Tenglong Huang | Engineering | Best Researcher Award

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

Northwest A&F University | China

Author Profile

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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


Mr. Zonghai Chen | Engineering | Best Researcher Award

Mr. Zonghai Chen | Engineering | Best Researcher Award

University of Science and Technology of China | China

Author Profile

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Early Academic Pursuits

Chen Zonghai's academic journey commenced with a Bachelor's degree in Systems Science and Management Science from USTC, spanning from 1983 to 1988. He continued his education at USTC, achieving a Master's in Control Science and Engineering from 1988 to 1991.

Professional Endeavors

Chen Zonghai's career began as a Teaching Assistant at USTC's Department of Automation from 1991 to 1993. Progressing through the academic ranks, he served as a Lecturer from 1993 to 1995, an Associate Professor from 1995 to 1998, and has held the position of Professor since 1998. His work primarily focused on modeling, simulation, optimization of petrochemical processes, and later expanded into control of complex systems, intelligent science, robotics technology, and green energy.

Contributions and Research Focus

With a profound impact in the field, Chen Zonghai's research spans diverse areas, including modeling and control of complex systems, intelligent science, robotics technology, and green energy. His research interests also encompass fuzzy logic applications, renewable energy vehicles, and decision-making processes.

Accolades and Recognition

Chen Zonghai's exemplary contributions have earned him 13 national or local state technology awards in China. He holds credit for applying for 40 national patents and has an extensive publication record with over 450 papers and 3 monographs.

Impact and Influence

Chen Zonghai's influence extends beyond academia, with significant contributions to the technological landscape. His work on power lithium battery management systems, intelligent control technology for wind-solar hybrid energy, and simulation training systems have garnered national recognition.

Legacy and Future Contributions

As a Professor and Doctoral tutor at USTC, Chen Zonghai continues to shape the future of control science and engineering. His legacy includes numerous awards, a prolific publication record, and advancements in technology. His ongoing research projects, such as intelligent information representation and adaptation techniques for renewable energy vehicles, reflect his commitment to addressing contemporary challenges in the field.

Notable Publications

End-to-end deep learning powered battery state of health estimation considering multi-neighboring incomplete charging data 2024

A LiDAR SLAM System With Geometry Feature Group-Based Stable Feature Selection and Three-Stage Loop Closure Optimization 2023 (1)

Feature&Distribution-based LiDAR SLAM with Generalized Feature Representation and Heuristic Nonlinear Optimization 2023 (2)

Lifelong Vehicle Trajectory Prediction Framework Based on Generative Replay 2023

Two-level Battery Health Diagnosis using Encoder-decoder Framework and Gaussian Mixture Ensemble Learning Based on Relaxation Voltage 2023