ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning. - Lukasz Dudziak; Mohamed S. Abdelfattah; Ravichander Vipperla; Stefanos Laskaridis; Nicholas D. Lane (INTERSPEECH, 2019)

EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices. - Mário Almeida; Stefanos Laskaridis; Ilias Leontiadis; Stylianos I. Venieris; Nicholas D. Lane (CoRR, 2019)

HAPI: Hardware-Aware Progressive Inference. - Stefanos Laskaridis; Stylianos I. Venieris; Hyeji Kim; Nicholas D. Lane (ICCAD, 2020)

SPINN: synergistic progressive inference of neural networks over device and cloud. - Stefanos Laskaridis; Stylianos I. Venieris; Mário Almeida; Ilias Leontiadis; Nicholas D. Lane (MobiCom, 2020)

Smart at what cost?: characterising mobile deep neural networks in the wild. - Mário Almeida; Stefanos Laskaridis; Abhinav Mehrotra; Lukasz Dudziak; Ilias Leontiadis; Nicholas D. Lane (Internet Measurement Conference, 2021)

Federated mobile sensing for activity recognition. - Stefanos Laskaridis; Dimitris Spathis; Mário Almeida (MobiCom, 2021)

Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions. - Stefanos Laskaridis; Alexandros Kouris; Nicholas D. Lane (EMDL@MobiSys, 2021)

FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. - Samuel Horváth; Stefanos Laskaridis; Mário Almeida; Ilias Leontiadis; Stylianos I. Venieris; Nicholas D. Lane (NeurIPS, 2021)

It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation. - Ilias Leontiadis; Stefanos Laskaridis; Stylianos I. Venieris; Nicholas D. Lane (HotMobile, 2021)

Multi-Exit Semantic Segmentation Networks. - Alexandros Kouris; Stylianos I. Venieris; Stefanos Laskaridis; Nicholas D. Lane (ECCV (21), 2022)

Adaptable mobile vision systems through multi-exit neural networks. - Alexandros Kouris; Stylianos I. Venieris; Stefanos Laskaridis; Nicholas D. Lane (MobiSys, 2022)

FedorAS: Federated Architecture Search under system heterogeneity. - Lukasz Dudziak; Stefanos Laskaridis; Javier Fernández-Marqués (CoRR, 2022)

Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs. - Alexandros Kouris; Stylianos I. Venieris; Stefanos Laskaridis; Nicholas D. Lane (CoRR, 2022)

Federated Learning for Inference at Anytime and Anywhere. - Zicheng Liu 006; Da Li 001; Javier Fernández-Marqués; Stefanos Laskaridis; Yan Gao 016; Lukasz Dudziak; Stan Z. Li; Shell Xu Hu; Timothy M. Hospedales (CoRR, 2022)

DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device. - Mário Almeida; Stefanos Laskaridis; Stylianos I. Venieris; Ilias Leontiadis; Nicholas D. Lane (ACM Trans. Embed. Comput. Syst., 2022)

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. - Samuel Horváth; Stefanos Laskaridis; Shashank Rajput; Hongyi Wang 001 (ICML, 2024)

Recurrent Early Exits for Federated Learning with Heterogeneous Clients. - Royson Lee; Javier Fernández-Marqués; Shell Xu Hu; Da Li 001; Stefanos Laskaridis; Lukasz Dudziak; Timothy M. Hospedales; Ferenc Huszár; Nicholas Donald Lane (ICML, 2024)

MELTing Point: Mobile Evaluation of Language Transformers. - Stefanos Laskaridis; Kleomenis Katevas; Lorenzo Minto; Hamed Haddadi (MobiCom, 2024)

A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024. - Dimitris Spathis; Aaqib Saeed; Ali Etemad; Sana Tonekaboni; Stefanos Laskaridis; Shohreh Deldari; Chi Ian Tang; Patrick Schwab; Shyam A. Tailor (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)

NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation. - Rob Romijnders; Stefanos Laskaridis; Ali Shahin Shamsabadi; Hamed Haddadi (CoRR, 2025)

LoFT: Low-Rank Adaptation That Behaves Like Full Fine-Tuning. - Nurbek Tastan; Stefanos Laskaridis; Martin Takác 001; Karthik Nandakumar; Samuel Horváth (CoRR, 2025)