Jinfeng Peng - Data management - Best Researcher Award
Northeastern University - China
AUTHOR PROFILE
🎓 ACADEMIC JOURNEY
Jinfeng Peng is a distinguished scholar in the field of Computer Science and Technology, currently pursuing his Ph.D. at Northeastern University, China. His academic journey began with a B.S. from the same institution, followed by an M.S. from Shandong University. His academic pursuits have laid a strong foundation for his innovative research in data management and deep learning.
🔍 RESEARCH INTERESTS
Peng’s research interests span across data management, data mining, data cleaning, deep learning, and reinforcement learning. His work is driven by a passion for uncovering hidden patterns in data and developing cutting-edge techniques for data analysis and processing, making significant contributions to these evolving fields.
💻 RESEARCH PROJECT EXPERIENCE
Peng has played a pivotal role in several prestigious research projects, including the National Key Research and Development Program of China and multiple grants from the National Natural Science Foundation of China. His involvement in these projects highlights his dedication to advancing research in data-driven technologies and his ability to collaborate on large-scale, impactful studies.
📚 PUBLICATIONS
Peng's research has been widely recognized, with numerous publications in top-tier journals and conferences. His notable works include papers on fraud detection in medical insurance, self-supervised data cleaning with generative adversarial networks, and reinforcement learning-based data cleaning frameworks. These publications underscore his expertise in applying advanced machine learning techniques to solve complex data challenges.
🔬 INNOVATIVE DATA CLEANING TECHNIQUES
Among Peng’s significant contributions is the development of innovative data cleaning methods. His work on GARF, a self-supervised data cleaning system, and RLclean, an unsupervised integrated data cleaning framework based on deep reinforcement learning, exemplifies his commitment to improving data quality and reliability in various applications.
🌟 RECOGNITION AND IMPACT
Jinfeng Peng’s research has not only earned him recognition within the academic community but has also had a profound impact on the field of data management. His contributions continue to influence the development of new methodologies and tools for data analysis, benefiting both academia and industry.
📈 FUTURE ASPIRATIONS
As Peng continues his academic and research career, he aims to further explore the intersections of data management and artificial intelligence, driving innovations that will shape the future of data-driven technologies. His ongoing work promises to contribute significantly to the advancement of these critical areas.
NOTABLE PUBLICATION
RLclean: An unsupervised integrated data cleaning framework based on deep reinforcement learning
Authors: J. Peng, D. Shen, T. Nie, Y. Kou
Year: 2024
Journal: Information Sciences
Comprehensive Error Detection Method for Multiple Types Errors Based on Multiple Views | 基于多视角的多类型错误全面检测方法
Authors: J.-F. Peng, D.-R. Shen, Y. Kou, T.-Z. Nie
Year: 2023
Journal: Ruan Jian Xue Bao/Journal of Software
Self-supervised and Interpretable Data Cleaning with Sequence Generative Adversarial Networks
Authors: J. Peng, D. Shen, N. Tang, H. Cui, G. Yu
Year: 2022
Journal: Proceedings of the VLDB Endowment