Transport protocols behaviour study in evolving mobile networks. - Rui Li 052; Mehrdad Shariat; Maziar M. Nekovee (ISWCS, 2016)

WiHaul: max-min fair wireless backhauling over multi-hop millimetre-wave links. - Rui Li 052; Paul Patras (HotWireless@MobiCom, 2016)

Learning from experience: Efficient decentralized scheduling for 60GHz mesh networks. - Gek Hong Sim; Rui Li 052; Cristina Cano; David Malone; Paul Patras; Joerg Widmer (WoWMoM, 2016)

Max-Min Fair Millimetre-Wave Backhauling. - Rui Li 052; Paul Patras (CoRR, 2017)

Delmu: A Deep Learning Approach to Maximising the Utility of Virtualised Millimetre-Wave Backhauls. - Rui Li 052; Chaoyun Zhang; Pan Cao; Paul Patras; John S. Thompson (MLN, 2018)

Learning Driven Mobility Control of Airborne Base Stations in Emergency Networks. - Rui Li 052; Chaoyun Zhang; Paul Patras; Razvan Stanica; Fabrice Valois (SIGMETRICS Perform. Evaluation Rev., 2018)

Learning to Listen... On-Device: Present and future perspectives of on-device ASR. - Ravichander Vipperla; Samin Ishtiaq; Rui Li 052; Sourav Bhattacharya; Ilias Leontiadis; Nicholas D. Lane (GetMobile Mob. Comput. Commun., 2019)

Resource management in future mobile networks: from millimetre-wave backhauls to airborne access networks. - Rui Li 052 (2019)

Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets With Multi-Stream Inputs. - Chaoyun Zhang; Rui Li 052; Woojin Kim; Daesub Yoon; Paul Patras (IEEE Access, 2020)

Max-Min Fair Resource Allocation in Millimetre-Wave Backhauls. - Rui Li 052; Paul Patras (IEEE Trans. Mob. Comput., 2020)

A Channel Coding Benchmark for Meta-Learning. - Rui Li 052; Ondrej Bohdal; Rajesh K. Mishra; Hyeji Kim; Da Li 001; Nicholas D. Lane; Timothy M. Hospedales (NeurIPS Datasets and Benchmarks, 2021)

Inferring Facing Direction from Voice Signals. - Yu-Lin Wei; Rui Li 052; Abhinav Mehrotra; Romit Roy Choudhury; Nicholas D. Lane (CoRR, 2021)

TransMUSE: Transferable Traffic Prediction in MUlti-Service EdgeNetworks. - Luyang Xu; Haoyu Liu; Junping Song; Rui Li 052; Yahui Hu; Xu Zhou; Paul Patras (CoRR, 2022)

TinyTrain: Deep Neural Network Training at the Extreme Edge. - Young D. Kwon; Rui Li 052; Stylianos I. Venieris; Jagmohan Chauhan; Nicholas D. Lane; Cecilia Mascolo (CoRR, 2023)

TransMUSE: Transferable Traffic Prediction in MUlti-Service Edge Networks. - Luyang Xu; Haoyu Liu; Junping Song; Rui Li 052; Yahui Hu; Xu Zhou; Paul Patras (Comput. Networks, 2023)

TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge. - Young D. Kwon; Rui Li 052; Stylianos I. Venieris; Jagmohan Chauhan; Nicholas Donald Lane; Cecilia Mascolo (ICML, 2024)

Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. - Royson Lee; Rui Li 052; Stylianos I. Venieris; Timothy M. Hospedales; Ferenc Huszár; Nicholas D. Lane (WACV, 2024)

Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference. - Hao Mark Chen; Wayne Luk; Ka Fai Cedric Yiu; Rui Li 052; Konstantin Mishchenko; Stylianos I. Venieris; Hongxiang Fan (CoRR, 2024)

The Future of Consumer Edge-AI Computing. - Stefanos Laskaridis; Stylianos I. Venieris; Alexandros Kouris; Rui Li 052; Nicholas D. Lane (IEEE Pervasive Comput., 2024)

FedP2EFT: Federated Learning to Personalize Parameter Efficient Fine-Tuning for Multilingual LLMs. - Royson Lee; Minyoung Kim 001; Fady Rezk; Rui Li 052; Stylianos I. Venieris; Timothy M. Hospedales (CoRR, 2025)

HierarchicalPrune: Position-Aware Compression for Large-Scale Diffusion Models. - Young D. Kwon; Rui Li 052; Sijia Li; Da Li 001; Sourav Bhattacharya; Stylianos I. Venieris (CoRR, 2025)