Fed2A: Federated Learning Mechanism in Asynchronous and Adaptive Modes
S Liu, Q Chen, and L You, "Fed2A: Federated Learning Mechanism in Asynchronous and Adaptive Modes", Electronics, 11(9):1393, Apr 2022, doi: 10.3390/electronics11091393.
CV
Employment
- Predoctoral Researcher in KTH Royal Institute of Technology, Sweden, Jul. 2024 - Now
- KTH Profile: Here
Education
- Bachelor’s Degree in Sun Yat-sen University, China, Sep. 2017 - Jun. 2021
- Major: Traffic Engineering, School of Intelligent Systems Engineering
- Minor: Logic, Department of Philosophy
- Thesis Title: Fatigue Driving Detection Algorithm Based on Federated Learning and Multi-source Heterogeneous Data, supervised by Prof. Junbo Wang
- Master’s Degree in Sun Yat-sen University, China, Sep. 2021 - Jun. 2024
- Major: Traffic Information Engineering & Control, School of Intelligent Systems Engineering
- Advisor: Prof. Linlin You
- Thesis Title: Research of Asynchronous Federated Learning Mechanism for Driver Distraction Detection
- Doctoral Degree in KTH Royal Institute of Technology, Sweden, Jul. 2024 - Now
- Major: Information and Communication Technology, Department of Computing and Learning Systems (CLS)
- Supervisor: Prof. Panos Papadimitratos
- KTH Profile: Here
Selected Publications
Adaptation and Learning to Learn (ALL): An Integrated Approach for Small-Sample Parking Occupancy Prediction
H Qu, S Liu, J Li, Y Zhou, and R Liu, "Adaptation and Learning to Learn (ALL): An Integrated Approach for Small-Sample Parking Occupancy Prediction", Mathematics, 10(12):2039, Jun 2022, doi: 10.3390//math10122039.
A Triple-step Asynchronous Federated Learning Mechanism for Client Activation, Interaction Optimization, and Aggregation Enhancement
L. You, S. Liu, Y. Chang and C. Yuen, "A Triple-Step Asynchronous Federated Learning Mechanism for Client Activation, Interaction Optimization, and Aggregation Enhancement," IEEE Internet of Things Journal, vol. 9, no. 23, pp. 24199-24211, Dec 2022, doi: 10.1109/JIOT.2022.3188556.
Federated Architecture for Personal Mobility Service in Autonomous Transportation System
J He, Z Deng, S Liu, L You, M Zhou, M Cai, and S Cheng, "Federated Architecture for Personal Mobility Service in Autonomous Transportation System",COTA International Conference of Transportation Professionals, Jul 2022: 23-33, doi: 10.1061/9780784484265.003.
Improving Parking Occupancy Prediction in Poor Data Conditions Through Customization and Learning to Learn
H Qu, S Liu, Z Guo, L You, and J Li, "Improving Parking Occupancy Prediction in Poor Data Conditions Through Customization and Learning to Learn", International Conference on Knowledge Science, Engineering and Management, 159-172, Jul 2022, doi: 10.1007/978-3-031-10983-6_13.
TWAFR-GRU: An Integrated Model for Real-Time Charging Station Occupancy Prediction
Q Chen, S Liu, H Qu, R Zhu, and L You, "TWAFR-GRU: An Integrated Model for Real-Time Charging Station Occupancy Prediction", IEEE International Conference on Ubiquitous Intelligence and Computing, 1611-1618, Dec 2022, doi: 10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00233.
AFMeta: Asynchronous Federated Meta-learning with Temporally Weighted Aggregation
S Liu, H Qu, Q Chen, W Jian, R Liu, and L You, "AFMeta: Asynchronous Federated Meta-learning with Temporally Weighted Aggregation", IEEE International Conference on Ubiquitous Intelligence and Computing, 641-648, Dec 2022, doi: 10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00100.
ICMFed: An Incremental and Cost-Efficient Mechanism of Federated Meta-Learning for Driver Distraction Detection
Z Guo, L You, S Liu, J He, and B Zuo, "ICMFed: An Incremental and Cost-Efficient Mechanism of Federated Meta-Learning for Driver Distraction Detection", Mathematics, 11(8):1867, Apr 2023, doi: 10.3390/math11081867.
Federated and Asynchronized Learning for Autonomous and Intelligent Things
L You, S Liu, B Zuo, C Yuen, D Niyato, and H Vincent Poor, "Federated and Asynchronized Learning for Autonomous and Intelligent Things", IEEE Network, vol. 38, no. 2, pp. 286-293, Mar 2024, doi: 10.1109/MNET.2023.3321519.
FedRSM: Representational-Similarity-Based Secured Model Uploading for Federated Learning
G Chen, S Liu, X Yang, T Wang, L You, and F Xia, "FedRSM: Representational-Similarity-Based Secured Model Uploading for Federated Learning", IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 189-196, Nov, 2023, doi: 10.1109/TrustCom60117.2023.00046.
FedRC: Representational Consistency Guided Model Uploading Mechanism for Asynchronous Federated Learning
S Liu, L You, and Y Zhou, "FedRC: Representational Consistency Guided Model Uploading Mechanism for Asynchronous Federated Learning", EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 239-256, Jul 2024, doi: 10.1007/978-3-031-63989-0_12.
AiFed: An Adaptive and Integrated Mechanism for Asynchronous Federated Data Mining
L You, S Liu, T Wang, B Zuo, Y Chang, and C Yuen, "AiFed: An Adaptive and Integrated Mechanism for Asynchronous Federated Data Mining", IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 9, pp. 4411-4427, Sep 2024, doi: 10.1109/TKDE.2023.3332770.
AFM3D: An Asynchronous Federated Meta-learning Framework for Driver Distraction Detection
S Liu, L You, R Zhu, B Liu, R Liu, H Yu, and C Yuen, "AFM3D: An Asynchronous Federated Meta-learning Framework for Driver Distraction Detection", IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 8, pp. 9659-9674, Aug 2024, doi: 10.1109/TITS.2024.3357138.
Safeguarding Federated Learning-Based Road Condition Classification
S Liu and Panos Papadimitratos, "Safeguarding Federated Learning-Based Road Condition Classification", IEEE Conference on Communications and Network Security (CNS), pp. 1-9, Sep 2025, doi: 10.1109/CNS66487.2025.11194922.
DEFEND: Poisoned Model Detection and Malicious Client Exclusion Mechanism for Secure Federated Learning-based Road Condition Classification
S Liu and Panos Papadimitratos, "DEFEND: Poisoned Model Detection and Malicious Client Exclusion Mechanism for Secure Federated Learning-based Road Condition Classification", ACM/SIGAPP Symposium on Applied Computing (SAC), pp. 1486–1495, Mar 2026, doi: 10.1145/3748522.3779807.
Awards
- Outstanding Graduate of Sun Yat-sen University, 2024
- National Scholarship for Postgraduates, 2023
- Shenzhen Excellent Academic Paper Award, 2023
- Samsung Scholarship (Only one person is selected in the school), 2022
- Guangdong Guangda Scholarship (Only five persons are selected in the school), 2021
Academic Services
Journals
- Reviewer for IEEE Transactions on Information Forensics and Security (TIFS)
- Reviewer for IEEE Transactions on Dependable and Secure Computing (TDSC)
- Reviewer for IEEE Transactions on Mobile Computing (TMC)
- Reviewer for IEEE Transactions on Industrial Informatics (TII)
- Reviewer for IEEE Transactions on Parallel and Distributed Systems (TPDS)
- Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE)
- Reviewer for IEEE Transactions on Intelligent Transportation Systems (T-ITS)
- Reviewer for Engineering Applications of Artificial Intelligence (EAAI)
- Reviewer for IEEE Network
- Reviewer for IEEE Transactions on Vehicular Technology (TVT)
- Reviewer for ACM Transactions on Internet of Things (TIOT)
- Reviewer for Results in Engineering
- Reviewer for Journal of Big Data
- Reviewer for Cluster Computing
- Reviewer for Pervasive and Mobile Computing
- Reviewer for Applied Network Science
- Reviewer for IEEE Internet of Things Journal (IoTJ)
- Reviewer for The Journal of Supercomputing (TJSC)
- Reviewer for PLOS ONE
- Reviewer for Scientific Reports
- Reviewer for IEEE Access
Conferences
- Artifact Evaluation Committee of Network and Distributed System Security (NDSS) Symposium 2027
- TPC Member of Artificial Intelligence Models and Systems Symposium (AIMS 2025)
- Reviewer for International Conference on Learning Representations (ICLR)
- Reviewer for Annual Conference on Neural Information Processing Systems (NeurIPS)