SaHosseini@su.edu.om Phone: +968 26850100 Extn: 311 Location: Rustaq building
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Dr Saeid Hosseini currently works as an Assistant Professor at Sohar University. He has won the Australian Postgraduate Award and received a Ph.D. in computer science from the University of Queensland, Australia, in 2017. He has also worked as a senior solution architect in Australia for more than ten years and obtained his M.Sc. from the Queensland University of Technology. He completed postdoctoral research studies at the Singapore University of Technology and Design and the Iran University of Science and Technology. He has published numerous scientific articles in reputable venues such as IEEE TKDE, IEEE MDM, DMKD, KBS, DASFAA, and WWWJ. His research interests as an active researcher and reviewer encompass spatiotemporal databases, dynamical processes, data and graph mining, big data analytics, recommendation systems, and knowledge graph inference.
- Ph.D. In Information Technology, University of Queensland, Australia, 2017
- MSc. In Information Technology, Queensland University of Technology, Australia, 2012
- BSc. In Software Engineering, Azad University, Tehran, Iran, 2000
- Data Science (Analytics and Deep learning)
- Database (Including Advanced DB, and Distributed DB)
- Web Application Development
- Research Methods
- Big Data Analytics
- Enterprise Resource Planning (ERP, SAP, Odoo)
- Wireless Sensors and Actuator Networks
- Enterprise Software Architecture
- Spatio-temporal databases
- Dynamical processes
- Recommendation systems
- Social network analytics
- Data Science
- Hosseini, S., Najafipour, S., Cheung, N., Yin, H., Kangavari, M.R., & Zhou, X. (2020) TEAGS: time-aware text embedding approach to generate subgraphs. Data Mining Knowledge Discovery, 1136–1174.
- Najafipour, S., Hosseini, S., Hua, W., Kangavari, M. R., & Zhou, X. (2020). SoulMate: Short-text author linking through Multi-aspect temporal-textual embedding. IEEE Transactions on Knowledge and Data Engineering.
- Ashrafi-Payaman, N., Kangavari, M. R., Hosseini, S., & Fander, A. M. (2020). GS4: Graph stream summarization based on both the structure and semantics. The Journal of Supercomputing, 1-21.
- Hosseini, S., Yin, H., Zhou, X., Sadiq, S., Kangavari, M. R., & Cheung, N. M. (2019). Leveraging multi-aspect time-related influence in location recommendation. World Wide Web, 22(3), 1001-1028.
- Hosseini, S., Yin, H., Zhang, M., Elovici, Y., & Zhou, X. (2018, June). Mining subgraphs from propagation networks through temporal dynamic analysis. In 2018 19th IEEE International Conference on Mobile Data Management (MDM) (pp. 66-75). IEEE.
- Hosseini, S., Yin, H., Cheung, N. M., Leng, K. P., Elovici, Y., & Zhou, X. (2018). Exploiting reshaping subgraphs from bilateral propagation graphs. In International Conference on Database Systems for Advanced Applications (pp. 342-351). Springer, Cham.
- Khalatbari, L., Kangavari, M. R., Hosseini, S., Yin, H., & Cheung, N. M. (2019). MCP: A multi-component learning machine to predict protein secondary structure. Computers in biology and medicine, 110, 144-155.
