Rongli Sun | Big Data | Best Researcher Award

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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

Scopus

Orcid

🏫 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

 

You-Jin Park | Data Science | Best Researcher Award

Published on by Academic Awards

Prof. You-Jin Park | Data science | Best Researcher Award

Prof. You-Jin Park, National Taipei University of Technology, Taiwan

🎓 Prof. You-Jin Park, PhD, is an accomplished educator and researcher in Industrial Engineering, specializing in optimization using genetic algorithms. With a doctoral degree from Arizona State University, Park has extensive teaching experience across Asia and the United States. Their research contributions include work on CDMA cellular systems and post-doctoral research in collaboration with Intel Corp. Park’s expertise spans academia and industry, with roles at Samsung Electronics and as a consultant. A dedicated professional, Park continues to advance knowledge in engineering and management, shaping future generations of engineers.

Publication profile:

Scopus

Education:

🎓 Dr. You-Jin Park pursued a comprehensive academic journey in Industrial Engineering, culminating in a PhD from Arizona State University in 2003. Their dissertation, “Application of Genetic Algorithms in Response Surface Optimization Problems,” showcased their innovative approach to optimization techniques. Prior to their doctoral studies, Park earned a Master’s degree from Hanyang University, Korea, focusing on call loss and call blocking probabilities in CDMA cellular systems. This research laid the groundwork for their subsequent contributions to the field. Park’s academic journey began with a Bachelor’s degree, also in Industrial Engineering, from Hanyang University, demonstrating a lifelong dedication to engineering excellence.

Teaching Experiences:

👨‍🏫 Dr. You-Jin Park’s teaching journey reflects a rich tapestry of academic engagement spanning various prestigious institutions and continents. Beginning as a Teaching Assistant at Hanyang University, Korea, Park’s passion for education blossomed. Subsequently, they ventured to the United States, serving as a Teaching Assistant and later as a Teaching Associate at Arizona State University. Their commitment to academia extended to leadership roles as Director of the Career Development Center at Chung-Ang University, Korea. Park’s career trajectory reached new heights with appointments as Assistant and Associate Professor at ChungAng University before assuming positions of Associate and now full Professor at National Taipei University of Technology, Taiwan, where they continue to inspire students in Industrial Engineering and Management. 🌟

Research Experiences:

🔍 Dr. You-Jin Park’s research journey showcases a dynamic exploration of industrial engineering’s forefront. As a Graduate Research Associate at Arizona State University, Park delved into cutting-edge projects, including collaborations funded by Intel Corp., highlighting their expertise in industry-academic partnerships. Their contributions extended to post-doctoral research, further honing their skills as a researcher. Notably, their role as a Researcher at the Locks Institute underscored their commitment to interdisciplinary inquiry. Park’s research endeavors have been integral in advancing knowledge in industrial engineering, bridging theory and practical applications to unlock new possibilities in optimization and beyond. 🌱

Work Experiences:

💼 Dr. You-Jin Park’s professional journey reflects a diverse blend of academic and industry experiences, showcasing versatility and expertise. As a Principal Consultant at Samsung SDS, Seoul, they provided invaluable insights and guidance, leveraging their academic background to inform strategic decisions. Their tenure as a Senior Engineer at Samsung Electronics demonstrated a hands-on approach to semiconductor technology, contributing to the company’s innovation drive. Park’s stint as a Research Scholar and Faculty Associate at Arizona State University solidified their connection between academia and industry, enriching both spheres with their insights and expertise. Their multifaceted career path underscores their adaptability and commitment to excellence in various domains. 🌟

Research Focus:

🔬 Dr. You-Jin Park’s research focus lies at the intersection of industrial engineering and applied artificial intelligence, with a particular emphasis on optimization techniques for addressing complex real-world problems. Their work spans various domains, including semiconductor manufacturing, quality engineering, and process optimization. Through innovative approaches such as hybrid resampling methods and instance density-based oversampling, Park contributes to advancing the field’s understanding of imbalanced classification problems. Their research also delves into fault detection, energy efficiency, and productivity enhancement in manufacturing processes, showcasing a commitment to improving operational effectiveness and sustainability. Park’s interdisciplinary expertise combines rigorous statistical analysis with practical applications, driving advancements in industrial engineering. 🔍

Publication Top Notes:

  1. “A novel hybrid resampling for semiconductor wafer defect bin classification” (Quality and Reliability Engineering International, 2023)
    • Year of Publication: 2023
  2. “A New Hybrid Under-sampling Approach to Imbalanced Classification Problems” (Applied Artificial Intelligence, 2022)
    • Year of Publication: 2022
  3. “A new instance density-based synthetic minority oversampling method for imbalanced classification problems” (Engineering Optimization, 2022)
    • Year of Publication: 2022
  4. “A Review on Fault Detection and Process Diagnostics in Industrial Processes” (Processes, 2020)
    • Year of Publication: 2020
  5. “Improvement of Productivity through the Reduction of Unexpected Equipment Faults in Die Attach Equipment” (Processes, 2020)
    • Year of Publication: 2020
  6. “A Graphical Model to Diagnose Product Defects with Partially Shuffled Equipment Data” (Processes, 2019)
    • Year of Publication: 2019
  7. “Performance computation methods for composition of tasks with multiple patterns in cloud manufacturing” (International Journal of Production Research, 2018)
    • Year of Publication: 2018
  8. “Optimization of pick-and-place in die attach process using a genetic algorithm” (Applied Soft Computing, 2018)
    • Year of Publication: 2018
  9. “Eco-Efficiency Evaluation Considering Environmental Stringency” (Sustainability, 2017)
    • Year of Publication: 2017
  10. “Probabilistic Graphical Framework for Estimating Collaboration Levels in Cloud Manufacturing” (Sustainability, 2017)
    • Year of Publication: 2017