust adaptive control, prescribed performance tracking, reinforcement learning-based control strategies, fault-tolerant systems, and aerospace engineering applications. He has developed strong research skills in nonlinear dynamics modeling, control algorithm design, simulation, and experimental validation, complemented by expertise in advanced optimization, adaptive neural networks, and machine intelligence approaches. Over the years, he has authored and co-authored multiple peer-reviewed publications in high-quality SCI and EI journals such as Neurocomputing, Journal of Applied Mathematics, Control Theory and Applications, and Machines, alongside IEEE conference proceedings, demonstrating both breadth and depth in control engineering research. His notable book Robust Constrained Flight Control for Near Space Vehicles (National Defense Industry Press, 2017) further highlights his contribution to the field. Professionally, he has led several significant research projects, including funding from the National Natural Science Foundation of China (Youth Fund) and the Shandong Provincial Natural Science Foundation, as well as a Key R&D Program of Shandong Province (2025–2028) with a major focus on industrial machine tool innovation. His recognition includes multiple project leadership roles and scholarly contributions that advance both theory and practice in engineering systems control. According to Scopus, Dr. Yang has received 142 citations, 15 documents, and an h-index of 5, reflecting his growing impact in the international research community. In conclusion, Assoc. Prof. Dr. Qingyun Yang is an accomplished researcher and academic whose sustained contributions to control theory, aerospace systems, and intelligent engineering mark him as an emerging leader in his field. With his strong foundation in robust adaptive methods, active involvement in funded projects, and expanding global visibility, he is well-positioned to make transformative contributions to control engineering and interdisciplinary automation research in the future.

Profile: Scopus

Featured Publications

Cai, L., Yang, Q., & Chen, M. (2016). Robust tracking control of near space vehicles with input and output saturation. Revista de la Facultad de Ingeniería, 31(3), 282–299.

Yang, Q., & Chen, M. (2013). Composite nonlinear control for near space vehicles with input saturation based on disturbance observer. In Proceedings of the 32nd Chinese Control Conference (pp. 2763–2768). IEEE.

Yang, Q., & Chen, M. (2014). Anti-windup control for near space vehicles subject to input saturation. In Proceedings of the 33rd Chinese Control Conference (pp. 3760–3765). IEEE.

Shao, S., Chen, M., & Yang, Q. (2016). Sliding mode control for a class of fractional-order nonlinear systems based on disturbance observer. In Proceedings of the 2016 IEEE International Conference on Industrial Technology (pp. 1790–1795). IEEE.

Min, H., & Yang, Q. (2018). Study on modeling and simulation of production logistics system based on Flexsim. Academic Journal of Manufacturing Engineering, 16(2).

 

Jiatao Ding | Robotics and Automation | Best Researcher Award

Dr. Jiatao Ding | Robotics and Automation | Best Researcher Award

Postdoctoral Researcher | University of Trento | Italy

Dr. Jiatao Ding is an accomplished robotics researcher whose work focuses on optimal control, robot learning, and legged robotics, with a strong record of international collaborations and impactful scientific contributions. He obtained his Bachelor’s degree in Mechanical Engineering from Wuhan University in 2014 (Cum Laude), followed by a Doctorate in Mechatronics Engineering from Wuhan University in 2020, during which he also served as a Ph.D. Fellow at the Italian Institute of Technology (2018–2020), gaining valuable international exposure. Professionally, Dr. Ding has held prestigious research appointments including Research Assistant Scientist at the Chinese University of Hong Kong (2020–2022), Postdoctoral Researcher at Delft University of Technology (2022–2025), and currently, Postdoctoral Researcher at the University of Trento, Italy (2025–present). His research interests lie in humanoid and quadruped locomotion, reinforcement learning, and bio-inspired robotic control, where he has actively contributed to major EU H2020 projects such as Inverse, Nature Intelligence, and CogIMon, along with NSFC-funded projects in China. Dr. Ding’s research skills span advanced reinforcement learning, trajectory optimization, hierarchical and model predictive control, and adaptive locomotion strategies, which have enabled breakthroughs in versatile bipedal and quadrupedal robotic systems. His scholarly output is extensive, with publications in flagship robotics venues such as IEEE ICRA, IROS, IEEE Transactions on Robotics, IEEE/ASME Transactions on Mechatronics, and Advanced Robotics, reflecting both quality and global reach. He has served the academic community as a reviewer for leading journals and conferences, session chair at AIM 2025, associate editor at UR 2025, and guest editor for special issues in reputed journals, demonstrating leadership and commitment to advancing robotics research. His awards and honors include invited talks, editorial board appointments, and recognition through collaborative project leadership across Europe and Asia. According to Scopus, Dr. Ding has achieved 262 citations across 241 documents with an h-index of 11, underscoring both productivity and research impact. In conclusion, Dr. Jiatao Ding exemplifies an emerging global leader in robotics whose academic excellence, technical expertise, and dedication to collaborative research position him strongly for future innovations in intelligent robotic systems, making him a deserving candidate for international recognition.

Profile: Google Scholar

Featured Publications

Atanassov, V., Ding, J., Kober, J., Havoutis, I., & Della Santina, C. (2024). Curriculum-based reinforcement learning for quadrupedal jumping: A reference-free design. IEEE Robotics & Automation Magazine, 32(2), 35–48. Citations: 24

Ding, J., Han, L., Ge, L., Liu, Y., & Pang, J. (2022). Robust locomotion exploiting multiple balance strategies: An observer-based cascaded model predictive control approach. IEEE/ASME Transactions on Mechatronics, 27(4), 2089–2097. Citations: 24

Ding, J., Wang, Y., Yang, M., & Xiao, X. (2018). Walking stabilization control for humanoid robots on unknown slope based on walking sequences adjustment. Journal of Intelligent & Robotic Systems, 90(3), 323–338. Citations: 16

Ding, J., Zhou, C., Xin, S., Xiao, X., & Tsagarakis, N. G. (2021). Nonlinear model predictive control for robust bipedal locomotion: Exploring angular momentum and CoM height changes. Advanced Robotics, 35(18), 1079–1097. Citations: 26*

Ding, J., Atanassov, V., Panichi, E., Kober, J., & Della Santina, C. (2024). Robust quadrupedal jumping with impact-aware landing: Exploiting parallel elasticity. IEEE Transactions on Robotics, 40(1), 3212–3231. Citations: 13