Dr Mingzhong Wang joined USC in 2015. Before that, he worked as a Lecturer at Beijing Institute of Technology in China. He has developed and taught a wide range of subjects, covering data analysis, artificial intelligence, algorithm design, and computational theory.
His current research interests include machine learning in general and knowledge graphs and deep reinforcement learning in specific. He is also interested in mobile computing and telepresence robots. He has won a grant from Chinese National Science Foundation, studying service-oriented scientific workflow scheduling in cloud environment. He has been the principal investigator of several industrial-funded projects, focusing on enterprise information system and business management system. He has won the Best Paper Award in 2013 (32nd) International Performance Computing and Communications Conference.
Professional memberships
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ACM |
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IEEE |
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CCF |
Awards
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Best Paper Award, 2013, 32nd International Performance Computing and Communications Conference (IPCCC 2013). |
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1st Prize, 2012, (China) National Undergraduate Information Security Contest. |
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Faculty Advisor Award, 2012, (China) National Undergraduate Information Security Contest. |
Potential research projects for HDR and Honours students
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Machine learning |
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Analysis and mining of mobile data |
Research grants
| Project name | Investigators | Funding body | Year | Focus |
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| Cloud-based Long-lived and Instance-intensive Workflow Management System | Mingzhong Wang, CI | Chinese National Science Foundation (A$44,000) | 2012–2014 | Management of large scale workflows in cloud and service environments |
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Service Component Architecture-based Business Management System |
Mingzhong Wang, CI |
China Electronics Technology Group Corporation |
2013 |
Design and implementation of business management systems with Service Component Architecture |
Research areas
- Machine learning
- Knowledge graphs and deep reinforcement learning
- Mobile and IoT systems
- Telepresence robots
Teaching areas
- Data Management and Analysis
- Programming
- Machine Learning
You can view Mingzhong's publications at:
* This is an external website and the University of the Sunshine Coast is not responsible for the content.
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X. Li, H. Zang, X. Yu, H. Wu, Z. Zhang, J. Liu, and M. Wang, “On improving knowledge graph facilitated simple question answering system,” Neural Computing and Applications, Mar. 2021, doi: 10.1007/s00521-021-05762-9. |
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H. Hong, X. Li, and M. Wang, “GANE: A Generative Adversarial Network Embedding,” IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 7, pp. 2325–2335, Jul. 2020, doi: 10.1109/TNNLS.2019.2921841. |
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L. Zhang, X. Li, S. Chen, H. Zang, J. Huang, and M. Wang, “Universal Value Iteration Networks: When Spatially-Invariant Is Not Universal,” AAAI, vol. 34, no. 04, pp. 6778-6785, Apr. 2020, doi: 10.1609/aaai.v34i04.6157. |
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X. Li, D. Han, J. He, L. Liao, and M. Wang, “Next and Next New POI Recommendation via Latent Behavior Pattern Inference, ” ACM Transactions on Information Systems, vol. 37, no. 4, Sep. 2019, doi: 10.1145/3354187. |
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R. Ye, X. Li, Y. Fang, H. Zang, and M. Wang, “A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment,” IJCAI 2019, pp.4135-4141, Aug. 2019, doi: 10.24963/ijcai.2019/574. |
Dr Mingzhong Wang’s specialist areas of knowledge include machine learning in general and knowledge graphs and deep reinforcement learning in specific. He is also interested in mobile computing and telepresence robots.