Dr. Cong Zhao has joint the AESE group at Imperial College London as a research associate in Jan 2018. He received his PhD in computer science and technology from Xi’an Jiaotong University (XJTU) in 2017. Affiliated to the joint program of Data-Centric Engineering (The Alan Turing Institute with the Lloyd’s Register Foundation), he is concentrating on Data-Driven solutions based on Edge Intelligence to accurate, adaptive and sustainable operations in emerging IoT applications in fields like smart manufacturing, smart city, and precision farming. His research interests include meta learning, federated learning, edge intelligence, and computing economics.
- C. Zhao, S. Yang, J. McCann, On the Data Quality in Privacy-Preserving Mobile Crowdsensing Systems with Untruthful Reporting, IEEE Transactions on Mobile Computing, accepted, 2019.
- C. Zhao, S. Yang, P. Yan, et. al., Data Quality Guarantee for Credible Caching Device Selection in Mobile Crowdsensing Systems, IEEE Wireless Communications, 25(3): 58-64, 2018.
- C. Zhao, S. Yang, X. Yang, et. al., Rapid, User-transparent, and Trustworthy Device Pairing for D2D-enabled Mobile Crowdsourcing, IEEE Transactions on Mobile Computing, 16(7): 2008-2022, 2017.
- C. Zhao, X. Yang, W. Yu, et. al., Cheating-Resilient Incentive Scheme for Mobile Crowdsensing Systems, in Proc. of IEEE CCNC, 2017, pp. 377-382.
- X. Yang, C. Zhao, W. Yu, et. al., A User Incentive-based Scheme Against Dishonest Reporting in Privacy-Preserving Mobile Crowdsensing Systems, in Proc. of WASA (Best Paper Award), 2017, pp. 755-767.
- C. Zhao, F. Shi, R. Huang, et. al., Trustworthy Device Pairing for Opportunistic Device-to-Device Communications in Mobile Crowdsourcing Systems, in Proc. of ACM S3, 2015, pp. 4-6.
- X. Yang, C. Zhao, S. Yang, et. al., A Systematic Key Management Mechanism for Practical Body Sensor Networks, in Proc. of IEEE ICC, 2015, pp.7310-7315.