Papers
2
Total Citations
20
H-Index
2
About
Hai Dinh-Tuan is a researcher at the forefront of modernizing industrial systems through software architecture and data analytics. His primary research areas include microservices-based architectures, industrial data analytics, and decentralized manufacturing paradigms. His most notable contribution is the development of **MAIA (Microservices-based Architecture for Industrial Data Analytics)**, a framework designed to help manufacturers transition from mass production to customized, decentralized operations. By leveraging microservices, MAIA enables more efficient, scalable, and flexible data analytics in industrial settings. This work has garnered significant attention, with his flagship 2019 paper on MAIA accumulating **18 citations**, reflecting its growing influence in the field of industrial informatics. Dinh-Tuan’s research directly addresses the pressing need for agile, data-driven manufacturing systems, making him a key voice in the intersection of software engineering and Industry 4.0. His contributions are particularly valuable for researchers and practitioners seeking to harness modern software paradigms for real-world industrial challenges, positioning him as an emerging authority in the evolution of smart factories and decentralized production ecosystems.
Research Focus
Key Achievements
Top Papers
- 1MAIA: A Microservices-based Architecture for Industrial Data Analytics18 citations · 2019
- 2MAIA: A Microservices-based Architecture for Industrial Data Analytics2 citations · 2019