Erdi Sayar | Control Engineering | Best Researcher Award

Mr. Erdi Sayar | Control Engineering | Best Researcher Award

Research Assistant| Technical University of Munich | Germany

Mr. Erdi Sayar is a dedicated researcher and academic in the fields of robotics, computer science, and intelligent systems. Currently pursuing his doctoral studies at the Technical University of Munich, he has developed a strong foundation in mechatronics, electrical engineering, and computer engineering through his earlier academic journey in Türkiye and Germany. His career reflects a blend of teaching, mentoring, and innovative research, leading to impactful contributions in robotics, reinforcement learning, and optimization. With several international publications and active involvement in cutting-edge projects, he continues to advance the frontiers of intelligent robotics and autonomous systems.

Publication Profile

Scopus

ORCID

Google Scholar

Education Background

Mr. Erdi Sayar began his academic path with distinction, completing his bachelor’s degree in mechatronics engineering at Kocaeli University as the valedictorian of his faculty. He further enhanced his expertise at Bochum University of Applied Sciences before advancing to RWTH Aachen University, where he earned a master’s degree in electrical engineering, information technology, and computer engineering. His thesis focused on anomaly detection in unknown environments using sensory agents, a work that received excellent recognition. He is now pursuing a doctorate in computer science at the Technical University of Munich, where he combines his interdisciplinary background to investigate advanced robotics and machine learning systems.

Professional Experience

Mr. Erdi Sayar has accumulated diverse academic and research experience across several prestigious institutions. He currently serves as a research assistant at the Technical University of Munich, where he also contributes to teaching courses on cognitive systems. Earlier, he worked as a student assistant at RWTH Aachen University and later as a research assistant at the Izmir Institute of Technology, contributing to teaching system analysis, control, and applied mathematics. His experience also includes a position at the Turkish-German University in Istanbul, where he supported teaching and research activities. Beyond academic duties, he actively mentors students at both undergraduate and postgraduate levels, guiding them in advanced robotics research.

Awards and Honors

Throughout his academic career, Mr. Erdi Sayar has consistently distinguished himself through remarkable achievements. He was ranked first in his faculty of engineering at Kocaeli University, graduating with top honors among more than a thousand students. His pursuit of lifelong learning is evident through his certifications, such as the EU open category drone pilot license and participation in international summer schools on robotics and drone technologies. He has also been recognized for his contributions to applied robotics research and teaching assistance across multiple universities. Additionally, his voluntary contributions to the community highlight his commitment to academic excellence and social responsibility.

Research Focus

Mr. Erdi Sayar’s research lies at the intersection of robotics, reinforcement learning, optimization, and control systems. His work focuses on developing intelligent methods for robotic manipulation, curriculum learning, and autonomous exploration in dynamic environments. He has contributed to the advancement of hierarchical optimization, evolutionary algorithms, and hindsight experience replay to improve robotic decision-making in complex scenarios. His publications demonstrate innovative approaches such as diffusion-based curriculum learning and evolutionary reinforcement techniques. By combining machine learning with robotic systems, his research aims to design adaptable and efficient robots capable of addressing real-world challenges in automation, autonomy, and human-robot interaction.

Publications Top Notes

  • Toward coordinated planning and hierarchical optimization control for highly redundant mobile manipulator
    Published Year: 2024
    Citation: 11

  • Curriculum learning for robot manipulation tasks with sparse reward through environment shifts
    Published Year: 2024
    Citation: 2

  • Diffusion-based Curriculum Reinforcement Learning
    Published Year: 2024
    Citation: 3

  • Multi-Objective Evolutionary Hindsight Experience Replay
    Published Year: 2024
    Citation: 1

  • Contact Energy Based Hindsight Experience Prioritization
    Published Year: 2024
    Citation: 3

Conclusion

Mr. Erdi Sayar exemplifies a modern researcher whose work bridges engineering and computer science with practical applications in robotics and intelligent systems. His academic achievements, professional experience, and strong publication record highlight a career dedicated to advancing scientific knowledge and supporting student development. With his interdisciplinary expertise, he is well-positioned to contribute to future innovations in robotics and artificial intelligence. His blend of technical excellence, mentoring, and community involvement underscores his role as a committed scholar and researcher, making meaningful contributions both in academia and society.

Dr. Pengtao Song | Control Science | Best Researcher Award

Dr. Pengtao Song | Control Science | Best Researcher Award

Student, Xi’an Jiaotong University, China

Pengtao Song is a dedicated Ph.D. student at Xi’an Jiaotong University, China, specializing in Control Science and Engineering. With a strong foundation in automation from Northeastern University, he has been actively involved in groundbreaking research in cyber-physical systems, networked control, and intelligent control of industrial processes. His expertise extends to the diagnosis and control of mechatronic systems, with a focus on improving the robustness and efficiency of complex engineering networks. As a member of the Chinese Association of Automation (CAA), Pengtao continues to contribute significantly to the field of control engineering.

Publication Profile

🎓 Education

Pengtao Song earned his B.S. degree in Automation from Northeastern University, Qinhuangdao, China, in 2020. Currently, he is pursuing his Ph.D. in the Faculty of Electronics and Information Engineering at Xi’an Jiaotong University, where he focuses on cyber-physical systems and networked control.

💼 Experience

Pengtao has been actively engaged in advanced research projects, including the prestigious National Science and Technology Major Project of China. His collaboration with the Logistics Science and Innovation Integration Development Research Center at Xi’an Jiaotong University has further enriched his experience in applied research and industrial innovation. His work has been recognized in high-impact journals such as Aerospace Science and Technology, IEEE Transactions on Automation Science and Engineering, and Nonlinear Dynamics, demonstrating his expertise in system modeling and intelligent control.

🏆 Awards and Honors

Pengtao Song’s outstanding contributions to control engineering have earned him recognition in the academic community. His publications in SCI and Scopus-indexed journals have made a significant impact, contributing to the advancement of cyber-physical systems. His research excellence has positioned him as a strong candidate for the Best Researcher Award in the field of Computer Science.

🔍 Research Focus

Pengtao’s research is centered on ensuring the efficient scheduling and robust operation of aero-engine networked systems. His work addresses challenges such as model perturbation, external disturbances, and communication delays, offering innovative control strategies like sliding mode control (SMC), H∞ control, fuzzy control, and data-driven control. His findings enhance the response performance of complex engineering systems, making significant contributions to the field of control and automation.

🚀Conclusion

Pengtao Song is an emerging leader in the field of control science and automation, contributing cutting-edge solutions to complex engineering challenges. His research in robust control strategies for networked systems has been widely recognized in top-tier journals, making a significant impact in the domain. As he continues his Ph.D. journey, his work promises to drive advancements in intelligent control, cyber-physical systems, and industrial automation.

📚 Publications

Pengtao Song has published extensively in leading journals and conferences, contributing valuable insights into control science and automation. Some of his notable works include:

Disturbance-Compensation-Based Predictive Sliding Mode Control for Aero-Engine Networked Systems With Multiple Uncertainties IEEE Transactions on Automation Science and Engineering (2025)
DOI: 10.1109/TASE.2024.3350020

Charge or Pick Up? Optimizing E-Taxi Management: A Dual-Stage Heuristic Coordinated Reinforcement Learning Approach – IEEE Transactions on Automation Science and Engineering (2024)
DOI: 10.1109/TASE.2024.3486342

Model-free event-triggered resilient control for discrete-time nonlinear systems under sparse actuator attacks via GrHDP – Nonlinear Dynamics (2024)
DOI: 10.1007/s11071-024-10477-2

Observer-based H∞ Sliding Mode Control for Networked Systems with Stochastic Communication Protocol and Packet Loss14th Asian Control Conference (ASCC 2024)
EID: 2-s2.0-85205697035

TAMTL: A Novel Meta-Transfer Learning Approach for Fault Diagnosis of Rotating Machinery – 14th Asian Control Conference (ASCC 2024)
EID: 2-s2.0-85205678502

Fuzzy H∞ robust control for T-S aero-engine systems with network-induced factors under round-robin-like protocol – Aerospace Science and Technology (2023)
DOI: 10.1016/j.ast.2023.108258

Observer-based output feedback control for networked systems with dual-channel event-triggered sampling and quantization – Journal of the Franklin Institute (2022)
DOI: 10.1016/j.jfranklin.2022.07.042