104 citations · 190 across the 10 of their papers we have counts for
17 papers
Towards a Roadmap on Software Engineering for Responsible AI
Qinghua Lu, Liming Zhu, Xiwei Xu +2
Although AI is transforming the world, there are serious concerns about its ability to behave and make decisions responsibly. Many ethical regulations, principles, and frameworks f…
Blockchain-based Trustworthy Federated Learning Architecture
Sin Kit Lo, Yue Liu, Qinghua Lu +4
Federated learning is an emerging privacy-preserving AI technique where clients (i.e., organisations or devices) train models locally and formulate a global model based on the loca…
FLRA: A Reference Architecture for Federated Learning Systems
Sin Kit Lo, Qinghua Lu, Hye-Young Paik +1
Federated learning is an emerging machine learning paradigm that enables multiple devices to train models locally and formulate a global model, without sharing the clients' local d…
AI and Ethics -- Operationalising Responsible AI
Liming Zhu, Xiwei Xu, Qinghua Lu +2
In the last few years, AI continues demonstrating its positive impact on society while sometimes with ethically questionable consequences. Building and maintaining public trust in…
A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things
Jiehan Zhou, Shouhua Zhang, Qinghua Lu +7
Federated learning (FL) brings collaborative intelligence into industries without centralized training data to accelerate the process of Industry 4.0 on the edge computing level. F…
Patterns for Blockchain-Based Payment Applications
Qinghua Lu, Xiwei Xu, H. M. N. Dilum Bandara +2
As the killer application of blockchain technology, blockchain-based payments have attracted extensive attention ranging from hobbyists to corporates to regulatory bodies. Blockcha…