Overview
Shuang is a Postdoctoral Research Associate in the Faculty of Environment, Science and Economy. Her research interests cover federated learning, distributed machine learning, privacy-preserving data mining, real-time smart meter big data clustering and forecasting. Shuang completed her PhD at the Department of Mathematical Sciences of University of Essex where she developed real-time federated/distributed privacy-preserving machine learning frameworks for smart meter big data. She achieved her Master Degree in advanced computer science (Artificial Intelligence) at the Department of Computer Science of University of Manchester. In addition she worked as an research assistant at the University of Essex with several orgnisations including the Institute of Social and Economic Research and Essex Partnership University NHS Foundation Trust and Essex County Council.Publications
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| 2024 | 2023 | 2022 | 2021 | 2020 |
2024
- Dai S, Meng F, Wang Q, Chen X. (2024) DP
2023
- Chen H, Dai S, Meng F. (2023) Smart Building Thermal Management: A Data-Driven Approach Based on Dynamic and Consensus Clustering, Sustainability, volume 15, no. 21, pages 15489-15489, DOI:10.3390/su152115489. [PDF]
- Dai S, Meng F, Wang Q, Chen X. (2023) FederatedNILM: A Distributed and Privacy-Preserving Framework for Non-Intrusive Load Monitoring Based on Federated Deep Learning, 2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast Convention And Exhibition Centre Queensland, Australia, 18th Jun - 23rd Jul 2023.
2022
- Dai S, Meng F. (2022) Addressing modern and practical challenges in machine learning: a survey of online federated and transfer learning, Applied Intelligence, volume 53, no. 9, pages 11045-11072, DOI:10.1007/s10489-022-04065-3. [PDF]
- Dai S, Meng F, Wang Q, Chen X. (2022) DP$^2$-NILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring. [PDF]
2021
- Dai S, Wang Q, Meng F. (2021) A telehealth framework for dementia care: an ADLs patterns recognition model for patients based on NILM, 2021 International Joint Conference on Neural Networks (IJCNN), 18th - 22nd Jul 2021, 2021 International Joint Conference on Neural Networks (IJCNN), DOI:10.1109/ijcnn52387.2021.9534058. [PDF]
- Dai S, Meng F, Dai H, Wang Q, Chen X. (2021) Electrical peak demand forecasting- A review. [PDF]
2020
- Dai S, Meng F. (2020) Energy Forecasting with Building Characteristics Analysis, 2020 International Joint Conference on Neural Networks (IJCNN), 19th - 24th Jul 2020, 2020 International Joint Conference on Neural Networks (IJCNN), DOI:10.1109/ijcnn48605.2020.9207402. [PDF]
