Tran Van Dang

Lecturer, Department Of Computer Science

Ph.D. (Informatics, National Institute of Informatics, Japan, 2022)

B.Sc. (Information Technology, Hanoi University of Science and Technology, 2017)

Email: dangtv@soict.hust.edu.vn, dang.tranvan1@hust.edu.vn

• Database
• Data Processing and Analysis
• Software Engineering

• Query languages and domain-specific languages for database management systems
• Integration, exchange, synchronization, and management of data across multiple sources
• Management of distributed data
• Program verification for database queries
• Applied machine learning and data mining

Tran Van Dang is currently a lecturer at School of Information and Communication Technology, Ha Noi University of Science and Technology. He received his PhD degree in Informatics at National Institute of Informatics (NII), Japan, in 2022. His research interests include databases, data processing and analysis, and software engineering for data management.

• Van-Dang Tran, Hiroyuki Kato, Zhenjiang Hu. Programmable View Update Strategies on Relations. In Proceedings of 46th International Conference on Very Large Data Bases (VLDB 2020), vol. 13(5), p. 726–739, Tokyo, Japan, 2020.
• Van-Dang Tran, Hiroyuki Kato, Zhenjiang Hu. A Counterexample-Guided Debugger for Non-Recursive Datalog. In Proceedings of 18th Asian Symposium on Programming Languages and Systems (APLAS 2020), p. 323-342, Virtual Conference, 2020.
• Van-Dang Tran, Hiroyuki Kato, Zhenjiang Hu. BIRDS: Programming view update strategies in Datalog. In Proceedings of 46th International Conference on Very Large Data Bases (VLDB 2020), Demonstration, vol. 13(12), p. 2897–2900, Tokyo, Japan, 2020.
• Xing Zhang, Van-Dang Tran, Kato, Zhenjiang Hu. A Cheap Implementation of Resugaring in BIRDS Based on Bidirectional Transformation. In Proceedings of Fourth Workshop on Software Foundations for Data Interoperability (SFDI 2020), Tokyo, Japan, 2020.
• Van-Dang Tran, Hiroyuki Kato, Zhenjiang Hu. A Declarative Framework for Updatable Views in Relational Databases. In Proceedings of WebDB Forum 2019, p. 85-88, Tokyo, Japan, Sep 2019. (Best student paper award)
• Cuong Ha, Van-Dang Tran, Linh Ngo Van, and Khoat Than. Eliminating overfitting of probabilistic topic models on short and noisy text: The role of dropout. In: International Journal of Approximate Reasoning, vol. 112, p. 85-104, 2019, ISSN 0888-613X.
• Giang Nguyen, Binh Minh Nguyen, Dang Tran, and Ladislav Hluchy. A heuristics approach to mine behavioral data logs in mobile malware detection system. In: Data & Knowledge Engineering, vol. 115, p. 129-151, 2018, ISSN 0169-023X.
• Dang Tran, Nhuan Tran, Giang Nguyen and Binh Minh Nguyen. A Proactive Cloud Scaling Model Based on Fuzzy Time Series and SLA Awareness. In Proceedings of International Conference on Computational Science (ICCS 2017), vol. 108, p.365-374, Switzerland, June 2017.
• Binh Minh Nguyen, Dang Tran and Giang Nguyen. Enhancing service capability with multiple finite capacity server queues in cloud data centers. In: Cluster Computing, vol. 19(4), p. 1747-1767, 2016, ISSN 1573-7543.

• Best Student Award at National Institute of Informatics (NII), Japan, 2020
• Best Student Paper Award in WebDB Forum 2019, Tokyo, Japan

• IT3090 – Database
• IT4931 – Big data storage and processing
• IT5419 – Information system integration
• IT3290 – Database lab
• IT3230 – C Basic