Niall Twomey - Google Scholar Citations

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	All	Since 2014
Citations	452	415
h-index	10	10
i10-index	13	12

140

105

2011201220132014201520162017201820199 6 21 6 16 41 95 140 108

Co-authors

Peter FlachProfessor of Artificial Intelligence, Department of Computer Science, University of BristolVerified email at bristol.ac.uk
Tom DietheAmazon Reasearch Cambridge; Honorary Research Fellow, University of BristolVerified email at bristol.ac.uk
Ian CraddockUniversity of BristolVerified email at bristol.ac.uk
Xenofon FafoutisTechnical University of DenmarkVerified email at dtu.dk
William MarnaneDepartment of Electrical & Electronic Engineering , University College CorkVerified email at ucc.ie
Alison BurrowsSenior Research Associate in User-Centred Design, University of BristolVerified email at bristol.ac.uk
Massimo CamplaniUniversity of BrisolVerified email at bristol.ac.uk
Ni ZhuUniversity of BristolVerified email at bristol.ac.uk
Majid MirmehdiProfessor of Computer Vision, University of BristolVerified email at bristol.ac.uk
Atis ElstsInstitute of Electronics and Computer Science (EDI) and University of BristolVerified email at bristol.ac.uk
Lili TaoUniversity of Bristol, University of the West of EnglandVerified email at bristol.ac.uk
Robert PiechockiUniversity of BristolVerified email at bristol.ac.uk
Meelis KullAssociate Professor, University of TartuVerified email at ut.ee
Raul Santos-RodriguezUniversity of BristolVerified email at bristol.ac.uk
Hao SongResearch Associate, University of BristolVerified email at bristol.ac.uk
Andriy TemkoML Lead, Qualcomm; Adjunct Senior Lecturer, University College CorkVerified email at qti.qualcomm.com
Sion HannunaUniversity of BristolVerified email at bris.ac.uk
Ryan McConvilleUniversity of BristolVerified email at bristol.ac.uk
Emma TonkinUniversity of Bristol; University of Leicester; King's College London; formerly UKOLN, BathVerified email at bath.edu
Jonathan HourihaneUniversity College CorkVerified email at ucc.ie

Niall Twomey

Research Fellow, University of Bristol, United Kingdom

Verified email at bristol.ac.uk - Homepage

machine learning behavioural modelling structural learning uncertainty modelling


Title	Cited by	Year
Bridging e-health and the internet of things: The sphere project N Zhu, T Diethe, M Camplani, L Tao, A Burrows, N Twomey, D Kaleshi, ... IEEE Intelligent Systems 30 (4), 39-46, 2015	132	2015
The SPHERE challenge: Activity recognition with multimodal sensor data N Twomey, T Diethe, M Kull, H Song, M Camplani, S Hannuna, X Fafoutis, ... arXiv preprint arXiv:1603.00797, 2016	44	2016
SPHERE: A sensor platform for healthcare in a residential environment P Woznowski, A Burrows, T Diethe, X Fafoutis, J Hall, S Hannuna, ... Designing, Developing, and Facilitating Smart Cities, 315-333, 2017	34	2017
Comparison of accelerometer-based energy expenditure estimation algorithms N Twomey, S Faul, WP Marnane 2010 4th International Conference on Pervasive Computing Technologies for …, 2010	33	2010
A Comprehensive Study of Activity Recognition Using Accelerometers N Twomey, T Diethe, X Fafoutis, A Elsts, R McConville, P Flach, ... Informatics 5, 2018	25	2018
Unsupervised learning of sensor topologies for improving activity recognition in smart environments N Twomey, T Diethe, I Craddock, P Flach Neurocomputing 234, 93-106, 2017	20	2017
Active transfer learning for activity recognition T Diethe, N Twomey, P Flach European Symposium on Artificial Neural Networks, Computational Intelligence …, 2016	18	2016
Bayesian Active Transfer Learning in Smart Homes T Diethe, N Twomey, P Flach Advances in Active Learning : Bridging Theory and Practice, ICML 2015, 2015	13	2015
The effect of lossy ECG compression on QRS and HRV feature extraction N Twomey, N Walsh, O Doyle, B McGinley, M Glavin, E Jones, ... 2010 Annual International Conference of the IEEE Engineering in Medicine and …, 2010	13	2010
On-Board Feature Extraction from Acceleration Data for Activity Recognition A Elsts, R McConville, X Fafoutis, N Twomey, R Piechocki, ... Proceedings of the International Conference on Embedded Wireless Systems and …, 2018	10	2018
Bayesian modelling of the temporal aspects of smart home activity with circular statistics T Diethe, N Twomey, P Flach Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015	10	2015
Context Modulation of Sensor Data Applied to Activity Recognition in Smart Homes N Twomey, P Flach Workshop on Learning over Multiple Contexts, European Conference on Machine …, 2014	10	2014
Automated detection of perturbed cardiac physiology during oral food allergen challenge in children N Twomey, A Temko, JOB Hourihane, WP Marnane IEEE journal of biomedical and health informatics 18 (3), 1051-1057, 2013	10	2013
Probabilistic sensor fusion for ambient assisted living T Diethe, N Twomey, M Kull, P Flach, I Craddock arXiv preprint arXiv:1702.01209, 2017	9	2017
Talk, text or tag? P Woznowski, E Tonkin, P Laskowski, N Twomey, K Yordanova, ... 1st International Workshop on Annotation of useR Data for UbiquitOUs Systems …, 2017	9	2017
An RSSI-based Wall Prediction Model for Residential Floor Map Construction X Fafoutis, E Mellios, N Twomey, T Diethe, G Hilton, R Piechocki 2nd IEEE World Forum on Internet of Things (WF-IoT),, 2015	9	2015
Bayesian Active Learning with Evidence-Based Instance Selection N Twomey, T Diethe, P Flach Second International Workshop on Learning over Multiple Contexts in …, 2015	9	2015
On the need for structure modelling in sequence prediction N Twomey, T Diethe, P Flach Machine Learning 104 (2-3), 291-314, 2016	6	2016
SPHERE-a Sensor Platform for HEalthcare in a Residential Environment TR Diethe, N Twomey, P Flach	6	2014
Talk, Text, Tag? Understanding Self-Annotation of Smart Home Data from a User’s Perspective E Tonkin, A Burrows, P Woznowski, P Laskowski, K Yordanova, ... Sensors 18 (7), 2365, 2018	5	2018

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