Imperial College London


Faculty of MedicineDepartment of Brain Sciences

Chair in Machine Intelligence Applied to Medicine



p.barnaghi Website




Sir Michael Uren HubWhite City Campus





Payam Barnaghi is Chair in Machine Intelligence Applied to Medicine and Deputy Head of Division of Neurology in the Department of Brain Sciences at Imperial College London. He is a Principal Investigator and Group Lead for Translational Machine Intelligence in the Care Research and Technology Centre at the UK Dementia Research Institute. He is an associate editor of the IEEE Transactions on Big Data and vice-chair of the IEEE SIG on Big Data Intelligent Networking. He is a Visiting Professor at the Great Ormond Street Institute of Child Health at University College London.

He is also an NVIDIA Deep Learning Institute (DLI) University Ambassador. 

His main research goal is to develop AI and machine learning solutions for healthcare and create affordable and scalable digital systems that can be applied across a range of health conditions. He works on machine learning, Internet of Things (IoT), semantic computing, adaptive algorithms and computational neuroscience to solve problems and develop new technologies for future healthcare systems. 

Lab Homepage:

Personal Homepage:

UK DRI Homepage:


Recent Projects

  • Principal Investigator, PROTECT: Predictive approaches in managing long-term conditions: from remote monitoring data to digital biomarkers, The Engineering and Physical Sciences Research Council (EPSRC)/NIHR (Sep. 2022 - Aug. 2025).
  • Principal Investigator and Programme Lead (Translational Machine Intelligence), Care Research and Technology Centre, The UK Dementia Research Institute (UK DRI), funded by: MRC, Alzheimer's Society, Alzheimer's Research UK, Programme Lead for: Translational Machine Intelligence (Apr. 2019 - Mar. 2028).
  • Continual learning models for personalised paediatric digital consultation, PhD studentship, Great Ormond Street Hospital/UCL Institute of Child Health, Nov 2023 - Oct 2027.
  • Principal Investigator, Infrastructure for a Trusted Research Environment to Support Cost-effective and Flexible Processing of Healthcare Data, World-Class Labs capital equipment award, MRC, (2021-2022).
  • Principal Investigator, Automated Body Monitoring System, Industry funding (Minebea Mitsumi-Intec)  (Oct. 2018 - Sept. 2020).



  •  Mentorship Award, Department of Brain Sciences, Imperial College London
  • Outstanding Service Award, The Web Intelligence Consortium (WIC), October 2019
  • IEEE Outstanding Leadership Award 2017
  • The Most Outstanding Innovation, Guildford's Innovation Awards (TIHM for Dementia Project)
  • HSJ 2018 Award for Improving Care with Technology (TIHM for Dementia Project)
  • Regional NHS Parliamentary Award, NHS 70th Anniversary, 2018 (TIHM for Dementia Project)
  • Best Mental Health Initiative Award, EHI 2017 Awards (TIHM for Dementia Project)

Selected Publications

Journal Articles

Capstick A, Palermo F, Zakka K, et al., 2024, Digital remote monitoring for screening and early detection of urinary tract infections, Npj Digital Medicine, Vol:7, ISSN:2398-6352

Raposo de Lima M, Vaidyanathan R, Barnaghi P, 2023, Discovering behavioural patterns using conversational technology for in-home health and well-being monitoring, Ieee Internet of Things Journal, Vol:10, ISSN:2327-4662, Pages:18537-18552

Palermo F, Chen Y, Capstick A, et al., 2023, TIHM: an open dataset for remote healthcare monitoring in dementia, Scientific Data, Vol:10, ISSN:2052-4463, Pages:1-10

Hine C, Nilforooshan R, Barnaghi P, 2023, Negotiating the capacities and limitations of sensor-mediated care in the home, Journal of Computer-Mediated Communication, Vol:28, ISSN:1083-6101

Fletcher-Lloyd N, Serban A-I, Kolanko M, et al., 2023, A Markov chain model for identifying changes in daily activity patterns of people living with dementia, Ieee Internet of Things Journal, ISSN:2327-4662

Lima MR, Wairagkar M, Gupta M, et al., 2022, Conversational affective social robots for ageing and dementia support, Ieee Transactions on Cognitive and Developmental Systems, Vol:14, ISSN:2379-8920, Pages:1378-1397

Serban A-I, Soreq E, Barnaghi P, et al., 2022, The effect of COVID-19 on the home behaviours of people affected by dementia, Npj Digital Medicine, Vol:5, ISSN:2398-6352

Kalantari E, Kouchaki S, Miaskowski C, et al., 2022, Network analysis to identify symptoms clusters and temporal interconnections in oncology patients, Scientific Reports, Vol:12, ISSN:2045-2322

Wairagkar M, Lima MR, Bazo D, et al., 2022, Emotive response to a hybrid-face robot and translation to consumer social robots, Ieee Internet of Things Journal, Vol:9, ISSN:2327-4662, Pages:3174-3188

Hine C, Nilforooshan R, Barnaghi P, 2022, Ethical considerations in design and implementation of home-based smart care for dementia, Nursing Ethics, Vol:29, ISSN:0969-7330, Pages:1035-1046

Fletcher-Lloyd N, Soreq E, Wilson D, et al., 2021, Home monitoring of daily living activities and prediction of agitation risk in a cohort of people living with dementia., Alzheimers & Dementia, Vol:17, ISSN:1552-5260, Pages:1-1

Rezvani R, Barnaghi P, Enshaeifar S, 2021, A New Pattern Representation Method for Time-Series Data, IEEE Transactions on Knowledge and Data Engineering, Vol:33, ISSN:1041-4347, Pages:2818-2832

Li H, Barnaghi P, Enshaeifar S, et al., 2020, Continual learning using Bayesian neural networks, Ieee Transactions on Neural Networks and Learning Systems, Vol:32, ISSN:2162-2388, Pages:4243-4252

Fathy Y, Barnaghi P, 2019, Quality-Based and Energy-Efficient Data Communication for the Internet of Things Networks, Ieee Internet of Things Journal, Vol:6, ISSN:2327-4662, Pages:10318-10331

Fathy Y, Barnaghi P, Tafazolli R, 2019, An Online Adaptive Algorithm for Change Detection in Streaming Sensory Data, IEEE Systems Journal, Vol:13, ISSN:1932-8184, Pages:2688-2699

Kolozali S, Bermudez-Edo M, FarajiDavar N, et al., 2019, Observing the Pulse of a City: A Smart City Framework for Real-Time Discovery, Federation, and Aggregation of Data Streams, Ieee Internet of Things Journal, Vol:6, ISSN:2327-4662, Pages:2651-2668

Papachristou N, Barnaghi P, Cooper B, et al., 2019, Network analysis of the multidimensional symptom experience of oncology, Scientific Reports, Vol:9, ISSN:2045-2322, Pages:1-11

Enshaeifar S, Zoha A, Skillman S, et al., 2019, Machine learning methods for detecting urinary tract infection and analysing daily living activities in people with dementia, PLOS One, Vol:14, ISSN:1932-6203

van den Brink L, Barnaghi P, Tandy J, et al., 2019, Best practices for publishing, retrieving, and using spatial data on the web, Semantic Web, Vol:10, ISSN:1570-0844, Pages:95-114

Papachristou N, Puschmann D, Barnaghi P, et al., 2018, Learning from data to predict future symptoms of oncology patients, PLOS One, Vol:13, ISSN:1932-6203, Pages:1-17

Gonzalez-Vidal A, Barnaghi P, Skarmeta AF, 2018, BEATS: Blocks of Eigenvalues Algorithm for Time Series Segmentation, IEEE Transactions on Knowledge and Data Engineering, Vol:30, ISSN:1041-4347, Pages:2051-2064

Puschmann D, Barnaghi P, Tafazolli R, 2018, Using LDA to Uncover the Underlying Structures and Relations in Smart City Data Streams, IEEE Systems Journal, Vol:12, ISSN:1932-8184, Pages:1755-1766

Fathy Y, Barnaghi P, Tafazolli R, 2018, Large-Scale Indexing, Discovery, and Ranking for the Internet of Things (IoT), ACM Computing Surveys, Vol:51, ISSN:0360-0300

Hoseinitabatabaei SA, Fathy Y, Barnaghi P, et al., 2018, A Novel Indexing Method for Scalable IoT Source Lookup, Ieee Internet of Things Journal, Vol:5, ISSN:2327-4662, Pages:2037-2054

Enshaeifar S, Zoha A, Markides A, et al., 2018, Health management and pattern analysis of daily living activities of people with dementia using in-home sensors and machine learning techniques, PLOS One, Vol:13, ISSN:1932-6203, Pages:1-20

Papachristou N, Barnaghi P, Cooper BA, et al., 2018, Congruence between latent class and K-modes analyses in the identification of oncology patients with distinct symptom experiences, Journal of Pain and Symptom Management, Vol:55, ISSN:0885-3924, Pages:318-333.e4

Enshaeifar S, Barnaghi P, Skillman S, et al., 2018, The Internet of Things for Dementia Care, IEEE Internet Computing, Vol:22, ISSN:1089-7801, Pages:8-17

Puschmann D, Barnaghi P, Tafazolli R, 2017, Adaptive Clustering for Dynamic IoT Data Streams, Ieee Internet of Things Journal, Vol:4, ISSN:2327-4662, Pages:64-74


Huang Y, Zhao Y, Haddadi H, et al., 2022, Using entropy measures for monitoring the evolution of activity patterns, IEEE 8th World Forum on Internet of Things, IEEE

Zhao Y, Barnaghi P, Haddadi H, 2022, Multimodal federated learning on IoT data, 2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI), IEEE

Enshaeifar S, Barnaghi P, Skillman S, et al., 2020, A Digital Platform for Remote Healthcare Monitoring, 29th World Wide Web Conference (WWW), ASSOC COMPUTING MACHINERY, Pages:203-206

Zhao Y, Haddadi H, Skillman S, et al., 2020, Privacy-preserving Activity and Health Monitoring on Databox, 3rd ACM International Workshop on Edge Systems, Analytics and Networking (EdgeSys), ASSOC COMPUTING MACHINERY, Pages:49-54

Nilforooshan R, Rostill H, Barnaghi P, et al., 2019, Transforming care for people with dementia using the Internet of Things, UBIQUITY PRESS LTD, ISSN:1568-4156

Elsaleh T, Bermudez-Edo M, Enshaeifar S, et al., 2019, IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams, 3rd Global IoT Summit (GIoTS), IEEE


Rassam A, Barnaghi P, 2023, Methods and apparatus for adaptive interaction with remote devices, US20200119938A1

Qingju L, Barnaghi P, 2021, IoT-based intelligent bed sensor system for contactless respiratory rate monitoring

Hoseinitabatabaei SA, Barnaghi P, Dong L, et al., 2019, Scalable data discovery in an internet of things (IoT) system, US10257678B2

More Publications