Leveraging Target k-Coverage in Wireless Rechargeable Sensor Networks. - Pengzhan Zhou; Cong Wang 006; Yuanyuan Yang 001 (ICDCS, 2017)

Modeling Dishonest Behavior in Mobile Data Gathering Over Leasing Residential Sensor Networks. - Yiming Zeng 001; Pengzhan Zhou; Ji Liu 001; Yuanyuan Yang 001 (GLOBECOM, 2018)

A Stackelberg Game Framework for Mobile Data Gathering in Leasing Residential Sensor Networks. - Yiming Zeng 001; Pengzhan Zhou; Ji Liu 001; Yuanyuan Yang 001 (IWQoS, 2018)

Explore Truthful Incentives for Tasks with Heterogenous Levels of Difficulty in the Sharing Economy. - Pengzhan Zhou; Xin Wei; Cong Wang 006; Yuanyuan Yang 001 (IJCAI, 2019)

Self-sustainable Sensor Networks with Multi-source Energy Harvesting and Wireless Charging. - Pengzhan Zhou; Cong Wang 006; Yuanyuan Yang 001 (INFOCOM, 2019)

Static and Mobile Target kk-Coverage in Wireless Rechargeable Sensor Networks. - Pengzhan Zhou; Cong Wang 006; Yuanyuan Yang 001 (IEEE Trans. Mob. Comput., 2019)

E-Sharing: Data-driven Online Optimization of Parking Location Placement for Dockless Electric Bike Sharing. - Pengzhan Zhou; Cong Wang 006; Yuanyuan Yang 001; Xin Wei (ICDCS, 2020)

Design and Optimization of Electric Autonomous Vehicles with Renewable Energy Source for Smart Cities. - Pengzhan Zhou; Cong Wang 006; Yuanyuan Yang 001 (INFOCOM, 2020)

Optimize Scheduling of Federated Learning on Battery-powered Mobile Devices. - Cong Wang 006; Xin Wei; Pengzhan Zhou (IPDPS, 2020)

Design of Self-sustainable Wireless Sensor Networks with Energy Harvesting and Wireless Charging. - Pengzhan Zhou; Cong Wang 006; Yuanyuan Yang 001 (ACM Trans. Sens. Networks, 2021)

Towards Efficient Scheduling of Federated Mobile Devices Under Computational and Statistical Heterogeneity. - Cong Wang 006; Yuanyuan Yang 001; Pengzhan Zhou (IEEE Trans. Parallel Distributed Syst., 2021)

k-Level Truthful Incentivizing Mechanism and Generalized k-MAB Problem. - Pengzhan Zhou; Xin Wei; Cong Wang 006; Yuanyuan Yang 001 (IEEE Trans. Computers, 2022)

Adaptive Federated Deep Reinforcement Learning for Proactive Content Caching in Edge Computing. - Dewen Qiao; Songtao Guo; Defang Liu; Saiqin Long; Pengzhan Zhou; Zhetao Li (IEEE Trans. Parallel Distributed Syst., 2022)

iCOS: A Deep Reinforcement Learning Scheme for Wireless-Charged MEC Networks. - Changwei Wan; Songtao Guo; Jing He 011; Guiyan Liu; Pengzhan Zhou (IEEE Trans. Veh. Technol., 2022)

Design and Optimization of Solar-Powered Shared Electric Autonomous Vehicle System for Smart Cities. - Pengzhan Zhou; Cong Wang 006; Yuanyuan Yang 001 (IEEE Trans. Mob. Comput., 2023)

Economical Behavior Modeling and Analyses for Data Collection in Edge Internet of Things Networks. - Yiming Zeng 001; Pengzhan Zhou; Cong Wang 006; Ji Liu 001; Yuanyuan Yang 001 (ACM Trans. Sens. Networks, 2023)

Deep Reinforcement Learning Empowers Wireless Powered Mobile Edge Computing: Towards Energy-Aware Online Offloading. - Xianlong Jiao; Yating Wang; Songtao Guo; Hong Zhang; Haipeng Dai 001; Mingyan Li; Pengzhan Zhou (IEEE Trans. Commun., 2023)

FedGDC-P: Communication-efficient Personalized Graph Federated Learning Based On Dataset Condensation. - Jiaming Zhang; Songtao Guo; Pengzhan Zhou (CSCWD, 2024)

HfedPES: Hierarchical Personalized Federated Learning with Edge Selection. - Kunhong He; Pengzhan Zhou; Yijun Zhai; Yuepeng He; Lin Tan 011; Dewen Qiao; Songtao Guo (MSN, 2024)

FedRAV: Hierarchically Federated Region-Learning for Traffic Object Classification of Autonomous Vehicles. - Yijun Zhai; Pengzhan Zhou; Yuepeng He; Fang Qu; Zhida Qin; Xianlong Jiao; Guiyan Liu; Songtao Guo (MSN, 2024)

FedAH: Aggregated Head for Personalized Federated Learning. - Pengzhan Zhou; Yuepeng He; Yijun Zhai; Kaixin Gao; Chao Chen; Zhida Qin; Chong Zhang; Songtao Guo (CoRR, 2024)

FedPAW: Federated Learning With Personalized Aggregation Weights for Urban Vehicle Speed Prediction. - Yuepeng He; Pengzhan Zhou; Yijun Zhai; Fang Qu; Zhida Qin; Mingyan Li; Songtao Guo (IEEE Trans. Cloud Comput., 2024)

Towards Relevance and Diversity in Crowdsourcing Worker Recruitment With Insufficient Information. - Zhida Qin; Siyun Yang; Yuchen Huang; Haoyan Fu; Pengzhan Zhou; Gangyi Ding (IEEE Trans. Netw. Sci. Eng., 2024)

HAT: Task Offloading and Resource Allocation in RIS-Assisted Collaborative Edge Computing. - Lin Tan 011; Songtao Guo; Pengzhan Zhou; Zhufang Kuang; Xianlong Jiao (IEEE Trans. Netw. Sci. Eng., 2024)

Parameters optimization and precision enhancement of Takagi-Sugeno fuzzy neural network. - Dewen Qiao; Pengzhan Zhou; Mingyan Li; Songtao Guo (Soft Comput., 2024)

Multi-UAV-Enabled Collaborative Edge Computing: Deployment, Offloading and Resource Optimization. - Lin Tan 011; Songtao Guo; Pengzhan Zhou; Zhufang Kuang; Saiqin Long; Zhetao Li (IEEE Trans. Intell. Transp. Syst., 2024)

PreM-FedIoV: A Novel Federated Reinforcement Learning Framework for Predictive Maintenance in IoV. - Lu Yang 012; Songtao Guo; Chen-Khong Tham; Mingyan Li; Guiyan Liu; Pengzhan Zhou (IEEE Trans. Mob. Comput., 2024)

Dual-GT: Dual-scale Spatial Dependency for Grid-based Traffic Flow Prediction. - Xufeng Liang; Zhida Qin; Pengzhan Zhou; Shuang Li 008; Tianyu Huang (INFOCOM, 2025)

Large Language Models Enhanced Hyperbolic Space Recommender Systems. - Wentao Cheng; Zhida Qin; Zexue Wu; Pengzhan Zhou; Tianyu Huang (SIGIR, 2025)

FedSPA: Heterogenous Federated Learning with Similarity-Based Prototype Aggregation. - Chen Yang; Songtao Guo; Pengzhan Zhou (WASA (1), 2025)

ASMAFL: Adaptive Staleness-Aware Momentum Asynchronous Federated Learning in Edge Computing. - Dewen Qiao; Songtao Guo; Jun Zhao 007; Junqing Le; Pengzhan Zhou; Mingyan Li; Xuetao Chen (IEEE Trans. Mob. Comput., 2025)

EMAFL: Evolutionary Momentum Auxiliary Adaptive Accelerating Federated Learning. - Dewen Qiao; Songtao Guo; Xuetao Chen; Pengzhan Zhou; Di Zhang 011; Yu Zhang (IEEE Internet Things J., 2025)

AMFL: Resource-Efficient Adaptive Metaverse-Based Federated Learning for the Human-Centric Augmented Reality Applications. - Dewen Qiao; Liangxin Qian; Songtao Guo; Jun Zhao 007; Pengzhan Zhou (IEEE Trans. Neural Networks Learn. Syst., 2025)

FedSODA: Federated Fine-tuning of LLMs via Similarity Group Pruning and Orchestrated Distillation Alignment. - Manning Zhu; Songtao Guo; Pengzhan Zhou; Yansong Ning; Chang Han; Dewen Qiao (CoRR, 2025)