Junchao Zhao | Engineering and Technology | Best Researcher Award

Junchao Zhao | Engineering and Technology | Best Researcher Award

Dr Junchao Zhao, University of Science and Technology of China, China

Dr. Junchao Zhao πŸŽ“ is an outstanding fire safety researcher specializing in lithium-ion battery fire suppression and ultra-fine dry powder extinguishing agents πŸ”₯🧯. He earned his Ph.D. in Safety Science and Engineering from the University of Science and Technology of China (USTC) πŸ›οΈ, where he now serves as a postdoctoral fellow at the State Key Laboratory of Fire Science. Guided by leading experts such as Prof. Heping Zhang and Prof. Xisheng Luo πŸ‘¨β€πŸ”¬, Dr. Zhao has led and contributed to numerous national research projects. His innovative work focuses on fire dynamics, suppression technology, and energy storage safety, addressing urgent issues in aviation and electric vehicle fires βœˆοΈπŸš—. With a rich portfolio of high-impact publications πŸ“š, prestigious awards πŸ†, and collaborative projects, Dr. Zhao’s scientific excellence and dedication to fire protection science continue to influence safety engineering globally 🌍.

Publication Profile

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Education

Dr. Junchao Zhao embarked on his academic journey in Safety Engineering at Henan University of Science and Technology (2013–2017) πŸŽ“. Graduating with honors, he proceeded to pursue a Ph.D. in Safety Science and Engineering at the University of Science and Technology of China (USTC) from 2017 to 2022 πŸ›οΈ. There, he conducted cutting-edge research at the prestigious State Key Laboratory of Fire Science πŸ”¬. Under the mentorship of Prof. Heping Zhang πŸ‘¨β€πŸ«, he focused on novel fire suppression technologies, specifically targeting lithium-ion battery fires and ultra-fine dry powder extinguishing agents πŸ”₯🧯. His academic path has been marked by consistent excellence, demonstrated by numerous national-level scholarships and distinctions 🌟. Dr. Zhao’s rigorous training and specialization in fire safety have built the foundation for his current postdoctoral research, allowing him to contribute significantly to national R&D initiatives and scientific innovation in fire science and engineering.

Research & Academic Experience

Since July 2022, Dr. Junchao Zhao has been serving as a Postdoctoral Fellow at the State Key Laboratory of Fire Science, USTC 🏒. Under the co-supervision of Prof. Xisheng Luo and Prof. Heping Zhang, he leads pioneering research on extinguishing technologies for high-risk environments like aircraft power cabins ✈️πŸ”₯. His experience spans key national R&D programs, the China Postdoctoral Science Foundation, and projects funded by the National Natural Science Foundation of China πŸ’°πŸ“Š. As both principal investigator and research backbone, he has significantly contributed to the development of fire extinguishing mechanisms involving lithium-ion batteries πŸ”‹, energy storage systems, and advanced suppression agents. His academic journey includes collaborations with firefighting institutions, cross-disciplinary innovation, and application-based safety engineering solutions. Dr. Zhao’s hands-on research experience, project leadership, and commitment to safety science make him a vital contributor to fire protection technology and its real-world applications πŸš’πŸ”.

Honors & Scholarships

Dr. Zhao’s academic excellence has been recognized through numerous prestigious honors 🌟. He was awarded the Graduate National Scholarship (Top 2%) in 2019 πŸ₯‡, and received the National Scholarship (Top 0.3%) in 2015. During his studies at USTC, he earned the School Specialty First-Grade Scholarship for three consecutive years (2017–2019) πŸ…. His leadership skills were acknowledged with the Outstanding Student Cadre Award (2018) and Excellent Volunteer Award (2017) πŸ™Œ. At Henan University, he received the Excellent Graduate of Henan Province (Top 2%) in 2017 and the National Encouragement Scholarship twice 🧠✨. Further, his active involvement in student governance earned him the Student Union Work Excellence Award and Social Work Excellence Award πŸŽ–οΈ. These accolades reflect his unwavering commitment to academic, research, and social excellence β€” qualities that firmly establish him as a top candidate for the Best Researcher Award πŸ†πŸ”¬.

Research Focus

Dr. Zhao’s research focuses on fire safety science, with emphasis on lithium-ion battery thermal runaway, ultrafine dry powder extinguishing agents, and novel suppression technologies πŸ”₯πŸ§―πŸ”‹. He investigates extinguishing dynamics in confined and ventilated conditions, particularly in aircraft power cabins and energy storage systems ✈️⚑. His projects explore the design, flow behavior, and minimum extinguishing concentration of advanced agents like KHCO₃ and NaHCO₃. He also studies gas-solid transport and full-flooding spray systems for high-risk applications πŸ’¨πŸ“ˆ. By integrating material science with fire suppression mechanisms, his work bridges the gap between theory and application, offering real-world safety solutions. Dr. Zhao’s interdisciplinary approach enhances fire protection strategies in aerospace, electric vehicle, and battery storage sectors πŸš—πŸš€. Through national-level collaborations, cutting-edge experiments, and impactful publications, he contributes significantly to the safety and sustainability of next-generation energy technologies 🌱πŸ§ͺ.

Publication Top Notes

  • πŸ”₯ Insights into the particle diameter and base chosen for dry powder fire extinguishing agents – Fire and Materials, 2023

  • 🧯 An improved method to determine minimum extinguishing concentrations of ultrafine dry powder agents – Process Safety and Environmental Protection, 2023

  • πŸ”‹ Comparative study on thermal runaway inhibition of lithium-ion batteries by different extinguishing agents – iScience, 2021

  • πŸ”₯ Experimental study on thermal runaway of 18650 Li-ion battery under enclosed and ventilated conditions – Fire Safety Journal, 2021

  • ✈️ Application of ultrafine dry chemicals modified by POTS/OBS for suppressing aviation kerosene pool fire – Fire Safety Journal, 2020

  • 🌊 Superhydrophobic and oleophobic ultra-fine dry chemical agent with extended fire-protection – Journal of Hazardous Materials, 2019

  • πŸ’§ Experimental study on extinguishing lithium battery box fire using low-pressure water mist system – Journal of Safety and Environment, 2021

  • πŸ§ͺ Study on Flowability Enhancement and Performance Testing of Ultrafine Dry Powder Fire Extinguishing Agents – Fire, 2024

  • βš—οΈ Pyrolysis of a perfluoro copolymer and its HF contribution – Polymer Degradation and Stability, 2020

  • πŸ§‚ Preparation of hydrophobic/oleophobic fine NaHCO₃ and enhanced fire performance – Materials & Design, 2020

 

 

 

Jiantao Shi | Robotics and Automation | Best Researcher Award

Jiantao Shi | Robotics and Automation | Best Researcher Award

Mrs Jiayun Nie, chongqing Jiaotong University, China

Jiayun Nie is a distinguished professor at Nanjing Tech University, China, specializing in cooperative control of multi-robot systems, fault diagnosis, and fault-tolerant control of distributed systems. πŸ“‘ With a Ph.D. in Control Science and Engineering from Tsinghua University, she has made pioneering contributions to multi-agent systems, UAV adaptive control, and reinforcement learning-based fault diagnosis. βœˆοΈπŸ” Her research has led to high-impact publications on fault estimation, bipartite consensus, and deep learning models for system diagnostics. πŸ€– She has served as a research fellow at the Nanjing Research Institute of Electronic Technology and has received recognition as an Outstanding Reviewer for the Journal of the Franklin Institute (2017). πŸ“š Her latest work explores AI-driven fault-tolerant frameworks for autonomous systems and aerospace applications. πŸš€ With a stellar academic record and transformative research, she is a deserving recipient of the Best Researcher Award. πŸ…

Publication Profile

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Education

Jiayun Nie’s academic journey is marked by excellence in control science and automation engineering. She earned her Ph.D. in Control Science and Engineering from Tsinghua University (2011-2016), focusing on fault-tolerant systems and adaptive control strategies for multi-robot cooperation. πŸ€–πŸ” Her doctoral research introduced novel iterative learning algorithms for fault estimation and compensation, improving system reliability. Before this, she completed her B.E. in Electrical Engineering and Automation at Beijing Institute of Technology (2007-2011), where she laid the groundwork in robotic control, embedded systems, and automation engineering. πŸŽ›οΈβš‘ During her studies, she was actively involved in research projects on UAV dynamics and cooperative control theory, leading to early publications and innovative designs for fault-resilient robotics. πŸš€ Her strong educational foundation, combined with rigorous research, has positioned her as a global leader in fault diagnosis and control engineering. πŸ“š

Experience

Jiayun Nie has an extensive academic and research career, currently serving as a Professor at Nanjing Tech University (2021-present), where she leads groundbreaking work on distributed control and autonomous systems. πŸ€–πŸ” Prior to this, she was a Research Fellow (2019-2021) and Associate Research Fellow (2016-2018) at the Nanjing Research Institute of Electronic Technology, contributing to fault detection models for phased array radar transceivers and advanced control strategies for UAVs. βœˆοΈπŸ“‘ Her expertise in adaptive control and AI-driven fault detection has been instrumental in developing next-generation intelligent robotic networks. πŸš€ Throughout her career, she has collaborated with leading research institutions, advancing the state-of-the-art in reinforcement learning-based fault diagnosis, consensus control, and multi-agent fault-tolerant frameworks. πŸ… Her work continues to influence aerospace, robotics, and autonomous vehicular technologies, making her an authority in the field. πŸ“š

Awards and Honors

Jiayun Nie’s outstanding contributions to robotics and fault-tolerant control have earned her several prestigious accolades. πŸŽ–οΈ She was recognized as an Outstanding Reviewer for the Journal of the Franklin Institute (2017) πŸ“š, reflecting her expertise in control systems and automation engineering. πŸš€ Her innovative research on fault diagnosis in distributed robotic systems has been cited extensively, leading to multiple best paper awards at international IEEE and IFAC conferences. πŸ… She has received multiple grants and funding awards for her pioneering work in multi-agent cooperative control and AI-driven adaptive learning control. πŸ€– As a highly regarded professor and researcher, her contributions continue to impact autonomous systems, aviation safety, and smart robotics. ✈️ With her extensive publications and transformative research, she is a deserving recipient of the Best Researcher Award, recognized for her excellence in innovation and scientific advancement. πŸ†πŸ“‘

Research Focus

Jiayun Nie’s research revolves around cooperative control, fault diagnosis, and learning-based fault-tolerant strategies in autonomous systems. πŸ€– She has made significant breakthroughs in multi-robot cooperation, bipartite consensus, and AI-driven adaptive fault detection. πŸ“Š Her work in fault-tolerant control enhances resilience in UAVs and aerospace systems, ensuring robustness against unknown disturbances and failures. ✈️ She has developed deep learning and reinforcement learning models for self-healing robotic networks, transforming distributed control frameworks. πŸ… Her studies in event-based control, collision avoidance, and system stability have contributed to advancements in autonomous vehicle technology. πŸš€ By integrating data-driven methods with real-time fault estimation, her research provides solutions for smart transportation, defense, and aerospace industries. πŸ“‘ With numerous high-impact publications, Jiayun Nie’s pioneering work defines the future of adaptive robotics and autonomous systems. πŸŽ“

Publications Top Notes

  1. “A parallel weighted ADTC-Transformer framework with FUnet fusion and KAN for improved lithium-ion battery SOH prediction” πŸ”‹ (2025)
  2. “Bipartite Fault-Tolerant Consensus Control for Multi-Agent Systems with a Leader of Unknown Input Under a Signed Digraph” πŸ€– (2025)
  3. “Iterative learning based fault estimation for stochastic systems with variable pass lengths and data dropouts” πŸ“Š (2025)
  4. “A Two-Stage Fault Diagnosis Method With Rough and Fine Classifiers for Phased Array Radar Transceivers” πŸ“‘ (2024)
  5. “An intuitively-derived decoupling and calibration model to the multi-axis force sensor using polynomials basis” πŸ“Š (2024)
  6. “Event-Based Adaptive Fault Tolerant Control and Collision Avoidance of Wheel Mobile Robots With Communication Limits” πŸ€– (2024)
  7. “Reinforcement Learning-Based Fault Tolerant Control Design for Aero-Engines With Multiple Types of Faults” ✈️ (2024)