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Michael Sheng

Professor

 https://orcid.org/0000-0002-3326-4147
  • 5068 Citations
  • 29 h-Index
20012021
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Personal profile

Biography

Dr. Michael Sheng is a full Professor and Head of Department of Computing at Macquarie University. Before moving to Macquarie, Michael spent 10 years at School of Computer Science, the University of Adelaide. Michael holds a PhD degree in computer science from the University of New South Wales (UNSW) and did his post-doc as a research scientist at CSIRO ICT Centre. From 1999 to 2001, Sheng also worked at UNSW as a visiting research fellow. Prior to that, he spent 6 years as a senior software engineer in industries. 

Prof. Michael Sheng's research interests include Web of Things, Internet of Things, Big Data Analytics, Web Science, Service-oriented Computing, Pervasive Computing, and Sensor Networks. He is the recipient of ARC Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003).

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Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2016 2021

Diverse and Dynamic Trust Evaluation in Online Social Networks

Liu, G. & Sheng, Q.

1/01/19 → 31/12/20

Project: Other

Modelling and defence against malicious information propagation

Wu, J., Sheng, Q. & Zhang, C.

1/01/19 → 31/12/20

Project: Other

Trust Evaluation and Spam Detection on Online Social Networks

Yang, J., Sheng, Q., Wu, J., Collins, A., Nepal, S. & Paris, C.

3/12/18 → 31/08/21

Project: Other

Scalable Recommender System for Big Data Environment using Deep Learning

Tran, D. & Sheng, Q.

16/07/18 → 14/12/20

Project: Other

Building Intelligence into Online Video Services by Learning User Interests

Zhou, Y. & Sheng, Q.

29/06/18 → 28/06/21

Project: Other

Research Outputs 2001 2019

A fitness-based evolving network for Web-APIs discovery

Adeleye, O., Yu, J., Yongchareon, S., Sheng, Q. Z. & Yang, L. H., 29 Jan 2019, Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2019. Association for Computing Machinery, 10 p. a49

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › Research › peer-review

Application programming interfaces (API)
Complex networks
Web services
Topology
Engineers

Guest editorial: data-centric Big Services

Sheng, Q. Z., Xu, X., Chang, R. N. & Zhang, L. J., 1 May 2019, In : IEEE Transactions on Services Computing. 12, 3, p. 341-342 2 p., 8733963.

Research output: Contribution to journal › Editorial › Research › peer-review

Guest editors' introduction for special issue on service management for the Internet of Things

Tata, S., Sheng, Q. Z. & Stroulia, E., Mar 2019, In : ACM Transactions on Internet Technology. 19, 1, p. 1-3 3 p., 6.

Research output: Contribution to journal › Editorial › Research › peer-review

iCOP: IoT-enabled policing processes

Schiliro, F., Beheshti, A., Ghodratnama, S., Amouzgar, F., Benatallah, B., Yang, J., Sheng, Q. Z., Casati, F. & Motahari-Nezhad, H. R., 1 Jan 2019, Service-Oriented Computing – ICSOC 2018 Workshops: ADMS, ASOCA, ISYyCC, CloTS, DDBS, and NLS4IoT, Revised Selected Papers. Liu, X., Mrissa, M., Zhang, L., Benslimane, D., Ghose, A., Wang, Z., Bucchiarone, A., Zhang, W., Zou, Y. & Yu, Q. (eds.). Switzerland: Springer-VDI-Verlag GmbH & Co. KG, p. 447-452 6 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11434 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › Research › peer-review

Internet of Things
Data-driven
Law enforcement
Business Process
Industry

Internet of Things meets brain-computer interface: a unified deep learning framework for enabling human-thing cognitive interactivity

Zhang, X., Yao, L., Zhang, S., Kanhere, S., Sheng, M. & Liu, Y., 1 Apr 2019, In : IEEE Internet of Things Journal. 6, 2, p. 2084-2092 9 p., 8506382.

Research output: Contribution to journal › Article › Research › peer-review

Brain computer interface
Brain
Domestic appliances
Reinforcement learning
Robots