Tenglong Huang | Engineering | Best Researcher Award

Assoc. Prof. Dr. Tenglong Huang | Engineering | Best Researcher Award

Northwest A&F University | China

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🎓 Early Academic Pursuits

Assoc. Prof. Dr. Tenglong Huang began his academic journey with a Bachelor of Engineering in Automation from Henan University of Technology (2015–2019), under the mentorship of Prof. Jingjing Yan. He then pursued his doctoral studies at the Harbin Institute of Technology, one of China's top engineering institutions, where he earned his Ph.D. in Control Science and Engineering in May 2024 under the esteemed guidance of Prof. Huijun Gao. His academic training laid a strong foundation in nonlinear control, intelligent systems, and robotics, which would define his career trajectory.

👨‍🏫 Professional Endeavors

In October 2024, Dr. Huang joined the College of Mechanical and Electronic Engineering at Northwest A&F University as an Associate Professor, where he continues to lead research and mentor the next generation of scholars. His professional engagements extend to multiple prestigious editorial and scientific boards. As of 2025, he serves on the Early Career Editorial Boards of Unmanned Systems Technology and Drones, as well as editorial roles for journals like Computer Science and Technology and Automation, Control and Intelligent Systems. These appointments reflect his growing leadership in the scientific community.

🔬 Contributions and Research Focus

Dr. Huang’s research contributions span across intelligent vehicles, mobile robots, robotic manipulators, and intelligent agriculture, with core expertise in nonlinear control, motion planning, and fault-tolerant systems. Noteworthy among his contributions is the Sine Resistance Network (SRN) for autonomous vehicle path planning, which improves trajectory smoothness and performance in dynamic environments. His publication in IEEE Transactions on Automation Science and Engineering introduced a bionic reliable suspension control system using pre-specified time convergence, enabling energy-efficient and fault-resilient vehicle dynamics.

Another impactful work includes a finite-time fault-tolerant integrated motion control system that ensures convergence and resilience in autonomous vehicle navigation, published in IEEE Transactions on Transportation Electrification. His research is widely recognized for eliminating the need for complex approximation tools while enhancing system reliability and computational efficiency.

🏅 Accolades and Recognition

Dr. Huang’s excellence has been recognized through various prestigious accolades, most notably earning Second Place (National First Prize) in the 2017 World Robot Contest Fighting Robot Competition. In addition to his technical achievements, he is a respected reviewer for top-tier journals such as IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Industrial Informatics, IEEE/ASME Transactions on Mechatronics, and IEEE Transactions on Intelligent Vehicles. He is also a frequent committee member and session chair at leading international conferences such as CVCI, ICRAIC, and China Automation Conference.

🌍 Impact and Influence

Dr. Huang’s research has had a transformative impact on the fields of autonomous driving and robotics, offering robust and innovative solutions to real-world engineering problems. His bioinspired and model-free control strategies have influenced both academic research and industrial applications. His interdisciplinary approach—integrating biology-inspired dynamics, control theory, and machine intelligence—demonstrates a pioneering spirit in the global smart mobility revolution. His mentorship and cross-institutional collaborations are helping shape new directions in intelligent automation and control systems.

🔭 Legacy and Future Contributions

As a leading voice in next-generation autonomous technologies, Assoc. Prof. Dr. Tenglong Huang is set to make even greater strides. With a growing portfolio of peer-reviewed publications, editorial board memberships, and global research collaborations, his work promises to further redefine the possibilities in autonomous systems, vehicle intelligence, and resilient control architectures. His visionary contributions continue to influence smart transportation, adaptive robotics, and intelligent agriculture—paving the way for more sustainable, safe, and responsive technological ecosystems.

Publications


📝 A Safe Motion Planning and Reliable Control Framework for Autonomous Vehicles

Authors: Huihui Pan, Mao Luo, Jue Wang, Tenglong Huang, Weichao Sun
Journal: IEEE Transactions on Intelligent Vehicles
Year: 2024


📝 A Sensor Fault Detection, Isolation, and Estimation Method for Intelligent Vehicles

Authors: Tenglong Huang, Huihui Pan, Weichao Sun
Journal: Control Engineering Practice
Year: 2023


📝 Finite-Time Fault-Tolerant Integrated Motion Control for Autonomous Vehicles With Prescribed Performance

Authors: Tenglong Huang, Jue Wang, Huihui Pan, Weichao Sun
Journal: IEEE Transactions on Transportation Electrification
Year: 2023


📝 Adaptive Bioinspired Preview Suspension Control With Constrained Velocity Planning for Autonomous Vehicles

Authors: Tenglong Huang, Jue Wang, Huihui Pan
Journal: IEEE Transactions on Intelligent Vehicles
Year: 2023


📝 Sine Resistance Network-Based Motion Planning Approach for Autonomous Electric Vehicles in Dynamic Environments

Authors: Tenglong Huang, Huihui Pan, Weichao Sun, Huijun Gao
Journal: IEEE Transactions on Transportation Electrification
Year: 2022


Fan Wang | Engineering | Best Researcher Award

Dr. Fan Wang | Engineering | Best Researcher Award

Nanjing University of Information Science and Technology | China

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Early Academic Pursuits

Dr. Fan Wang's academic journey commenced with a Bachelor of Science in Mathematics from Hefei Normal University, China. This foundational education laid the groundwork for her subsequent pursuit of higher studies. She then pursued a Master's degree at the School of Mathematics, Southeast University, Nanjing, China, followed by a Doctor of Science degree, further specializing in Mathematics.

Professional Endeavors

Dr. Wang's professional endeavors reflect a global engagement with various esteemed academic institutions. She has held research positions at prominent universities such as the University of Macau, the University of Hong Kong, and Southeast University in China. Additionally, she has enriched her academic experience through international collaborations, serving as a Visiting PhD Student at Brunel University London, UK, and an Alexander von Humboldt Research Fellow at the University of Duisburg-Essen, Germany.

Contributions and Research Focus

Dr. Wang's research primarily focuses on advanced topics in control theory, with a specialization in two-dimensional systems and sensor networks. Her contributions encompass robust control and filtering techniques, distributed filtering over wireless sensor networks, and state estimation for networked systems with incomplete information. Through her publications in esteemed journals and conferences, she has significantly advanced the understanding and application of these techniques in real-world scenarios.

Accolades and Recognition

Dr. Wang's dedication and contributions to the field have been recognized through various awards and honors. Notably, she received the prestigious Alexander von Humboldt Research Fellowship of Germany in 2020 and has been acknowledged as an Excellent Reviewer of Neurocomputing in 2023. Her outstanding contributions to research have consistently earned her recognition from peers and institutions alike.

Impact and Influence

Dr. Wang's research has made a significant impact on the field of control theory and related disciplines. Her work on recursive filtering, robust state estimation, and protocol-based control has contributed to advancing the state-of-the-art in handling complex systems with limited information and communication constraints. Her findings have practical implications across diverse domains, including engineering, automation, and information technology.

Legacy and Future Contributions

Dr. Wang's legacy lies in her pioneering research and dedication to advancing the frontiers of control theory. Her work serves as a foundation for future researchers in the field, offering insights and methodologies that can address emerging challenges in complex system analysis and control. Her commitment to excellence and interdisciplinary collaboration ensures that her contributions will continue to shape the landscape of control theory and its applications in the years to come.

Notable publications

Recursive filtering for two-dimensional systems with amplify-and-forward relays: Handling degraded measurements and dynamic biases 2024

Finite-Horizon H State Estimation for Complex Networks With Uncertain Couplings and Packet Losses: Handling Amplify-and-Forward Relays 2023

Distributed Fusion Filtering for Nonlinear Time-Varying Systems Over Amplify-and-Forward Relay Networks: An H Quantized Framework 2023 (1)

Recursive locally minimum-variance filtering for two-dimensional systems: When dynamic quantization effect meets random sensor failure 2023 (5)

Robust set-membership filtering for two-dimensional systems with sensor saturation under the Round-Robin protocol 2022 (33)