BeFAQT - Team
🎉 BeFAQT team won the NSW iAwards 2020! 🎉

Project Team
The BeFAQT team comprises researchers, developers, PhD students, and managers from UTS and Sydney Fish Market.

Prof. Ren Ping Liu
Project Leader

Dr. Xu Wang
Blockchain Stream Lead

Prof. Jian Zhang
E-eye Stream Lead

A/Prof. Steven Su
E-nose Stream Lead

Dr. Ying He
IoT Stream Lead

A./Prof. Qiang Wu
Advisor

Prof. Eryk Dutkiewicz
Advisor

Peter Loneragan
Project Manager

Saber Yu
Blockchain Developer

Dr. Zongjian Zhang
E-eye Developer

Wentian Zhang
IoT Developer

Taoping Liu
e-nose Developer
Sydney Fish Market
Erik Poole and Nick Paton from the Sydney Fish Market.
List of Publications
- Xu Wang, Guangsheng Yu, Ren Ping Liu, Jian Zhang, Qiang Wu, Steven W. Su, etc, Blockchain-Enabled Fish Provenance and Quality Tracking System, IEEE Internet of Things Journal, June 2022
- Guangsheng Yu, Xuan Zha, Xu Wang, Wei Ni, Kan Yu, J. Andrew Zhang, Ren Ping Liu, A Unified Analytical model for proof-of-X schemes, Computers & Security,2020
- Guangsheng Yu, Xuan Zha, Xu Wang, Wei Ni, Kan Yu, Ping Yu, J. Andrew, Ren Ping Liu, Y. Jay Guo, Enabling Attribute Revocation for Fine-Grained Access Control in Blockchain-IoT Systems, IEEE Transactions on Engineering Management, Feb. 2020.
- Guangsheng Yu, Xu Wang, Kan Yu, Wei Ni, J. Andrew Zhang, Ren Ping Liu, Survey: Sharding in Blockchains, IEEE Access, 2020
- Xu Wang, Ping Yu, Guangsheng Yu, Xuan Zha, Wei Ni, Ren Ping Liu, Y. Jay Guo, A High-Performance Hybrid Blockchain System for Traceable IoT Applications, International Conference on Network and System Security, December 2019.
- Wentian Zhang et al. A novel data pre-processing method for odour detection and identification system. Sensors and Actuators A: Physical, 287:113–120, 2019.
- Taoping Liu et al. A novel multi-odour identification by electronic nose using non-parametric modelling-based feature extraction and time-series classification. Sensors and Actuators B: Chemical, 2019.
- Huaxi Huang et al. Compare More Nuanced: Pairwise Alignment Bilinear Network for Few-Shot Fine-Grained Learning, IEEE International Conference on Multimedia and Expo, ICME 2019, pp.91-96.
Contact Us
If you have any questions or would like to get in touch with the BeFAQT team, please email us at renping.liu@uts.edu.au