Lecture at Shanghai Normal University, Chinađź“–
Dr. AN Dongdong is a lecturer at Shanghai Normal University in the College of Information and Mechanical & Electrical Engineering. He has a strong academic background with a focus on the security and verification of AI and cyber-physical systems. His work, including research on Graph Neural Networks and dynamic verification, has contributed significantly to advancing the reliability and security of AI applications. Dr. An is also actively involved in several research projects funded by prestigious institutions like the National Natural Science Foundation of China.
Profile
Scopus Profile
Orcid Profile
Education Background🎓
- Ph.D. in Software Engineering (2013–2020), East China Normal University
Supervisor: Prof. Jing Liu
- Master’s Program (2016–2018), French National Institute for Research in Computer Science and Automation (INRIA), Joint Training with Robert de Simone
- Bachelor’s in Software Engineering (2009–2013), East China Normal University
Professional Experience🌱
- Lecturer (2020–Present), Shanghai Normal University, College of Information and Mechanical & Electrical Engineering
- Researcher (2016–2018), INRIA, France, with Robert de Simone on advanced security modeling and verification techniques in AI
- Ph.D. Candidate (2013–2020), East China Normal University, School of Software Engineering, under the supervision of Prof. Jing Liu
- Verifiable and Efficient Security Training for Graph Neural Networks
- Security Modeling and Verification of Trustworthy AI Systems
- Uncertainty Modeling and Dynamic Verification for Cyber-Physical-Social Systems
Author Metrics
Publications Top Notes đź“„
1. TaneNet: Two-Level Attention Network Based on Emojis for Sentiment Analysis
- Authors: Zhao, Q., Wu, P., Lian, J., An, D., Li, M.
- Journal: IEEE Access
- Year: 2024
- Volume: 12
- Pages: 86106–86119
- Citations: 0
2. Louvain-Based Fusion of Topology and Attribute Structure of Social Networks
- Authors: Zhao, Q., Miao, Y., Lian, J., Li, X., An, D.
- Journal: Computing and Informatics
- Year: 2024
- Volume: 43(1)
- Pages: 94–125
- Citations: 0
3. HGNN-QSSA: Heterogeneous Graph Neural Networks With Quantitative Sampling and Structure-Aware Attention
- Authors: Zhao, Q., Miao, Y., An, D., Lian, J., Li, M.
- Journal: IEEE Access
- Year: 2024
- Volume: 12
- Pages: 25512–25524
- Citations: 1
4. Modeling Structured Dependency Tree with Graph Convolutional Networks for Aspect-Level Sentiment Classification
- Authors: Zhao, Q., Yang, F., An, D., Lian, J.
- Journal: Sensors
- Year: 2024
- Volume: 24(2)
- Article Number: 418
- Citations: 12
5. Sentiment Analysis Based on Heterogeneous Multi-Relation Signed Network
- Authors: Zhao, Q., Yu, C., Huang, J., Lian, J., An, D.
- Journal: Mathematics
- Year: 2024
- Volume: 12(2)
- Article Number: 331
- Citations: 2
Conclusion
Dr. Dongdong An is a highly deserving candidate for the Best Researcher Award due to his innovative contributions to AI security, particularly in the areas of Graph Neural Networks, uncertainty modeling, and dynamic verification. His academic credentials, research publications, and involvement in high-impact research projects make him a prominent figure in his field. With improvements in citation outreach, interdisciplinary collaboration, and practical applications, Dr. An has the potential to make even greater strides in the research community, further enhancing the trustworthiness and security of AI systems globally.
Final Recommendation:
Dr. Dongdong An’s pioneering work in the security of AI systems and Graph Neural Networks places him at the forefront of AI research. His commitment to improving the reliability and security of AI models makes him a worthy candidate for the Best Researcher Award.