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Assoc. Prof. Dr. Mei Song | Computer Science | Best Scholar Award

Assoc. Prof. Dr Mei Song, Jiangsu Normal University, China.

Assoc. Prof. Dr. Mei Song is an accomplished academic and researcher at Jiangsu Normal University, China. Holding a Ph.D. from Shanghai Jiao Tong University, she specializes in machine learning and natural language processing. With over 40 publications in prestigious journals and conferences, she has also authored four monographs and secured multiple software copyrights. Her research projects, including the National Natural Science Foundation of China grant, emphasize innovation in FinTech and intelligent education. An active collaborator with institutions like Arizona State University, Dr. Song is a member of the China Computer Federation and a leader in advancing computational and information sciences.

Author Profile:

Scopus Profile

🎓 Education Background:

Assoc. Prof. Dr. Mei Song’s educational background reflects her dedication to academic excellence and innovation. She earned her Ph.D. in 2012 from the prestigious Shanghai Jiao Tong University, one of China’s leading institutions. Her doctoral studies laid the foundation for her expertise in machine learning and natural language processing. Further enhancing her academic credentials, Dr. Song completed a postdoctoral program at the Financial Research Institute and Credit Information Center, People’s Bank of China. These formative experiences have significantly shaped her research trajectory, equipping her with the knowledge and skills to lead cutting-edge projects in computational and financial technologies.

💼 Professional Experience:

Assoc. Prof. Dr. Mei Song has an extensive professional background in academia and research. Currently serving at Jiangsu Normal University in the School of Computer Science and Technology, she has made significant contributions to the fields of machine learning and natural language processing. Dr. Song earned her Ph.D. from Shanghai Jiao Tong University and completed a postdoctoral fellowship at the Financial Research Institute of the People’s Bank of China. Her expertise spans academic publishing, with over 40 papers, and leadership in research projects funded by prestigious organizations such as the National Natural Science Foundation of China and the Jiangsu Provincial Education Science Planning Project.

🌍Research Contributions:

Assoc. Prof. Dr. Mei Song has made significant research contributions in machine learning, natural language processing, and FinTech. She has authored over 40 academic papers in leading journals and conferences, including Neurocomputing and Systems Engineering – Theory & Practice. Her innovative methodologies, such as improved over-sampling techniques, have advanced data processing and classification. Dr. Song has led and participated in over 30 research projects, including grants from the National Natural Science Foundation of China and the China Postdoctoral Science Foundation. Additionally, she has secured multiple software copyrights and authored monographs, showcasing her dedication to impactful and applied research.

🥇Award and Honors:

Assoc. Prof. Dr. Mei Song has received numerous accolades throughout her distinguished academic career. Her contributions to machine learning and natural language processing have been recognized with funding from prestigious bodies, including the National Natural Science Foundation of China. She has also been honored for her innovative research in FinTech and intelligent education, receiving awards for excellence in academic publishing and software development. Dr. Song’s work has earned her positions on editorial boards and memberships in esteemed organizations, such as the China Computer Federation. Her awards and honors reflect her profound impact on advancing computational sciences and education technology.

Conclusion:

Assoc. Prof. Dr. Mei Song’s extensive contributions to academia and research position her as a deserving candidate for the Best Scholar Award. Her work in machine learning and natural language processing has led to over 40 impactful publications, four authored monographs, and numerous patents. Through prestigious projects like the National Natural Science Foundation of China grant, she has demonstrated exceptional innovation and leadership. Her collaborations with global institutions and active participation in professional organizations highlight her commitment to advancing science and fostering international academic exchange. Dr. Song’s achievements exemplify excellence, making her a worthy recipient of this prestigious recognition.

📚Publication Top Notes:

📘 Hierarchical Dijkstra Algorithm Based on Generalized Rule Tree for Crowdsourced Express Delivery
Huang, J., Ding, C., Wang, R., Song, M., Yang, M.
🗓️ 2024 | 🔢 0 Citations

📗 Credit Risk Prediction Based on Improved ADASYN Sampling and Optimized LightGBM
Song, M., Ma, H., Zhu, Y., Zhang, M.
🗓️ 2024 | 🔢 0 Citations

📙 A Dynamic Interest-Aware Message-Passing GCN for Recommendation
He, W., Zhu, Y., Song, M., Wu, Z., Hao, G.
🗓️ 2024 | 🔢 0 Citations

📕 An Adaptive Learning Feature Model Validation Methodology Based on Formal Methods
Wang, C., Zhu, Y., Song, M.
🗓️ 2023 | 🔢 1 Citation

📘 Chinese Nested Named Entity Recognition Based on Boundary Prompt
Li, Z., Song, M., Zhu, Y., Zhang, L.
🗓️ 2023 | 🔢 3 Citations

📗 A Review of 3D Reconstruction from High-Resolution Urban Satellite Images
Zhao, L., Wang, H., Zhu, Y., Song, M.
🗓️ 2023 | 🔢 19 Citations

📙 Fixed-Time Bipartite Consensus of Nonlinear Multi-Agent Systems Under Directed Signed Graphs with Disturbances
Xu, Z., Liu, X., Cao, J., Song, M.
🗓️ 2022 | 🔢 27 Citations

📕 Analysis and Verification of Bisimulation Relationship for Learning Time-Behavior Sequence
Feng, S., Zhu, Y., Song, M., Gao, Y.
🗓️ 2022 | 🔢 0 Citations

📘 Research on Trust Formation of Dissimilar Source Information Within G2B Infomediary
Song, M., Zhang, P.-Z., Fan, J.
🗓️ 2015 | 🔢 1 Citation

📗 An Objective Measurement of Information Value Using Application Traces in Infomediary
Song, M., Wang, J.
🗓️ Year Unavailable | 🔢 Citation Data Not Listed

 

Mei Song | Computer Science | Best Scholar Award

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