Rongli Sun | Big Data | Best Researcher Award

Published on by Global Academic Awards

Dr. Rongli Sun | Big Data | Best Researcher Award

Dr. Rongli Sun, Chongqing University of Posts and Telecommunications, China

Dr. Rongli Sun is a dedicated researcher at Chongqing University of Posts and Telecommunications, China 🇨🇳, specializing in Big Data Mining and Life Estimation Algorithms for New Energy Vehicles 🚗🔋. His expertise lies in battery State of Health (SOH) estimation using advanced models like BiGRU-Attention and neural networks 🧠. Proficient in Matlab, Python, and C, he has published in top journals such as Energy and Journal of Power Sources 📚. Passionate about sports, he enjoys basketball 🏀 and marathon running 🏃‍♂️. Dr. Sun’s work significantly contributes to electric vehicle sustainability and intelligent battery management systems.

Publication Profile

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🏫 Employment

Dr. Rongli Sun has been serving at the School of Computer Science and Technology at Chongqing University of Posts and Telecommunications, China 🇨🇳. In this role, he actively contributes to cutting-edge research in Big Data Mining, Neural Networks, and Battery Life Estimation for New Energy Vehicles 🔋🚗. His academic involvement includes both teaching and guiding research projects, fostering innovation in intelligent energy systems 💡. Through his position, Dr. Sun continues to advance sustainable technologies and smart mobility solutions, helping shape the future of eco-friendly transportation and battery diagnostics 🌱🔧

📚 Academic Contributions

Dr. Rongli Sun has made notable contributions to the field of battery health diagnostics through his extensive research and publications 📖. He has authored several peer-reviewed journal articles and international conference papers, demonstrating expertise in data-driven approaches and intelligent algorithms 🔍🧠. His works are featured in high-impact journals like Energy, Journal of Power Sources, and Journal of Energy Storage 📑. Notably, his 2025 article in Energy introduced the BiGRU-Attention model, showcasing advanced deep learning applications in real-world lithium-ion battery State of Health (SOH) estimation 🔋📊. His research supports smarter, more sustainable energy systems 🌱

🔬 Research Focus

Dr. Rongli Sun focuses his research on Big Data Mining and Life Estimation Algorithms for New Energy Vehicles 🚗🔋, addressing critical challenges in energy efficiency and battery longevity. His work primarily centers on the State of Health (SOH) estimation of lithium-ion and lead-acid batteries, aiming to improve predictive maintenance and operational safety ⚙️📊. By leveraging large-scale data and intelligent models, Dr. Sun contributes to the advancement of sustainable energy and smart mobility technologies 🌱🚀. His innovative methods play a key role in enhancing the reliability and performance of electric vehicle power systems worldwide 🌍

Conclusion

Dr. Rongli Sun is highly suitable for the Research for Best Researcher Award. His cutting-edge contributions to battery health estimation in new energy vehicles, solid publication record, and alignment with global sustainability goals make him a compelling nominee

Publication Top Notes

  • 📘 Sun R, Chen J, Li B, et al. State of health estimation for Lithium-ion batteries based on novel feature extraction and BiGRU-Attention model. Energy, 2025

  • 📘 Sun R, Chen J, Piao C. Battery health features extraction and state of health estimation based on real-vehicle operation data. Journal of Power Sources, 2024

  • 📘 Piao C, Sun R, Chen J, et al. A feature extraction approach for state-of-health estimation of lithium-ion battery. Journal of Energy Storage, 2023

  • 📘 Sun R, Xie J, Piao C. A multi-scenario driving range prediction method for electric vehicles in low temperature. Proceedings of the 16th International Conference on Computer Science and its Applications (CSA), 2024

  • 📘 Sun R, Liu Q. Research on Electric Vehicle State of Health Estimation Based on Multi-Feature Attribute Data Mining. Proceedings of the 4th International Conference on Electronics Technology and Artificial Intelligence (ETAI), 2025

  • 📘 Sun R, Hu P, Wang R, et al. A new method for charging and repairing Lead-acid batteries. IOP Conference Series: Earth and Environmental Science, 2020

 

Zhidong CAO | Data Science | Best Researcher Award

Published on by Global Academic Awards

Mr. Zhidong CAO | Data Science |  Best Researcher Award

Zhidong CAO at Institute of Automation, Chinese Academy of Sciences, China

Zhidong CAO is a renowned professor and principal investigator at the National Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. With a Doctor of Science degree, he has made significant contributions to the field of artificial intelligence and has been recognized for his work in various national and international platforms.

Profile

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Education

Zhidong CAO earned his Ph.D. from the Institute of Geographic Sciences and Natural Resources Research at the Chinese Academy of Sciences in 2008. He also holds a Master’s degree and a Bachelor’s degree from Changsha University of Science and Technology, completed in 2005 and 2001 respectively.

Research Focus

His research interests lie primarily in the areas of multimodal artificial intelligence systems, social computing, and geographic information analysis. He has been instrumental in several key national scientific and technological projects, including the National Medium- and Long-term Scientific and Technological Development Plan (2021-2035) and the New Generation Artificial Intelligence Strategic Plan.

Professional Journey

Zhidong CAO began his professional journey as a Postdoctoral Fellow at the Institute of Automation, Chinese Academy of Sciences, in 2008. He progressed to become an Assistant Researcher in 2010, then an Associate Researcher in 2011, and has been serving as a Researcher since 2020. His roles have seen him engage deeply with various research projects and contribute significantly to the field of automation and artificial intelligence.

Honors & Awards

Throughout his career, Zhidong CAO has received numerous prestigious awards. Notable among these are the Beijing Science and Technology Progress Award (Second Prize, 2022), the China Surveying and Mapping Society Science and Technology Award (Grand Prize, 2021), and the Chinese Society of Simulation Natural Science First Prize (2018). His contributions have also been recognized by the Chinese Association of Automation and the Chinese Preventive Medicine Association.

Publications Noted & Contributions

Zhidong CAO has an impressive portfolio of over 120 research papers published in leading domestic and international journals and conferences. He has also authored three books, further establishing his expertise in his field. His research has earned him six scientific and technological awards, underscoring his significant contributions to the advancement of artificial intelligence and related domains.

  1. Coordinated Cyber Security Enhancement for Grid-Transportation Systems With Social Engagement
    • Journal: IEEE Transactions on Emerging Topics in Computational Intelligence
    • DOI: 10.1109/TETCI.2022.3209306
    • Contributors: Pengfei Zhao, Shuangqi Li, Paul Jen-Hwa Hu, Zhidong Cao, Chenghong Gu, Da Xie, Daniel Dajun Zeng
    • Summary: This article discusses methods for enhancing cybersecurity in grid-transportation systems through coordinated efforts and social engagement. It emphasizes the importance of integrating social factors and community involvement in cybersecurity strategies.
  2. Energy-Social Manufacturing for Social Computing
    • Journal: IEEE Transactions on Computational Social Systems
    • DOI: 10.1109/TCSS.2024.3379254
    • Contributors: Alexis Pengfei Zhao, Shuangqi Li, Yanjia Wang, Paul Jen-Hwa Hu, Chenye Wu, Zhidong Cao, Faith Xue Fei
    • Summary: This article explores the concept of energy-social manufacturing, which integrates energy systems with social computing to enhance efficiency and sustainability. The research highlights the role of social computing in optimizing energy production and consumption.
  3. Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks
    • Journal: IEEE Transactions on Computational Social Systems
    • DOI: 10.1109/TCSS.2023.3306014
    • Contributors: Tianyi Luo, Duo Xu, Zhidong Cao, Pengfei Zhao, Jiaojiao Wang, Qingpeng Zhang
    • Summary: This study models the interactions and propagation dynamics of information, behavior, and disease within multilayer heterogeneous networks. It provides insights into how these elements influence each other and spread across different network layers.
  4. Socially Governed Energy Hub Trading Enabled by Blockchain-Based Transactions
    • Journal: IEEE Transactions on Computational Social Systems
    • DOI: 10.1109/TCSS.2023.3308608
    • Contributors: Pengfei Zhao, Shuangqi Li, Zhidong Cao, Paul Jen-Hwa Hu, Chenghong Gu, Xiaohe Yan, Da Huo, Tianyi Luo, Zikang Wang
    • Summary: This article examines how blockchain technology can facilitate socially governed energy hub trading. It discusses the implementation of blockchain-based transactions to enhance transparency, security, and efficiency in energy markets.
  5. A Cross-Lingual Transfer Learning Method for Online COVID-19-Related Hate Speech Detection
    • Journal: Expert Systems with Applications
    • DOI: 10.1016/j.eswa.2023.121031
    • Contributors: Lin Liu, Duo Xu, Pengfei Zhao, Daniel Dajun Zeng, Paul Jen-Hwa Hu, Qingpeng Zhang, Yin Luo, Zhidong Cao
    • Summary: This research presents a method for detecting COVID-19-related hate speech online using cross-lingual transfer learning. The study demonstrates the effectiveness of the proposed method in identifying hate speech across different languages, aiding in the fight against online misinformation and discrimination.