An Empirical Study of Textual and Graphical Travel Itinerary Visualization using Mobile Phones. - Masood Masoodian; Nicholas D. Lane (AUIC, 2003)

Virtual sensing range. - Emiliano Miluzzo; Nicholas D. Lane; Andrew T. Campbell (SenSys, 2006)

People-centric urban sensing. - Andrew T. Campbell; Shane B. Eisenman; Nicholas D. Lane; Emiliano Miluzzo; Ronald A. Peterson (WICON, 2006)

Ambient beacon localization: using sensed characteristics of the physical world to localize mobile sensors. - Nicholas D. Lane; Hong Lu 006; Andrew T. Campbell (EmNets, 2007)

CenceMe - Injecting Sensing Presence into Social Networking Applications. - Emiliano Miluzzo; Nicholas D. Lane; Shane B. Eisenman; Andrew T. Campbell (EuroSSC, 2007)

Techniques for Improving Opportunistic Sensor Networking Performance. - Shane B. Eisenman; Nicholas D. Lane; Andrew T. Campbell (DCOSS, 2008)

CaliBree: A Self-calibration System for Mobile Sensor Networks. - Emiliano Miluzzo; Nicholas D. Lane; Andrew T. Campbell; Reza Olfati-Saber (DCOSS, 2008)

Cooperative Techniques Supporting Sensor-Based People-Centric Inferencing. - Nicholas D. Lane; Hong Lu 006; Shane B. Eisenman; Andrew T. Campbell (Pervasive, 2008)

Transforming the social networking experience with sensing presence from mobile phones. - Andrew T. Campbell; Shane B. Eisenman; Kristóf Fodor; Nicholas D. Lane; Hong Lu 006; Emiliano Miluzzo; Mirco Musolesi; Ronald A. Peterson; Xiao Zheng (SenSys, 2008)

Sensing meets mobile social networks: the design, implementation and evaluation of the cenceme application. - Emiliano Miluzzo; Nicholas D. Lane; Kristóf Fodor; Ronald A. Peterson; Hong Lu 006; Mirco Musolesi; Shane B. Eisenman; Xiao Zheng; Andrew T. Campbell (SenSys, 2008)

Integrating sensor presence into virtual worlds using mobile phones. - Mirco Musolesi; Emiliano Miluzzo; Nicholas D. Lane; Shane B. Eisenman; Tanzeem Choudhury; Andrew T. Campbell (SenSys, 2008)

Urban sensing systems: opportunistic or participatory? - Nicholas D. Lane; Shane B. Eisenman; Mirco Musolesi; Emiliano Miluzzo; Andrew T. Campbell (HotMobile, 2008)

The Rise of People-Centric Sensing. - Andrew T. Campbell; Shane B. Eisenman; Nicholas D. Lane; Emiliano Miluzzo; Ronald A. Peterson; Hong Lu 006; Xiao Zheng; Mirco Musolesi; Kristóf Fodor; Gahng-Seop Ahn (IEEE Internet Comput., 2008)

SoundSense: scalable sound sensing for people-centric applications on mobile phones. - Hong Lu 006; Wei Pan; Nicholas D. Lane; Tanzeem Choudhury; Andrew T. Campbell (MobiSys, 2009)

BikeNet: A mobile sensing system for cyclist experience mapping. - Shane B. Eisenman; Emiliano Miluzzo; Nicholas D. Lane; Ronald A. Peterson; Gahng-Seop Ahn; Andrew T. Campbell (ACM Trans. Sens. Networks, 2009)

Community-Guided Learning: Exploiting Mobile Sensor Users to Model Human Behavior. - Daniel Peebles; Hong Lu 006; Nicholas D. Lane; Tanzeem Choudhury; Andrew T. Campbell (AAAI, 2010)

Hapori: context-based local search for mobile phones using community behavioral modeling and similarity. - Nicholas D. Lane; Dimitrios Lymberopoulos; Feng Zhao 001; Andrew T. Campbell (UbiComp, 2010)

The Jigsaw continuous sensing engine for mobile phone applications. - Hong Lu 006; Jun Yang; Zhigang Liu 010; Nicholas D. Lane; Tanzeem Choudhury; Andrew T. Campbell (SenSys, 2010)

A survey of mobile phone sensing. - Nicholas D. Lane; Emiliano Miluzzo; Hong Lu 006; Daniel Peebles; Tanzeem Choudhury; Andrew T. Campbell (IEEE Commun. Mag., 2010)

Bubble-sensing: Binding sensing tasks to the physical world. - Hong Lu 006; Nicholas D. Lane; Shane B. Eisenman; Andrew T. Campbell (Pervasive Mob. Comput., 2010)

Mobile sensing: challenges, opportunities and future directions. - Nicholas D. Lane; Tanzeem Choudhury; Feng Zhao 001 (UbiComp, 2011)

Enabling large-scale human activity inference on smartphones using community similarity networks (csn). - Nicholas D. Lane; Ye Xu; Hong Lu 006; Shaohan Hu; Tanzeem Choudhury; Andrew T. Campbell; Feng Zhao 001 (UbiComp, 2011)

Balancing energy, latency and accuracy for mobile sensor data classification. - David Chu; Nicholas D. Lane; Ted Tsung-Te Lai; Cong Pang; Xiangying Meng; Qing Guo; Fan Li 007; Feng Zhao 001 (SenSys, 2011)

Exploiting Social Networks for Large-Scale Human Behavior Modeling. - Nicholas D. Lane; Ye Xu; Hong Lu 006; Andrew T. Campbell; Tanzeem Choudhury; Shane B. Eisenman (IEEE Pervasive Comput., 2011)

Towards Population Scale Activity Recognition: A Framework for Handling Data Diversity. - Saeed Abdullah; Nicholas D. Lane; Tanzeem Choudhury (AAAI, 2012)

Automatically characterizing places with opportunistic crowdsensing using smartphones. - Yohan Chon; Nicholas D. Lane; Fan Li 007; Hojung Cha; Feng Zhao 001 (UbiComp, 2012)

CarSafe demo: supporting driver safety using dual-cameras on smartphones. - Chuang-Wen You; Martha Montes-de-Oca; Thomas J. Bao; Nicholas D. Lane; Hong Lu 006; Giuseppe Cardone; Lorenzo Torresani; Andrew T. Campbell (UbiComp, 2012)

CarSafe: a driver safety app that detects dangerous driving behavior using dual-cameras on smartphones. - Chuang-Wen You; Martha Montes-de-Oca; Thomas J. Bao; Nicholas D. Lane; Hong Lu 006; Giuseppe Cardone; Lorenzo Torresani; Andrew T. Campbell (UbiComp, 2012)

Visage: A Face Interpretation Engine for Smartphone Applications. - Xiaochao Yang; Chuang-Wen You; Hong Lu 006; Mu Lin; Nicholas D. Lane; Andrew T. Campbell (MobiCASE, 2012)

BeWell+: multi-dimensional wellbeing monitoring with community-guided user feedback and energy optimization. - Mu Lin; Nicholas D. Lane; Mashfiqui Mohammod; Xiaochao Yang; Hong Lu 006; Giuseppe Cardone; Shahid Ali; Afsaneh Doryab; Ethan Berke; Andrew T. Campbell; Tanzeem Choudhury (Wireless Health, 2012)

Community-Aware Smartphone Sensing Systems. - Nicholas D. Lane (IEEE Internet Comput., 2012)

Understanding the coverage and scalability of place-centric crowdsensing. - Yohan Chon; Nicholas D. Lane; Yunjong Kim; Feng Zhao 001; Hojung Cha (UbiComp, 2013)

2nd ACM international workshop on mobile systems for computational social science. - Nicholas D. Lane; Mirco Musolesi (UbiComp (Adjunct Publication), 2013)

Preference, context and communities: a multi-faceted approach to predicting smartphone app usage patterns. - Ye Xu; Mu Lin; Hong Lu 006; Giuseppe Cardone; Nicholas D. Lane; Zhenyu Chen 003; Andrew T. Campbell; Tanzeem Choudhury (ISWC, 2013)

MoodScope: building a mood sensor from smartphone usage patterns. - Robert LiKamWa; Yunxin Liu 001; Nicholas D. Lane; Lin Zhong 001 (MobiSys, 2013)

CarSafe app: alerting drowsy and distracted drivers using dual cameras on smartphones. - Chuang-Wen You; Nicholas D. Lane; Fanglin Chen; Rui Wang 016; Zhenyu Chen 003; Thomas J. Bao; Martha Montes-de-Oca; Yuting Cheng 001; Mu Lin; Lorenzo Torresani; Andrew T. Campbell (MobiSys, 2013)

Unobtrusive sleep monitoring using smartphones. - Zhenyu Chen 003; Mu Lin; Fanglin Chen; Nicholas D. Lane; Giuseppe Cardone; Rui Wang 016; Tianxing Li 001; Yiqiang Chen 001; Tanzeem Choudhury; Andrew T. Campbell (PervasiveHealth, 2013)

Piggyback CrowdSensing (PCS): energy efficient crowdsourcing of mobile sensor data by exploiting smartphone app opportunities. - Nicholas D. Lane; Yohan Chon; Lin Zhou; Yongzhe Zhang; Fan Li 007; Dongwon Kim; Guanzhong Ding; Feng Zhao 001; Hojung Cha (SenSys, 2013)

ContextSense: unobtrusive discovery of incremental social context using dynamic bluetooth data. - Zhenyu Chen 003; Yiqiang Chen 001; Lisha Hu; Shuangquan Wang; Xinlong Jiang; Xiaojuan Ma; Nicholas D. Lane; Andrew T. Campbell (UbiComp Adjunct, 2014)

Connecting personal-scale sensing and networked community behavior to infer human activities. - Nicholas D. Lane; Li Pengyu; Lin Zhou; Feng Zhao 001 (UbiComp, 2014)

Caiipa: automated large-scale mobile app testing through contextual fuzzing. - Chieh-Jan Mike Liang; Nicholas D. Lane; Niels Brouwers; Li Zhang; Börje F. Karlsson; Hao Liu 006; Yan Liu; Jun Tang; Xiang Shan; Ranveer Chandra; Feng Zhao 001 (MobiCom, 2014)

DSP.Ear: leveraging co-processor support for continuous audio sensing on smartphones. - Petko Georgiev; Nicholas D. Lane; Kiran K. Rachuri; Cecilia Mascolo (SenSys, 2014)

BeWell: Sensing Sleep, Physical Activities and Social Interactions to Promote Wellbeing. - Nicholas D. Lane; Mu Lin; Mashfiqui Mohammod; Xiaochao Yang; Hong Lu 006; Giuseppe Cardone; Shahid Ali; Afsaneh Doryab; Ethan Berke; Andrew T. Campbell; Tanzeem Choudhury (Mob. Networks Appl., 2014)

Community Similarity Networks. - Nicholas D. Lane; Ye Xu; Hong Lu 006; Shaohan Hu; Tanzeem Choudhury; Andrew T. Campbell; Feng Zhao 001 (Pers. Ubiquitous Comput., 2014)

Prime: a framework for co-located multi-device apps. - David Chu; Zengbin Zhang; Alec Wolman; Nicholas D. Lane (UbiComp, 2015)

DeepEar: robust smartphone audio sensing in unconstrained acoustic environments using deep learning. - Nicholas D. Lane; Petko Georgiev; Lorena Qendro (UbiComp, 2015)

More with less: lowering user burden in mobile crowdsourcing through compressive sensing. - Liwen Xu; Xiaohong Hao; Nicholas D. Lane; Xin Liu 002; Thomas Moscibroda (UbiComp, 2015)

Unobtrusive Sensing Incremental Social Contexts Using Fuzzy Class Incremental Learning. - Zhenyu Chen 003; Yiqiang Chen 001; Xingyu Gao 001; Shuangquan Wang; Lisha Hu; Chenggang Clarence Yan; Nicholas D. Lane; Chunyan Miao (ICDM, 2015)

SIFT: building an internet of safe things. - Chieh-Jan Mike Liang; Börje F. Karlsson; Nicholas D. Lane; Feng Zhao 001; Junbei Zhang; Zheyi Pan; Zhao Li; Yong Yu 001 (IPSN, 2015)

Cost-aware compressive sensing for networked sensing systems. - Liwen Xu; Xiaohong Hao; Nicholas D. Lane; Xin Liu 002; Thomas Moscibroda (IPSN, 2015)

ZOE: A Cloud-less Dialog-enabled Continuous Sensing Wearable Exploiting Heterogeneous Computation. - Nicholas D. Lane; Petko Georgiev; Cecilia Mascolo; Ying Gao (MobiSys, 2015)

An Early Resource Characterization of Deep Learning on Wearables, Smartphones and Internet-of-Things Devices. - Nicholas D. Lane; Sourav Bhattacharya; Petko Georgiev; Claudio Forlivesi; Fahim Kawsar (IoT-App@SenSys, 2015)

Can Deep Learning Revolutionize Mobile Sensing? - Nicholas D. Lane; Petko Georgiev (HotMobile, 2015)

How to the Smash Next Billion Mobile App Bugs? - Ranveer Chandra; Börje F. Karlsson; Nicholas D. Lane; Chieh-Jan Mike Liang; Suman Nath; Jitu Padhye; Lenin Ravindranath; Feng Zhao 001 (GetMobile Mob. Comput. Commun., 2015)

Engagement-aware computing: modelling user engagement from mobile contexts. - Akhil Mathur; Nicholas D. Lane; Fahim Kawsar (UbiComp, 2016)

Towards multimodal deep learning for activity recognition on mobile devices. - Valentin Radu; Nicholas D. Lane; Sourav Bhattacharya; Cecilia Mascolo; Mahesh K. Marina; Fahim Kawsar (UbiComp Adjunct, 2016)

ppNav: Peer-to-Peer Indoor Navigation for Smartphones. - Zuwei Yin; Chenshu Wu; Zheng Yang 002; Nicholas D. Lane; Yunhao Liu 001 (ICPADS, 2016)

HeadScan: A Wearable System for Radio-Based Sensing of Head and Mouth-Related Activities. - Biyi Fang; Nicholas D. Lane; Mi Zhang 002; Fahim Kawsar (IPSN, 2016)

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices. - Nicholas D. Lane; Sourav Bhattacharya; Petko Georgiev; Claudio Forlivesi; Lei Jiao 002; Lorena Qendro; Fahim Kawsar (IPSN, 2016)

Demonstration Abstract: Accelerating Embedded Deep Learning Using DeepX. - Nicholas D. Lane; Sourav Bhattacharya; Petko Georgiev; Claudio Forlivesi; Fahim Kawsar (IPSN, 2016)

DXTK: Enabling Resource-efficient Deep Learning on Mobile and Embedded Devices with the DeepX Toolkit. - Nicholas D. Lane; Sourav Bhattacharya; Akhil Mathur; Claudio Forlivesi; Fahim Kawsar (MobiCASE, 2016)

LEO: scheduling sensor inference algorithms across heterogeneous mobile processors and network resources. - Petko Georgiev; Nicholas D. Lane; Kiran K. Rachuri; Cecilia Mascolo (MobiCom, 2016)

BodyScan: Enabling Radio-based Sensing on Wearable Devices for Contactless Activity and Vital Sign Monitoring. - Biyi Fang; Nicholas D. Lane; Mi Zhang 002; Aidan Boran; Fahim Kawsar (MobiSys, 2016)

Poster: Towards Radio-based Sensing on Wearables. - Biyi Fang; Nicholas D. Lane; Mi Zhang 002; Aidan Boran; Fahim Kawsar (MobiSys (Companion Volume), 2016)

Demo: Accelerated Deep Learning Inference for Embedded and Wearable Devices using DeepX. - Nicholas D. Lane; Sourav Bhattacharya; Petko Georgiev; Claudio Forlivesi; Fahim Kawsar (MobiSys (Companion Volume), 2016)

From smart to deep: Robust activity recognition on smartwatches using deep learning. - Sourav Bhattacharya; Nicholas D. Lane (PerCom Workshops, 2016)

Sparsification and Separation of Deep Learning Layers for Constrained Resource Inference on Wearables. - Sourav Bhattacharya; Nicholas D. Lane (SenSys, 2016)

X-CNN: Cross-modal convolutional neural networks for sparse datasets. - Petar Velickovic; Duo Wang; Nicholas D. Lane; Pietro Liò (SSCI, 2016)

Density-aware compressive crowdsensing. - Xiaohong Hao; Liwen Xu; Nicholas D. Lane; Xin Liu 002; Thomas Moscibroda (IPSN, 2017)

Accelerating Mobile Audio Sensing Algorithms through On-Chip GPU Offloading. - Petko Georgiev; Nicholas D. Lane; Cecilia Mascolo; David Chu (MobiSys, 2017)

DeepEye: Resource Efficient Local Execution of Multiple Deep Vision Models using Wearable Commodity Hardware. - Akhil Mathur; Nicholas D. Lane; Sourav Bhattacharya; Aidan Boran; Claudio Forlivesi; Fahim Kawsar (MobiSys, 2017)

Scaling health analytics to millions without compromising privacy using deep distributed behavior models. - Petar Velickovic; Nicholas D. Lane; Sourav Bhattacharya; Angela Chieh; Otmane Bellahsen; Matthieu Vegreville (PervasiveHealth, 2017)

Behavior Recognition Based on Wi-Fi CSI: Part 1. - Bin Guo 001; Yingying (Jennifer) Chen; Nicholas D. Lane; Yunxin Liu 001; Zhiwen Yu 001 (IEEE Commun. Mag., 2017)

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics. - Seyed Ali Ossia; Ali Shahin Shamsabadi; Ali Taheri; Hamid R. Rabiee; Nicholas D. Lane; Hamed Haddadi (CoRR, 2017)

Cross-modal Recurrent Models for Human Weight Objective Prediction from Multimodal Time-series Data. - Petar Velickovic; Laurynas Karazija; Nicholas D. Lane; Sourav Bhattacharya; Edgar Liberis; Pietro Liò; Angela Chieh; Otmane Bellahsen; Matthieu Vegreville (CoRR, 2017)

Privacy-Preserving Deep Inference for Rich User Data on The Cloud. - Seyed Ali Ossia; Ali Shahin Shamsabadi; Ali Taheri; Kleomenis Katevas; Hamid R. Rabiee; Nicholas D. Lane; Hamed Haddadi (CoRR, 2017)

Low-resource Multi-task Audio Sensing for Mobile and Embedded Devices via Shared Deep Neural Network Representations. - Petko Georgiev; Sourav Bhattacharya; Nicholas D. Lane; Cecilia Mascolo (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017)

Multimodal Deep Learning for Activity and Context Recognition. - Valentin Radu; Catherine Tong; Sourav Bhattacharya; Nicholas D. Lane; Cecilia Mascolo; Mahesh K. Marina; Fahim Kawsar (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017)

Gain Without Pain: Accurate WiFi-based Localization using Fingerprint Spatial Gradient. - Chenshu Wu; Jingao Xu; Zheng Yang 002; Nicholas D. Lane; Zuwei Yin (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017)

Squeezing Deep Learning into Mobile and Embedded Devices. - Nicholas D. Lane; Sourav Bhattacharya; Akhil Mathur; Petko Georgiev; Claudio Forlivesi; Fahim Kawsar (IEEE Pervasive Comput., 2017)

Monitoring Daily Activities of Multiple Sclerosis Patients with Connected Health Devices. - Sourav Bhattacharya; Alberto Gil C. P. Ramos; Fahim Kawsar; Nicholas D. Lane; Lynn M. Gionta; Joanne Manidis; Greg Silvesti; Matthieu Vegreville (UbiComp/ISWC Adjunct, 2018)

On Robustness of Cloud Speech APIs: An Early Characterization. - Akhil Mathur; Anton Isopoussu; Fahim Kawsar; Robert Smith; Nicholas D. Lane; Nadia Berthouze (UbiComp/ISWC Adjunct, 2018)

Deterministic Binary Filters for Convolutional Neural Networks. - Vincent W. S. Tseng; Sourav Bhattacharya; Javier Fernández-Marqués; Milad Alizadeh; Catherine Tong; Nicholas D. Lane (IJCAI, 2018)

Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices. - Akhil Mathur; Tianlin Zhang; Sourav Bhattacharya; Petar Velickovic; Leonid Joffe; Nicholas D. Lane; Fahim Kawsar; Pietro Liò (IPSN, 2018)

Embracing Spatial Awareness for Reliable WiFi-Based Indoor Location Systems. - Jingao Xu; Zheng Yang 002; Hengjie Chen; Yunhao Liu 001; Xiancun Zhou; Jianbo Li; Nicholas D. Lane (MASS, 2018)

Using Pre-trained Full-Precision Models to Speed Up Training Binary Networks For Mobile Devices. - Milad Alizadeh; Nicholas D. Lane (MobiSys, 2018)

Deterministic binary filters for keyword spotting applications. - Javier Fernández-Marqués; Vincent W. S. Tseng; Sourav Bhattacharya; Nicholas D. Lane (MobiSys, 2018)

On-the-fly deterministic binary filters for memory efficient keyword spotting applications on embedded devices. - Javier Fernández-Marqués; Vincent W. S. Tseng; Sourav Bhattacharya; Nicholas D. Lane (EMDL@MobiSys, 2018)

Inference of Big-Five Personality Using Large-scale Networked Mobile and Appliance Data. - Catherine Tong; Gabriella M. Harari; Angela Chieh; Otmane Bellahsen; Matthieu Vegreville; Eva Roitmann; Nicholas D. Lane (MobiSys, 2018)

Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data. - Petar Velickovic; Laurynas Karazija; Nicholas D. Lane; Sourav Bhattacharya; Edgar Liberis; Pietro Liò; Angela Chieh; Otmane Bellahsen; Matthieu Vegreville (PervasiveHealth, 2018)

Behavior Recognition Based on Wi-Fi CSI: Part 2. - Bin Guo 001; Yingying (Jennifer) Chen; Nicholas D. Lane; Yunxin Liu 001; Zhiwen Yu 001 (IEEE Commun. Mag., 2018)

The Deep (Learning) Transformation of Mobile and Embedded Computing. - Nicholas D. Lane; Pete Warden (Computer, 2018)

Robust Cross-View Gait Identification with Evidence: A Discriminant Gait GAN (DiGGAN) Approach on 10000 People. - BingZhang Hu; Yan Gao 016; Yu Guan; Yang Long 001; Nicholas D. Lane; Thomas Ploetz (CoRR, 2018)

Towards the Design and Evaluation of Robust Audio-Sensing Systems. - Akhil Mathur; Anton Isopoussu; Fahim Kawsar; Robert Smith; Nadia Berthouze; Nicholas D. Lane (Human Activity Sensing, 2019)

Learning Temporal and Bodily Attention in Protective Movement Behavior Detection. - Chongyang Wang; Min Peng 004; Temitayo A. Olugbade; Nicholas D. Lane; Amanda C. de C. Williams; Nadia Bianchi-Berthouze (ACII Workshops, 2019)

A Vision for Adaptive and Generalizable Audio-Sensing Systems. - Akhil Mathur; Fahim Kawsar; Nadia Berthouze; Nicholas D. Lane (SocialSens@CPSIoTWeek, 2019)

Unsupervised domain adaptation for robust sensory systems. - Akhil Mathur; Anton Isopoussu; Nadia Berthouze; Nicholas D. Lane; Fahim Kawsar (UbiComp/ISWC Adjunct, 2019)

Recurrent network based automatic detection of chronic pain protective behavior using MoCap and sEMG data. - Chongyang Wang; Temitayo A. Olugbade; Akhil Mathur; Amanda C. de C. Williams; Nicholas D. Lane; Nadia Bianchi-Berthouze (UbiComp, 2019)

An Empirical study of Binary Neural Networks' Optimisation. - Milad Alizadeh; Javier Fernández-Marqués; Nicholas D. Lane; Yarin Gal (ICLR (Poster), 2019)

FlexAdapt: Flexible Cycle-Consistent Adversarial Domain Adaptation. - Akhil Mathur; Anton Isopoussu; Fahim Kawsar; Nadia Bianchi-Berthouze; Nicholas D. Lane (ICMLA, 2019)

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

Mic2Mic: using cycle-consistent generative adversarial networks to overcome microphone variability in speech systems. - Akhil Mathur; Anton Isopoussu; Fahim Kawsar; Nadia Berthouze; Nicholas D. Lane (IPSN, 2019)

MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors. - Royson Lee; Stylianos I. Venieris; Lukasz Dudziak; Sourav Bhattacharya; Nicholas D. Lane (MobiCom, 2019)

Poster: MobiSR - Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors. - Royson Lee; Stylianos I. Venieris; Lukasz Dudziak; Sourav Bhattacharya; Nicholas D. Lane (MobiCom, 2019)

Automatic Detection of Protective Behavior in Chronic Pain Physical Rehabilitation: A Recurrent Neural Network Approach. - Chongyang Wang; Temitayo A. Olugbade; Akhil Mathur; Amanda C. de C. Williams; Nicholas D. Lane; Nadia Bianchi-Berthouze (CoRR, 2019)

Learning Bodily and Temporal Attention in Protective Movement Behavior Detection. - Chongyang Wang; Min Peng 004; Temitayo A. Olugbade; Nicholas D. Lane; Amanda C. de C. Williams; Nadia Bianchi-Berthouze (CoRR, 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)

Neural networks on microcontrollers: saving memory at inference via operator reordering. - Edgar Liberis; Nicholas D. Lane (CoRR, 2019)

Tracking Fatigue and Health State in Multiple Sclerosis Patients Using Connnected Wellness Devices. - Catherine Tong; Matthew Craner; Matthieu Vegreville; Nicholas D. Lane (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2019)

Pervasive Data Science and AI. - Nigel Davies 001; Nicholas D. Lane; Mirco Musolesi (IEEE Pervasive Comput., 2019)

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)

Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions. - Royson Lee; Stylianos I. Venieris; Nicholas D. Lane (DistributedML@CoNEXT, 2020)

Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator. - Mohamed S. Abdelfattah; Lukasz Dudziak; Thomas Chau 001; Royson Lee; Hyeji Kim; Nicholas D. Lane (DAC, 2020)

Journey Towards Tiny Perceptual Super-Resolution. - Royson Lee; Lukasz Dudziak; Mohamed S. Abdelfattah; Stylianos I. Venieris; Hyeji Kim; Hongkai Wen 001; Nicholas D. Lane (ECCV (26), 2020)

EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions. - Joy O. Egede; Siyang Song; Temitayo A. Olugbade; Chongyang Wang; Amanda C. de C. Williams; Hongying Meng; Min S. Hane Aung; Nicholas D. Lane; Michel F. Valstar; Nadia Bianchi-Berthouze (FG, 2020)

Codesign-NAS: Automatic FPGA/CNN Codesign Using Neural Architecture Search. - Mohamed S. Abdelfattah; Lukasz Dudziak; Thomas Chau 001; Royson Lee; Hyeji Kim; Nicholas D. Lane (FPGA, 2020)

Libri-Adapt: a New Speech Dataset for Unsupervised Domain Adaptation. - Akhil Mathur; Fahim Kawsar; Nadia Berthouze; Nicholas D. Lane (ICASSP, 2020)

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

Unsupervised Domain Adaptation Under Label Space Mismatch for Speech Classification. - Akhil Mathur; Nadia Berthouze; Nicholas D. Lane (INTERSPEECH, 2020)

Iterative Compression of End-to-End ASR Model Using AutoML. - Abhinav Mehrotra; Lukasz Dudziak; Jinsu Yeo; Young-Yoon Lee; Ravichander Vipperla; Mohamed S. Abdelfattah; Sourav Bhattacharya; Samin Ishtiaq; Alberto Gil C. P. Ramos; SangJeong Lee; Daehyun Kim; Nicholas D. Lane (INTERSPEECH, 2020)

FusionRNN: Shared Neural Parameters for Multi-Channel Distant Speech Recognition. - Titouan Parcollet; Xinchi Qiu; Nicholas D. Lane (INTERSPEECH, 2020)

Quaternion Neural Networks for Multi-Channel Distant Speech Recognition. - Xinchi Qiu; Titouan Parcollet; Mirco Ravanelli; Nicholas D. Lane; Mohamed Morchid (INTERSPEECH, 2020)

Bunched LPCNet: Vocoder for Low-Cost Neural Text-To-Speech Systems. - Ravichander Vipperla; Sangjun Park; Kihyun Choo; Samin Ishtiaq; Kyoungbo Min; Sourav Bhattacharya; Abhinav Mehrotra; Alberto Gil C. P. Ramos; Nicholas D. Lane (INTERSPEECH, 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)

BRP-NAS: Prediction-based NAS using GCNs. - Lukasz Dudziak; Thomas Chau 001; Mohamed S. Abdelfattah; Royson Lee; Hyeji Kim; Nicholas D. Lane (NeurIPS, 2020)

The Final Frontier: Deep Learning in Space. - Vivek Kothari; Edgar Liberis; Nicholas D. Lane (HotMobile, 2020)

Are Accelerometers for Activity Recognition a Dead-end? - Catherine Tong; Shyam A. Tailor; Nicholas D. Lane (HotMobile, 2020)

Single Shot Structured Pruning Before Training. - Joost van Amersfoort; Milad Alizadeh; Sebastian Farquhar; Nicholas D. Lane; Yarin Gal (CoRR, 2020)

Flower: A Friendly Federated Learning Research Framework. - Daniel J. Beutel; Taner Topal; Akhil Mathur; Xinchi Qiu; Titouan Parcollet; Nicholas D. Lane (CoRR, 2020)

A first look into the carbon footprint of federated learning. - Xinchi Qiu; Titouan Parcollet; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (CoRR, 2020)

Deep Learning in the Era of Edge Computing: Challenges and Opportunities. - Mi Zhang 002; Faen Zhang; Nicholas D. Lane; Yuanchao Shu; Xiao Zeng; Biyi Fang; Shen Yan; Hui Xu (CoRR, 2020)

Countering Acoustic Adversarial Attacks in Microphone-equipped Smart Home Devices. - Sourav Bhattacharya; Dionysis Manousakas; Alberto Gil C. P. Ramos; Stylianos I. Venieris; Nicholas D. Lane; Cecilia Mascolo (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020)

IMUTube: Automatic Extraction of Virtual on-body Accelerometry from Video for Human Activity Recognition. - HyeokHyen Kwon; Catherine Tong; Harish Haresamudram; Yan Gao 016; Gregory D. Abowd; Nicholas D. Lane; Thomas Plötz (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020)

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics. - Seyed Ali Osia; Ali Shahin Shamsabadi; Sina Sajadmanesh; Ali Taheri; Kleomenis Katevas; Hamid R. Rabiee; Nicholas D. Lane; Hamed Haddadi (IEEE Internet Things J., 2020)

2020 ACM SIGMOBILE Rockstar Award: Nicholas D. Lane. - Nicholas D. Lane (GetMobile Mob. Comput. Commun., 2020)

Distilling Knowledge from Ensembles of Acoustic Models for Joint CTC-Attention End-to-End Speech Recognition. - Yan Gao 016; Titouan Parcollet; Nicholas D. Lane (ASRU, 2021)

Defensive Tensorization. - Adrian Bulat; Jean Kossaifi; Sourav Bhattacharya; Yannis Panagakis; Timothy M. Hospedales; Georgios Tzimiropoulos; Nicholas D. Lane; Maja Pantic (BMVC, 2021)

Secure aggregation for federated learning in flower. - Kwing Hei Li; Pedro Porto Buarque de Gusmão; Daniel J. Beutel; Nicholas D. Lane (DistributedML@CoNEXT, 2021)

μNAS: Constrained Neural Architecture Search for Microcontrollers. - Edgar Liberis; Lukasz Dudziak; Nicholas D. Lane (EuroMLSys@EuroSys, 2021)

unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation. - Stylianos I. Venieris; Javier Fernández-Marqués; Nicholas D. Lane (FCCM, 2021)

Temporal Kernel Consistency for Blind Video Super-Resolution. - Lichuan Xiang; Royson Lee; Mohamed S. Abdelfattah; Nicholas D. Lane; Hongkai Wen 001 (ICCVW, 2021)

Zero-Cost Proxies for Lightweight NAS. - Mohamed S. Abdelfattah; Abhinav Mehrotra; Lukasz Dudziak; Nicholas Donald Lane (ICLR, 2021)

NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition. - Abhinav Mehrotra; Alberto Gil C. P. Ramos; Sourav Bhattacharya; Lukasz Dudziak; Ravichander Vipperla; Thomas Chau 001; Mohamed S. Abdelfattah; Samin Ishtiaq; Nicholas Donald Lane (ICLR, 2021)

Degree-Quant: Quantization-Aware Training for Graph Neural Networks. - Shyam Anil Tailor; Javier Fernández-Marqués; Nicholas Donald Lane (ICLR, 2021)

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)

Are Mobile DNN Accelerators Accelerating DNNs? - Qingqing Cao; Alexandru Eugen Irimiea; Mohamed S. Abdelfattah; Aruna Balasubramanian; Nicholas D. Lane (EMDL@MobiSys, 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)

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)

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)

Predicting Patient Outcomes with Graph Representation Learning. - Emma Rocheteau; Catherine Tong; Petar Velickovic; Nicholas D. Lane; Pietro Liò (CoRR, 2021)

A first look into the carbon footprint of federated learning. - Xinchi Qiu; Titouan Parcollet; Javier Fernández-Marqués; Pedro Porto Buarque de Gusmão; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (CoRR, 2021)

Adaptive Filters and Aggregator Fusion for Efficient Graph Convolutions. - Shyam A. Tailor; Felix L. Opolka; Pietro Liò; Nicholas D. Lane (CoRR, 2021)

On-device Federated Learning with Flower. - Akhil Mathur; Daniel J. Beutel; Pedro Porto Buarque de Gusmão; Javier Fernández-Marqués; Taner Topal; Xinchi Qiu; Titouan Parcollet; Yan Gao 016; Nicholas D. Lane (CoRR, 2021)

End-to-End Speech Recognition from Federated Acoustic Models. - Yan Gao 016; Titouan Parcollet; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Daniel J. Beutel; Nicholas D. Lane (CoRR, 2021)

Zero-Cost Proxies Meet Differentiable Architecture Search. - Lichuan Xiang; Lukasz Dudziak; Mohamed S. Abdelfattah; Thomas Chau 001; Nicholas D. Lane; Hongkai Wen 001 (CoRR, 2021)

AgreementLearning: An End-to-End Framework for Learning with Multiple Annotators without Groundtruth. - Chongyang Wang; Yuan Gao 024; Chenyou Fan; Junjie Hu 003; Tin Lun Lam; Nicholas D. Lane; Nadia Bianchi-Berthouze (CoRR, 2021)

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

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. - Alexandros Karargyris; Renato Umeton; Micah J. Sheller; Alejandro Aristizabal; Johnu George; Srini Bala; Daniel J. Beutel; Victor Bittorf; Akshay Chaudhari; Alexander Chowdhury; Cody Coleman; Bala Desinghu; et al. (CoRR, 2021)

Differentiable Network Pruning for Microcontrollers. - Edgar Liberis; Nicholas D. Lane (CoRR, 2021)

Chronic Pain Protective Behavior Detection with Deep Learning. - Chongyang Wang; Temitayo A. Olugbade; Akhil Mathur; Amanda C. de C. Williams; Nicholas D. Lane; Nadia Bianchi-Berthouze (ACM Trans. Comput. Heal., 2021)

Zero-Shot Learning for IMU-Based Activity Recognition Using Video Embeddings. - Catherine Tong; Jinchen Ge; Nicholas D. Lane (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021)

Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data. - Chongyang Wang; Yuan Gao 024; Akhil Mathur; Amanda C. de C. Williams; Nicholas D. Lane; Nadia Bianchi-Berthouze (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021)

Can You See It?: Good, So We Can Sense It! - HyeokHyen Kwon; Catherine Tong; Harish Haresamudram; Yan Gao 016; Gregory D. Abowd; Nicholas D. Lane; Thomas Ploetz (GetMobile Mob. Comput. Commun., 2021)

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

Federated Self-supervised Learning for Video Understanding. - Yasar Abbas Ur Rehman; Yan Gao 016; Jiajun Shen; Pedro Porto Buarque de Gusmão; Nicholas D. Lane (ECCV (31), 2022)

Deep learning on microcontrollers: a study on deployment costs and challenges. - Filip Svoboda; Javier Fernández-Marqués; Edgar Liberis; Nicholas D. Lane (EuroMLSys@EuroSys, 2022)

Protea: client profiling within federated systems using flower. - Wanru Zhao; Xinchi Qiu; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Nicholas D. Lane (FedEdge@MobiCom, 2022)

End-to-End Speech Recognition from Federated Acoustic Models. - Yan Gao 016; Titouan Parcollet; Salah Zaiem; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Daniel J. Beutel; Nicholas D. Lane (ICASSP, 2022)

Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients. - Milad Alizadeh; Shyam A. Tailor; Luisa M. Zintgraf; Joost van Amersfoort; Sebastian Farquhar; Nicholas Donald Lane; Yarin Gal (ICLR, 2022)

ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity. - Xinchi Qiu; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Yan Gao 016; Titouan Parcollet; Nicholas Donald Lane (ICLR, 2022)

Conditioning Sequence-to-sequence Networks with Learned Activations. - Alberto Gil Couto Pimentel Ramos; Abhinav Mehrotra; Nicholas Donald Lane; Sourav Bhattacharya (ICLR, 2022)

Do We Need Anisotropic Graph Neural Networks? - Shyam A. Tailor; Felix L. Opolka; Pietro Liò; Nicholas Donald Lane (ICLR, 2022)

Federated Self-supervised Speech Representations: Are We There Yet? - Yan Gao 016; Javier Fernández-Marqués; Titouan Parcollet; Abhinav Mehrotra; Nicholas D. Lane (INTERSPEECH, 2022)

Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design. - Hongxiang Fan; Thomas Chau 001; Stylianos I. Venieris; Royson Lee; Alexandros Kouris; Wayne Luk; Nicholas D. Lane; Mohamed S. Abdelfattah (MICRO, 2022)

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

BLOX: Macro Neural Architecture Search Benchmark and Algorithms. - Thomas Chau 001; Lukasz Dudziak; Hongkai Wen 001; Nicholas D. Lane; Mohamed S. Abdelfattah (NeurIPS, 2022)

Match to Win: Analysing Sequences Lengths for Efficient Self-Supervised Learning in Speech and Audio. - Yan Gao 016; Javier Fernández-Marqués; Titouan Parcollet; Pedro P. B. de Gusmao; Nicholas D. Lane (SLT, 2022)

Multi-DNN Accelerators for Next-Generation AI Systems. - Stylianos I. Venieris; Christos-Savvas Bouganis; Nicholas D. Lane (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)

Pex: Memory-efficient Microcontroller Deep Learning through Partial Execution. - Edgar Liberis; Nicholas D. Lane (CoRR, 2022)

Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions. - Royson Lee; Stylianos I. Venieris; Nicholas D. Lane (ACM Comput. Surv., 2022)

MobiVQA: Efficient On-Device Visual Question Answering. - Qingqing Cao; Prerna Khanna; Nicholas D. Lane; Aruna Balasubramanian (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022)

Differentiable Neural Network Pruning to Enable Smart Applications on Microcontrollers. - Edgar Liberis; Nicholas D. Lane (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022)

Wireless Localization with Spatial-Temporal Robust Fingerprints. - Danyang Li; Jingao Xu; Zheng Yang 002; Chenshu Wu; Jianbo Li; Nicholas D. Lane (ACM Trans. Sens. Networks, 2022)

FRuDA: Framework for Distributed Adversarial Domain Adaptation. - Shaoduo Gan; Akhil Mathur; Anton Isopoussu; Fahim Kawsar; Nadia Berthouze; Nicholas D. Lane (IEEE Trans. Parallel Distributed Syst., 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)

Zero-Cost Operation Scoring in Differentiable Architecture Search. - Lichuan Xiang; Lukasz Dudziak; Mohamed S. Abdelfattah; Thomas C. P. Chau; Nicholas D. Lane; Hongkai Wen 001 (AAAI, 2023)

Can Fair Federated Learning Reduce the need for Personalisation? - Alex Iacob; Pedro Porto Buarque de Gusmão; Nicholas D. Lane (EuroMLSys@EuroSys, 2023)

Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates. - Chenyang Ma; Xinchi Qiu; Daniel J. Beutel; Nicholas D. Lane (EuroMLSys@EuroSys, 2023)

L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning. - Yasar Abbas Ur Rehman; Yan Gao 016; Pedro Porto Buarque de Gusmão; Mina Alibeigi; Jiajun Shen; Nicholas D. Lane (ICCV, 2023)

Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads. - Hongxiang Fan; Stylianos I. Venieris; Alexandros Kouris; Nicholas D. Lane (MICRO, 2023)

FedL2P: Federated Learning to Personalize. - Royson Lee; Minyoung Kim 001; Da Li 001; Xinchi Qiu; Timothy M. Hospedales; Ferenc Huszar; Nicholas D. Lane (NeurIPS, 2023)

Learn2Agree: Fitting with Multiple Annotators Without Objective Ground Truth. - Chongyang Wang; Yuan Gao 024; Chenyou Fan; Junjie Hu 003; Tin Lum Lam; Nicholas D. Lane; Nadia Bianchi-Berthouze (TML4H, 2023)

FedVal: Different good or different bad in federated learning. - Viktor Valadi; Xinchi Qiu; Pedro Porto Buarque de Gusmão; Nicholas D. Lane; Mina Alibeigi (USENIX Security Symposium, 2023)

Decentralized Training of 3D Lane Detection with Automatic Labeling Using HD Maps. - Yadong Mao; Zhuqi Xiao; Che-Tsung Lin; Pedro Porto Buarque de Gusmão; Nicholas D. Lane; Christopher Zach; Mina Alibeigi (VTC2023-Spring, 2023)

A Federated Learning Benchmark for Drug-Target Interaction. - Gianluca Mittone; Filip Svoboda; Marco Aldinucci; Nicholas D. Lane; Pietro Lió (WWW (Companion Volume), 2023)

A Federated Learning Benchmark for Drug-Target Interaction. - Filip Svoboda; Gianluca Mittone; Nicholas D. Lane; Pietro Liò (CoRR, 2023)

Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates. - Chenyang Ma; Xinchi Qiu; Daniel J. Beutel; Nicholas D. Lane (CoRR, 2023)

Efficient Vertical Federated Learning with Secure Aggregation. - Xinchi Qiu; Heng Pan; Wanru Zhao; Chenyang Ma; Pedro Porto Buarque de Gusmão; Nicholas D. Lane (CoRR, 2023)

Privacy in Multimodal Federated Human Activity Recognition. - Alex Iacob; Pedro Porto Buarque de Gusmão; Nicholas D. Lane; Armand K. Koupai; Mohammud Junaid Bocus; Raúl Santos-Rodríguez; Robert J. Piechocki; Ryan McConville (CoRR, 2023)

vFedSec: Efficient Secure Aggregation for Vertical Federated Learning via Secure Layer. - Xinchi Qiu; Heng Pan; Wanru Zhao; Chenyang Ma; Pedro P. B. de Gusmao; Nicholas D. Lane (CoRR, 2023)

Are We There Yet? Product Quantization and its Hardware Acceleration. - Javier Fernández-Marqués; Ahmed F. AbouElhamayed; Nicholas D. Lane; Mohamed S. Abdelfattah (CoRR, 2023)

High-throughput Simulation of Federated Learning via Resource-Aware Client Placement. - Lorenzo Sani; Pedro Porto Buarque de Gusmão; Alex Iacob; Wanru Zhao; Xinchi Qiu; Yan Gao 016; Javier Fernández-Marqués; Nicholas Donald Lane (CoRR, 2023)

FDAPT: Federated Domain-adaptive Pre-training for Language Models. - Lekang Jiang; Filip Svoboda; Nicholas D. Lane (CoRR, 2023)

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)

How Much Is Hidden in the NAS Benchmarks? Few-Shot Adaptation of a NAS Predictor. - Hrushikesh Loya; Lukasz Dudziak; Abhinav Mehrotra; Royson Lee; Javier Fernández-Marqués; Nicholas D. Lane; Hongkai Wen 001 (CoRR, 2023)

A First Look into the Carbon Footprint of Federated Learning. - Xinchi Qiu; Titouan Parcollet; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Yan Gao 016; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (J. Mach. Learn. Res., 2023)

Multiple-Deep Neural Network Accelerators for Next-Generation Artificial Intelligence Systems. - Stylianos I. Venieris; Christos-Savvas Bouganis; Nicholas D. Lane (Computer, 2023)

Federated benchmarking of medical artificial intelligence with MedPerf. - Alexandros Karargyris; Renato Umeton; Micah J. Sheller; Alejandro Aristizabal; Johnu George; Anna Wuest; Sarthak Pati; Hasan Kassem; Maximilian Zenk; Ujjwal Baid; Prakash Narayana Moorthy; Alexander Chowdhury; et al. (Nat. Mac. Intell., 2023)

Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation. - Stylianos I. Venieris; Javier Fernández-Marqués; Nicholas D. Lane (ACM Trans. Design Autom. Electr. Syst., 2023)

Federated Learning with Swift: An Extension of Flower and Performance Evaluation. - Maximilian Kapsecker; Daniel N. Nugraha; Christoph Weinhuber; Nicholas D. Lane; Stephan M. Jonas (SoftwareX, 2023)

Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages. - Wanru Zhao; Yihong Chen; Royson Lee; Xinchi Qiu; Yan Gao 016; Hongxiang Fan; Nicholas Donald Lane (ICLR, 2024)

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)

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)

Towards Neural Architecture Search through Hierarchical Generative Modeling. - Lichuan Xiang; Lukasz Dudziak; Mohamed S. Abdelfattah; Abhinav Mehrotra; Nicholas Donald Lane; Hongkai Wen 001 (ICML, 2024)

CLUES: Collaborative Private-domain High-quality Data Selection for LLMs via Training Dynamics. - Wanru Zhao; Hongxiang Fan; Shell Xu Hu; Wangchunshu Zhou; Nicholas D. Lane (NeurIPS, 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)

Federated Learning Priorities Under the European Union Artificial Intelligence Act. - Herbert Woisetschläger; Alexander Erben; Bill Marino; Shiqiang Wang 001; Nicholas D. Lane; Ruben Mayer; Hans-Arno Jacobsen (CoRR, 2024)

FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients. - Xinchi Qiu; Yan Gao 016; Lorenzo Sani; Heng Pan; Wanru Zhao; Pedro P. B. de Gusmao; Mina Alibeigi; Alex Iacob; Nicholas D. Lane (CoRR, 2024)

Enhancing Data Quality in Federated Fine-Tuning of Foundation Models. - Wanru Zhao; Yaxin Du; Nicholas Donald Lane; Siheng Chen; Yanfeng Wang 001 (CoRR, 2024)

Aardvark Weather: end-to-end data-driven weather forecasting. - Anna Vaughan; Stratis Markou; Will Tebbutt; James Requeima; Wessel P. Bruinsma; Tom R. Andersson; Michael Herzog; Nicholas D. Lane; J. Scott Hosking; Richard E. Turner (CoRR, 2024)

Attacks on Third-Party APIs of Large Language Models. - Wanru Zhao; Vidit Khazanchi; Haodi Xing; Xuanli He; Qiongkai Xu; Nicholas Donald Lane (CoRR, 2024)

The Future of Large Language Model Pre-training is Federated. - Lorenzo Sani; Alex Iacob; Zeyu Cao; Bill Marino; Yan Gao 016; Tomás Paulik; Wanru Zhao; William F. Shen; Preslav Aleksandrov; Xinchi Qiu; Nicholas D. Lane (CoRR, 2024)

Worldwide Federated Training of Language Models. - Alex Iacob; Lorenzo Sani; Bill Marino; Preslav Aleksandrov; William F. Shen; Nicholas Donald Lane (CoRR, 2024)

Sheaf HyperNetworks for Personalized Federated Learning. - Bao Nguyen; Lorenzo Sani; Xinchi Qiu; Pietro Liò; Nicholas D. Lane (CoRR, 2024)

Compliance Cards: Computational Artifacts for Automated AI Regulation Compliance. - Bill Marino; Preslav Aleksandrov; Carwyn Rahman; Yulu Pi; Bill Shen; Rui-Jie Yew; Nicholas D. Lane (CoRR, 2024)

PISTOL: Dataset Compilation Pipeline for Structural Unlearning of LLMs. - Xinchi Qiu; William F. Shen; Yihong Chen; Nicola Cancedda; Pontus Stenetorp; Nicholas D. Lane (CoRR, 2024)

Supercharging Federated Learning with Flower and NVIDIA FLARE. - Holger R. Roth; Daniel J. Beutel; Yan Cheng; Javier Fernández-Marqués; Heng Pan; Chester Chen; Zhihong Zhang 001; Yuhong Wen; Sean Yang; Isaac Yang; Yuan-Ting Hsieh; Ziyue Xu 001; et al. (CoRR, 2024)

Small Language Models: Survey, Measurements, and Insights. - Zhenyan Lu; Xiang Li 067; Dongqi Cai 001; Rongjie Yi; Fangming Liu; Xiwen Zhang; Nicholas D. Lane; Mengwei Xu (CoRR, 2024)

Space for Improvement: Navigating the Design Space for Federated Learning in Satellite Constellations. - Grace Kim; Luca Powell; Filip Svoboda; Nicholas D. Lane (CoRR, 2024)

Photon: Federated LLM Pre-Training. - Lorenzo Sani; Alex Iacob; Zeyu Cao; Royson Lee; Bill Marino; Yan Gao 016; Dongqi Cai 001; Zexi Li; Wanru Zhao; Xinchi Qiu; Nicholas D. Lane (CoRR, 2024)

FedMMA-HAR: Federated Learning for Human Activity Recognition With Missing Modalities Using Head-Worn Wearables. - Alessandro Gobbetti; Martin Gjoreski; Hristijan Gjoreski; Nicholas D. Lane; Marc Langheinrich (IEEE Pervasive Comput., 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)

NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution. - Stylianos I. Venieris; Mário Almeida; Royson Lee; Nicholas D. Lane (IEEE Trans. Mob. Comput., 2024)

Demystifying Small Language Models for Edge Deployment. - Zhenyan Lu; Xiang Li 067; Dongqi Cai 001; Rongjie Yi; Fangming Liu; Wei Liu 061; Jian Luan 001; Xiwen Zhang; Nicholas D. Lane; Mengwei Xu (ACL (1), 2025)

Exploring Code Language Models for Automated HLS-based Hardware Generation: Benchmark, Infrastructure and Analysis. - Jiahao Gai; Hao Chen; Zhican Wang; Hongyu Zhou; Wanru Zhao; Nicholas D. Lane; Hongxiang Fan (ASP-DAC, 2025)

SparsyFed: Sparse Adaptive Federated Learning. - Adriano Guastella; Lorenzo Sani; Alex Iacob; Alessio Mora; Paolo Bellavista; Nicholas Donald Lane (ICLR, 2025)

DEPT: Decoupled Embeddings for Pre-training Language Models. - Alex Iacob; Lorenzo Sani; Meghdad Kurmanji; William F. Shen; Xinchi Qiu; Dongqi Cai 001; Yan Gao 016; Nicholas Donald Lane (ICLR, 2025)

Rapid Distributed Fine-tuning of a Segmentation Model Onboard Satellites. - Meghan Plumridge; Rasmus Maråk; Chiara Ceccobello; Pablo Gómez; Gabriele Meoni; Filip Svoboda; Nicholas D. Lane (IPAS, 2025)

End-to-end data-driven weather prediction. - Anna Allen; Stratis Markou; Will Tebbutt; James Requeima; Wessel P. Bruinsma; Tom R. Andersson; Michael Herzog; Nicholas D. Lane; Matthew Chantry; J. Scott Hosking; Richard E. Turner (Nat., 2025)

PQA: Exploring the Potential of Product Quantization in DNN Hardware Acceleration. - Ahmed F. AbouElhamayed; Angela Cui; Javier Fernández-Marqués; Nicholas D. Lane; Mohamed S. Abdelfattah (ACM Trans. Reconfigurable Technol. Syst., 2025)

A Survey on Federated Learning in Human Sensing. - Mohan Li; Martin Gjoreski; Pietro Barbiero; Gasper Slapnicar; Mitja Lustrek; Nicholas D. Lane; Marc Langheinrich (CoRR, 2025)

LUNAR: LLM Unlearning via Neural Activation Redirection. - William F. Shen; Xinchi Qiu; Meghdad Kurmanji; Alex Iacob; Lorenzo Sani; Yihong Chen; Nicola Cancedda; Nicholas D. Lane (CoRR, 2025)

Bridge the Gaps between Machine Unlearning and AI Regulation. - Bill Marino; Meghdad Kurmanji; Nicholas D. Lane (CoRR, 2025)

Evidencing Unauthorized Training Data from AI Generated Content using Information Isotopes. - Tao Qi; Jinhua Yin; Dongqi Cai 001; Yueqi Xie; Huili Wang; Hu Zhiyang; Peiru Yang; Guoshun Nan; Zhili Zhou 001; Shangguang Wang; Lingjuan Lyu; Yongfeng Huang 001; et al. (CoRR, 2025)

SparsyFed: Sparse Adaptive Federated Training. - Adriano Guastella; Lorenzo Sani; Alex Iacob; Alessio Mora; Paolo Bellavista; Nicholas D. Lane (CoRR, 2025)

Editing as Unlearning: Are Knowledge Editing Methods Strong Baselines for Large Language Model Unlearning? - Zexi Li; Xiangzhu Wang; William F. Shen; Meghdad Kurmanji; Xinchi Qiu; Dongqi Cai 001; Chao Wu; Nicholas D. Lane (CoRR, 2025)

DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models. - Alex Iacob; Lorenzo Sani; Mher Safaryan; Paris Giampouras; Samuel Horváth; Andrej Jovanovic; Meghdad Kurmanji; Preslav Aleksandrov; William F. Shen; Xinchi Qiu; Nicholas D. Lane (CoRR, 2025)

Advancing AI-assisted Hardware Design with Hierarchical Decentralized Training and Personalized Inference-Time Optimization. - Hao Mark Chen; Zehuan Zhang; Wanru Zhao; Nicholas D. Lane; Hongxiang Fan (CoRR, 2025)

FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models. - Yan Gao 016; Massimo Roberto Scamarcia; Javier Fernández-Marqués; Mohammad Naseri; Chong Shen Ng; Dimitris Stripelis; Zexi Li; Tao Shen; Jiamu Bai; Daoyuan Chen; Zikai Zhang; Rui Hu; et al. (CoRR, 2025)

Cascadia: A Cascade Serving System for Large Language Models. - Youhe Jiang; Fangcheng Fu; Wanru Zhao; Stephan Rabanser; Nicholas D. Lane; Binhang Yuan (CoRR, 2025)

Accelerating 3D Gaussian Splatting with Neural Sorting and Axis-Oriented Rasterization. - Zhican Wang; Guanghui He; Dantong Liu; Lingjun Gao; Shell Xu Hu; Chen Zhang; Zhuoran Song; Nicholas D. Lane; Wayne Luk; Hongxiang Fan (CoRR, 2025)

Don't Make It Up: Preserving Ignorance Awareness in LLM Fine-Tuning. - William F. Shen; Xinchi Qiu; Nicola Cancedda; Nicholas D. Lane (CoRR, 2025)

CLUES: Collaborative High-Quality Data Selection for LLMs via Training Dynamics. - Wanru Zhao; Hongxiang Fan; Shell Xu Hu; Wangchunshu Zhou; Bofan Chen; Nicholas D. Lane (CoRR, 2025)

AbbIE: Autoregressive Block-Based Iterative Encoder for Efficient Sequence Modeling. - Preslav Aleksandrov; Meghdad Kurmanji; Fernando García-Redondo; David O'Shea; William F. Shen; Alex Iacob; Lorenzo Sani; Xinchi Qiu; Nicola Cancedda; Nicholas D. Lane (CoRR, 2025)