Towards Federated Learning with Attention Transfer to Mitigate System and Data Heterogeneity of Clients. - Hongrui Shi; Valentin Radu (EdgeSys@EuroSys, 2021)

Data selection for efficient model update in federated learning. - Hongrui Shi; Valentin Radu (EuroMLSys@EuroSys, 2022)

Closing the Gap between Client and Global Model Performance in Heterogeneous Federated Learning. - Hongrui Shi; Valentin Radu; Po Yang 001 (CoRR, 2022)

Lightweight Workloads in Heterogeneous Federated Learning via Few-shot Learning. - Hongrui Shi; Valentin Radu; Po Yang 001 (DistributedML@CoNEXT, 2023)

Distributed Training for Speech Recognition using Local Knowledge Aggregation and Knowledge Distillation in Heterogeneous Systems. - Hongrui Shi; Valentin Radu; Po Yang 001 (EuroMLSys@EuroSys, 2023)

A Model-Free Controller Based on RBFNN for EGRV System. - Jie Jiang; Ruili Dong; Yonghong Tan 001; Hongrui Shi (RCAR, 2023)

Federated Learning with Workload Reduction through Partial Training of Client Models and Entropy-Based Data Selection. - Hongrui Shi; Valentin Radu; Po Yang 001 (CoRR, 2025)

PestMA: LLM-based Multi-Agent System for Informed Pest Management. - Hongrui Shi; Shunbao Li; Zhipeng Yuan; Po Yang 001 (CoRR, 2025)

Habitat Classification from Ground-Level Imagery Using Deep Neural Networks. - Hongrui Shi; Lisa Norton; Lucy Ridding; Simon Rolph; Tom August; Claire M. Wood; Lan Qie; Petra Bosilj; James M. Brown 001 (CoRR, 2025)