Prof. Dr. Zne-Jung Lee | Data Mining | Best Researcher Award

Zne-Jung Lee is a distinguished professor at the School of Advanced Manufacturing, Fuzhou University, China. He earned his Ph.D. in Electrical Engineering from the National Taiwan University of Science and Technology in 2002. With over 240 publications, including more than 80 in SCI, SSCI, and EI-indexed journals, his research spans artificial intelligence, big data, data mining, and computational intelligence. He has made significant contributions to these fields, earning recognition as one of the World’s Top 2% Scientists from 2020 to 2024. His work focuses on developing advanced algorithms and techniques for data processing and intelligent systems.

Prof. Dr. Zne-Jung Lee | Fuzhou University | China

Profile

SCOPUS ID

ORCID ID

🎓 Education

  • Zne-Jung Lee received his Ph.D. degree in Electrical Engineering from the National Taiwan University of Science and Technology (NTUST) in Taipei, Taiwan, in 2002. His academic journey in electrical engineering laid the foundation for his contributions to the fields of artificial intelligence, big data, and computational intelligence.

💼 Experience

  • Currently, Zne-Jung Lee is a full professor at the School of Advanced Manufacturing at Fuzhou University in China. With a wealth of experience in academia, he has published over 240 papers in both journals and conferences, including more than 80 papers in SCI, SSCI, and EI-indexed publications. His extensive experience in research and teaching has established him as a prominent figure in his field.

 🏆 Honors and Awards

  • Zne-Jung Lee has been recognized for his significant contributions to the scientific community and has been consistently listed in the World’s Top 2% Scientists from 2020 to 2024. This recognition underscores his impact and excellence in research, particularly in the areas of artificial intelligence and computational intelligence.

🛠️ Skills and Certifications

  • Zne-Jung Lee possesses a broad set of skills in advanced topics such as artificial intelligence, big data analysis, data mining, and computational intelligence. His expertise enables him to explore innovative solutions to complex problems and to push the boundaries of research in these cutting-edge fields.

🔬 Research Focus

  • Zne-Jung Lee’s current research interests are centered around artificial intelligence, big data, data mining, and computational intelligence. His work delves into developing advanced algorithms and techniques that enhance data processing capabilities and support the effective application of these technologies in various domains. Through his research, he aims to contribute to the continued advancement of intelligent systems and data-driven solutions.

Conclusion

  • Zne-Jung Lee’s consistent output of impactful research, combined with his academic leadership and recognition in the scientific community, makes him a highly deserving candidate for the Best Researcher Award. His contributions not only advance his field but also have a tangible impact on the development of cutting-edge technologies that will shape future industries. His innovative approaches in AI, big data, and computational intelligence further enhance his candidacy, marking him as a top researcher in his domain.

📄Publications

  • Paper-Recorded ECG Digitization Method with Automatic Reference Voltage Selection for Telemonitoring and Diagnosis
    Authors: Wang, L.-H., Xie, C.-X., Yang, T., Chen, S.-L., Abu, P.A.R.
    Journal: Diagnostics, 2024, 14(17), 1910
  • A multi-strategy surrogate-assisted social learning particle swarm optimization for expensive optimization and applications
    Authors: Chu, S.-C., Yuan, X., Pan, J.-S., Lin, B.-S., Lee, Z.-J.
    Journal: Applied Soft Computing, 2024, 162, 111876
  • A Sustainable Development for Building Energy Consumption Based on Improved Rafflesia Optimization Algorithm with Feature Selection and Ensemble Deep Learning
    Authors: Lee, Z.-J., Pan, J.-S., Hwang, B.-J.
    Journal: Sustainability (Switzerland), 2024, 16(15), 6306
  • A Multi-objective Evolutionary Algorithm based on Hierarchical Grouping for Large-scale Multi-objective Optimization
    Authors: Liang, Q., Chu, S.-C., Song, P.-C., Lee, Z.-J., Pan, J.-S.
    Journal: GECCO 2024 Companion – Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion, 2024, pp. 343–346
  • A Sustainable Approach to Asthma Diagnosis: Classification with Data Augmentation, Feature Selection, and Boosting Algorithm
    Authors: Lee, Z.-J., Yang, M.-R., Hwang, B.-J.
    Journal: Diagnostics, 2024, 14(7), 723
Zne-Jung Lee | Data Mining | Best Researcher Award
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