Jie Wang | Flight Control | Best Researcher Award

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Assist. Prof. Dr. Jie Wang | Flight Control | Best Researcher Award

Professor, University of Science and Technology Beijing China

Jie Wang is an Associate Professor at the University of Science and Technology Beijing, specializing in intelligent and autonomous control of unmanned systems, aircraft guidance, and information security for multi-unmanned systems. He has an extensive research background in nonlinear control, event-driven control, and privacy protection. Wang has held several academic roles, including assistant researcher at City University of Hong Kong and postdoctoral fellow at the Chinese Academy of Sciences. He leads significant national research projects and has contributed significantly to journals in his field.

Profile

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🎓 Education

PhD: Tianjin University, Control Science and Engineering (2009-2014). Lecturer: Hebei University of Technology, School of Control Science and Engineering (2014-2018). Postdoctoral: Chinese Academy of Sciences, Institute of Mathematics and Systems Science (2018-2020). Associate Professor: Hebei University of Technology, School of Artificial Intelligence and Data Science (2018-2021). Current Role: University of Science and Technology Beijing, School of Intelligent Science and Technology (2021-Present)

💼Experience

Associate Professor: University of Science and Technology Beijing, School of Intelligent Science and Technology (2021-Present). Associate Professor: Hebei University of Technology, School of Artificial Intelligence and Data Science (2018-2021). Assistant Researcher: City University of Hong Kong, Department of Bioengineering (2019). Postdoctoral Fellow: Chinese Academy of Sciences, Institute of Mathematics and Systems Science (2018-2020). Lecturer: Hebei University of Technology (2014-2018). PhD: Tianjin University, Control Science and Engineering (2009-2014)

🏆 Awards & Honors 

Wang has led and participated in several prestigious scientific research projects, including the National Natural Science Foundation of China. His work has received recognition in the field of unmanned systems, hypersonic vehicles, and control systems. He has earned several distinctions, including being Principal Investigator in multiple projects such as “Autonomous Formation Assembly of Hypersonic Vehicles” and “Distributed Identification of Multiple UAV Systems.” His work is frequently published in high-impact journals like Aerospace Science and Technology and IEEE Transactions.

🔬 Research Focus

Jie Wang’s research is focused on intelligent control systems for unmanned aerial and hypersonic vehicles, with an emphasis on autonomy, formation control, and information security. His work includes event-driven control strategies, distributed identification, and collaborative formation control for multiple unmanned systems in complex environments. Wang’s projects, including those on privacy protection and robust control, aim to address challenges in both aerospace and autonomous systems, contributing to advancements in their safety and performance.

🔹Conclusion

Jie Wang is undoubtedly a strong candidate for the Best Researcher Award, given his prolific research output, leadership in pioneering scientific projects, and impactful contributions to autonomous control systems. His extensive experience with unmanned systems and hypersonic vehicles positions him at the forefront of his field. With his deep expertise and track record of innovative contributions, Jie Wang is a deserving contender for this prestigious recognition.

📚 Publications

  • Title: Distributed Average Consensus Attitude Synchronization of Multi-Rigid Spacecrafts with Predefined Time Event-Triggered Sliding Mode Control
    Authors: J. Wang, M. Yang, D. Wang, T. Wang
    Journal: Aerospace Science and Technology
    Year: 2025
    Citations: 0

 

  • Title: Event-Based Dynamic Quantized Control for Bipartite Consensus
    Authors: J. Wang, Y. Dong, B. Tian, Q. Zong
    Journal: IEEE Transactions on Systems, Man, and Cybernetics: Systems
    Year: 2024
    Citations: 0

 

  • Title: Collision Avoidance and Formation Control of Hypersonic Glide Vehicles within Predefined Time
    Authors: J. Wang, D. Wang, T. Wang, Y. Hu
    Journal: Scientia Sinica Informationis
    Year: 2024
    Citations: 0

 

  • Title: Pre-Specifiable Fixed-Time Control for Quadrotor Aircraft with Output Constraints
    Authors: X. Sun, Q. Li, J. Wang, Q. Yao
    Journal: Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
    Year: 2024
    Citations: 0

 

  • Title: Predefined-Time Based Tracking and Formation Control for Hypersonic Flight Vehicles
    Authors: D. Wang, J. Wang, J. Yuan
    Conference: [No source information available]
    Citations: 0

 

  • Title: Event-Based Robust Optimal Consensus Control for Nonlinear Multiagent System with Local Adaptive Dynamic Programming
    Authors: J. Wang, Z. Zhang, B. Tian, Q. Zong
    Journal: IEEE Transactions on Neural Networks and Learning Systems
    Year: 2024
    Citations: 20

 

  • Title: Distributed Event-Triggered Control for Bipartite Consensus under Complex Cyber-Attacks
    Authors: T. Wu, G. Cai, J. Wang, C. Mu
    Journal: International Journal of Robust and Nonlinear Control
    Year: 2023
    Citations: 7

 

  • Title: Fractional-Order Prescribed Performance Sliding-Mode Control with Time-Delay Estimation for Wearable Exoskeletons
    Authors: J. Sun, J. Wang, P. Yang, S. Guo
    Journal: IEEE Transactions on Industrial Informatics
    Year: 2023
    Citations: 17

 

 

 

Mohammad Mohammadpour | Motion planning | Best Researcher Award

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Dr. Mohammad Mohammadpour | Motion planning| Best Researcher Award

 Dr. University of Quebec at Trois-Rivières, Canada

👩‍🔬 Ph.D. in Mechanical Engineering with over eight years of specialized experience in R&D, contributing to cutting-edge projects at two renowned institutions.

 

Profile

Scopus

 

Education 🎓

Ph.D. in Mechanical Engineering (Robotics), University of Quebec at Trois Rivières, QC, Trois Rivières, Canada; May 2019-Feb 2024Master’s degree in Aerospace Engineering (Flight Dynamic & Control), Amirkabir University of Technology, Tehran, Iran; 2014Bachelor’s degree in Mechanical Engineering, Tehran, Iran; 2011

Skills 🛠️

Programming Language: Python, C++Software: ROS, Gazebo, Rviz, MATLAB & Simulink Research: Navigation and Sensor Data Fusion Motion Planning (Guidance)Movement Sciences (Kinetic & Kinematic)Dynamic Modelling and Control Machine Learning and Deep Learning Obstacle Avoidance Applications: Autonomous Mobile Robots (simulation and experiment)Learning Frameworks: Scikit-learn, Keras, TensorFlow

Experience 🚀 Robotics Engineer

Hydrogen Research Institute, University of Quebec at Trois Rivières, Trois Rivières, QC, Canada; 2019-2024Dynamic modeling, simulating, and analyzing robots’ motion Implementing motion planning (guidance) algorithms on an Autonomous Mobile Robot and an Autonomous Forklift (simulation and experiment)Developing motion planning (guidance) algorithms using deep neural networks and the robots’ kinetic models (simulation and experiment)Designing and implementing motion controllers (simulation and experiment). Research And Development Engineer Research Center of Amirkabir University of Technology, Tehran, Iran; 2015-2019Contributed to the Attitude Determination And Control System Executed MIL, SIL, PIL, and HIL simulation and testing Conducted operation and calibration tests of sensors Participated in dynamic modelling

Publications Top Notes 📝

i. Energy-efficient motion planning of an autonomous forklift using deep neural networks and kinetic model, Authors: M. Mohammadpour et al., 2023

 

ii. Energy-efficient Local Path Planning of a Self-Guided Vehicle by Considering the Load Position, Authors: Not provided, 2022

 

iii. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots, Authors: M. Mohammadpour et al., 2021

 

 

Sahar Zeinali | Autonomous systems| Best Researcher Award

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Dr. Sahar Zeinali| Autonomous systems | Best Researcher Award

Dr, Institute for Electrical Engineering in Medicine, University of Luebeck, Germany

👩‍🔬 With a Ph.D. in Control Systems from Sharif University of Technology and experience as a Researcher in Automotive Systems at the University of Lübeck, Germany, I specialize in developing driving assistance systems for autonomous vehicles. Collaborating with industry leaders like ZF Group and Infineon Technologies, my work focuses on model-based and AI-based methods to enhance energy efficiency, driving comfort, and safety. Proficient in MATLAB, Simulink, and Python, I have a strong background in software architecture design and algorithm implementation. Recognized for academic excellence and ranked among top university entrants, I bring expertise in control engineering and a dedication to innovation in automotive technology.🌟

Profile

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Orcid

 

💼Professional Experience

Researcher in Automotive Systems University of Lübeck, Lübeck, Germany 2022–Present Collaborated with ZF Group and Infineon Technologies on the EEmotion project. Developed driving assistance systems for autonomous vehicles using model-based and AI-based methods. Enhanced energy-efficiency, driving comfort, and safety. Created software and system simulation requirements. Designed software architecture and interfaces for integration and evaluation purposes. Implemented and validated algorithms in the simulation environment. Conducted Software-in-the-loop (SIL) testing. Control Engineer (Part-time) Namvaran Consulting Company, Tehran, Iran 2018–2019

🎓Education

Ph.D. in Control Systems Sharif University of Technology, Tehran, Iran 2016–2021 Visiting Researcher in Control Systems Universitat Autònoma de Barcelona, Barcelona, Spain 2019–2020 M.Sc. in Modeling, Simulation and Control Sharif University of Technology, Tehran, Iran 2013–2015 B.Sc. in Chemical Engineering Sharif University of Technology, Tehran, Iran 2009–2013 Notable Projects Design of Interaction-Aware Driving Assistance Systems for Autonomous Vehicles University of Lübeck, Lübeck, Germany 2023–Present

🖥️Skills

  • Software: MATLAB & Simulink, IPG CarMaker, Comsol Multiphysics
  • Python Packages & Libraries: TensorFlow, Keras, Scikit-learn, Gymnasium
  • Programming Language: Python, MATLAB, C++
  • Agile Methodology: Scrum
  • Development Tools: Git
  • Typesetting: LaTeX, Microsoft Office
  • Operating System: Windows, macOS

🏆Honors

Recognized for studying at Sharif University of Technology, Iran’s top university. Ranked 3rd out of over 2000 participants in the Ph.D. Entrance Exam in Iran, 2015. Directly admitted to the M.Sc. program as an Exceptional Talented Student, top 10% by GPA, at Sharif University of Technology, Tehran, Iran, 2013. Ranked 500th among more than 350,000 university entrance participants in Iran, 2009. Member of Iran’s National Elites Foundation. Admitted to Exceptional Talents Schools, 2002–2009, Tabriz, Iran.

Publications Top Notes 📝

  1. S. Zeinali, M. Fleps-Dezasse, J. King, and G. Schildbach, “Design of a utility-based lane change decision making algorithm and a motion planning for energy-efficient highway driving,” Control Engineering Practice, 146, 105881, 2024.

 

  1. X. Zhang, S. Zeinali, and G. Schildbach, “Interaction-aware traffic prediction and scenario-based model predictive control for autonomous vehicles on highways,” European Control Conference (ECC), 2024.

 

  1. X. Zhang, S. Zeinali, and G. Schildbach, “Interaction-aware traffic prediction and scenario-based model predictive control for autonomous vehicles on highways,” Accepted in IEEE Transactions on Control Systems Technology, 2024.

 

  1. S. Zeinali, M. Shahrokhi, and A. Pishro, “Observer-based controller for treatment of hepatitis C infection using fractional order model,” Mathematical Methods in the Applied Sciences, 45(17), 10689-10709, 2022.

 

  1. S. Zeinali and M. Shahrokhi, “Observer-based singularity-free nonlinear controller for uncertain systems subject to input saturation,” European Journal of Control, 52, 49-58, 2020.

 

  1. S. Zeinali, M. Shahrokhi, and A. Ibeas, “Observer-based impulsive controller design for treatment of hepatitis C disease,” Industrial & Engineering Chemistry Research, 59(43), 19370-19382, 2020.

 

  1. S. Zeinali and M. Shahrokhi, “Adaptive control strategy for treatment of hepatitis C infection,” Industrial & Engineering Chemistry Research, 58(33), 15262-15270, 2019.