Staff profile

Other roles

2022: PGR Director (Durham University)

2019: Chief Technical Officer (CTO), 0.5FTE, More Life (UK) Ltd: More Life is a health and well being company providing services under contract to NHS England and various local authorities. The services include weight management and smoking cessation among others. The company has been operating for 20+ year with 160+ staff.

Short Bio

Dorothy Monekosso (PhD) is Professor of Computer Science and Chief Technical Officer (CTO) at More Life UK Ltd. Dorothy holds a PhD (2000) in Spacecraft Engineering, a Master’s in Satellite Engineering from the Surrey Space Centre (University of Surrey) and Bachelor in Electronic Engineering. She began her career in space sector, developing on-board computers and control systems for spacecraft and satellites. Dorothy became interested in Artificial Intelligence during her PhD applying machine learning methods and techniques to spacecraft autonomy. On the basis of this work, she was awarded a Royal Academy of Engineering, Engineering Foresight Award. Her current research applies the same techniques to develop innovative healthcare technologies. In 2020, she was awarded an honorary fellowship of the British Computer Society for work in assistive and rehabilitation technologies.

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Social Media

www.linkedin.com/in/prof-dorothy-monekosso

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Projects

Digital Health Hub 

Insights - automated analysis using sentiment analysis 

More Life & Durham - Personalising weight management programmes (Innovate UK)

Healthy Lifestyle Programmes | MoreLife UK (more-life.co.uk)

MRC - IAA "Technology Supported Rehabilitation Impact Evaluation Study" Virtual Physiotherapist - physiotherapy at home

MRC impact acceleration accounts (previously confidence in concept) – UKRI

https://www.virtualphysioproject.com/

Grow MedTech Virtual Physiotherapist could improve stroke recovery - Grow MedTech

Digital Twins in Health

Smart homes - Supporting independent living

•  Activty recognition, behaviour modelling, 

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Supervision

If you're interested in undertaking a research project at PhD, Masters, or a 3rd/4th year undergraduate project under my supervision in assistive and rehabilitations technologies, human digital twins, applications of machine learning to healthcare technologies, and digital health please get in touch.

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• Behaviour Analytics
• Digital Twin Computing
• Anomaly detection
• Data analytics: applications of machine learning to decision support systems in health
• Digital health: wearables, assistive and rehabilitation technologies, medical image analysis, clinical decision support
• Smart Environments & Cities: supporting people to live independently

• 2022: Royal Society Diversity Committee - member:
• 2021: BCS - British Computer Society, Fellows Technical Advisory Group (F-TAG): BCS Fellows Technical Advisory Group (F-TAG) - member
• 2020: World Economic Forum:
• 2020: Commissioner at Digital Futures Commission: Commissioner at the Digital Futures Commission - a research collaboration of unique organisations that invites innovators, policy makers, regulators, academics and civil society, to unlock digital innovation in the interests of children and young people.
• 2019: Expert Evaluator: R&I Projects Unit, Research Promotion Foundation, Cyprus
  Central Finance and Contracting Agency, Riga, Latvia
  National Science Centre, Warsaw, Poland
  HORIZON2020
  
  
• 2019: Research Impact: Promoting the diversity of impacts that Knowledge Exchange and Commercialisation can deliver at the RE Connecting Capability Fund’s Technology & Talent Showcase at
  @ImperialColl
• 2019: UKRI - Peer Review College / SIFT Panel Member: Future Leaders Fellowships SIFT Panel Member

Chapter in book

• Espina, M. V., Grech, R., De Jager, D., Remagnino, P., Iocchi, L., Marchetti, L., …King, C. (2011). Multi-robot Teams for Environmental Monitoring. In P. Remagnino, D. Monekosso, & L. Jain (Eds.), INNOVATIONS IN DEFENCE SUPPORT SYSTEMS - 3: INTELLIGENT PARADIGMS IN SECURITY (183-209)
• Monekosso, D. N., Remagnino, P., & Kuno, Y. (2009). Intelligent Environments: Methods, Algorithms and Applications. In D. Monekosso, P. Remagnino, & Y. Kuno (Eds.), INTELLIGENT ENVIRONMENTS: METHODS, ALGORITHMS AND APPLICATIONS (1-11). https://doi.org/10.1007/978-1-84800-346-0%5C_1
• Zhan, B., Remagnino, P., Monekosso, D., & Velastin, S. (2009). The Analysis of Crowd Dynamics: From Observations to Modelling. In C. Mumford, & L. Jain (Eds.), COMPUTATIONAL INTELLIGENCE: COLLABORATION, FUSION AND EMERGENCE (441-472)
• Monekosso, D. N., & Remagnino, P. (2009). Anomalous Behavior Detection: Supporting Independent Living. In D. Monekosso, P. Remagnino, & Y. Kuno (Eds.), INTELLIGENT ENVIRONMENTS: METHODS, ALGORITHMS AND APPLICATIONS (35-50). https://doi.org/10.1007/978-1-84800-346-0%5C_3
• Zhan, B., Monekosso, D., Rush, S., Remagnino, P., & Velastin, S. (2009). Augmenting Professional Training, an Ambient Intelligence Approach. In D. Monekosso, P. Remagnino, & Y. Kuno (Eds.), INTELLIGENT ENVIRONMENTS: METHODS, ALGORITHMS AND APPLICATIONS (109-125). https://doi.org/10.1007/978-1-84800-346-0%5C_7

Conference Paper

• Oghaz, M. M. D., Argyriou, V., Monekosso, D., & Remagnino, P. (2020). Skin Identification Using Deep Convolutional Neural Network. In G. Bebis, R. Boyle, B. Parvin, D. Koracin, D. Ushizima, S. Chai, …P. Xu (Eds.), . https://doi.org/10.1007/978-3-030-33720-9%5C_14
• Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2020). Latent Bernoulli Autoencoder. In H. Daume, & A. Singh (Eds.),
• Fajtl, J., Sokeh, H. S., Argyriou, V., Monekosso, D., & Remagnino, P. (2019). Summarizing Videos with Attention. In G. Carneiro, & S. You (Eds.), . https://doi.org/10.1007/978-3-030-21074-8%5C_4
• Schez-Sobrino, S., Monekosso, D. N., Remagnino, P., Vallejo, D., & Glez-Morcillo, C. (2019). Automatic recognition of physical exercises performed by stroke survivors to improve remote rehabilitation.
• Zarachoff, M., Sheikh-Akbari, A., & Monekosso, D. (2019). Single Image Ear Recognition Using Wavelet-Based Multi-Band PCA.
• Sokeh, H. S., Argyriou, V., Monekosso, D., & Remagnino, P. (2018). Superframes, A Temporal Video Segmentation.
• Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2018). AMNet: Memorability Estimation with Attention. . https://doi.org/10.1109/cvpr.2018.00666
• Zarachoff, M., Sheikh-Akbari, A., & Monekosso, D. (2018). 2D Multi-Band PCA and its Application for Ear Recognition.
• Mandal, B., Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2018). DEEP RESIDUAL NETWORK WITH SUBCLASS DISCRIMINANT ANALYSIS FOR CROWD BEHAVIOR RECOGNITION.
• Zarachoff, M., Sheikh-Akbari, A., & Monekosso, D. (2018). Application of Single Image Super-Resolution in Human Ear Recognition Using Eigenvalues.
• Jhawar, A., Chan, C. S., Monekosso, D., & Remagnino, P. (2016). Fuzzy-Rough based Decision System for Gait adopting Instance Selection.
• Tzanidou, G., Climent-Perez, P., Hummel, G., Schmitt, M., Stuetz, P., Monekosso, D. N., & Remagnino, P. (2015). Telemetry assisted frame registration and background subtraction in low-altitude UAV videos.
• Climent-Perez, P., Mauduit, A., Monekosso, D. N., & Remagnino, P. (2014). Detecting Events in Crowded Scenes using Tracklet Plots. In S. Battiato, & J. Braz (Eds.),
• Grech, R., Florez-Revuelta, F., Monekosso, D. N., & Remagnino, P. (2014). Robot Teams: Sharing Visual Memories. In M. Hsieh, & G. Chirikjian (Eds.), . https://doi.org/10.1007/978-3-642-55146-8%5C_26
• Climent-Perez, P., Monekosso, D. N., & Remagnino, P. (2014). Multi-view event detection in crowded scenes using tracklet plots. . https://doi.org/10.1109/icpr.2014.748
• Climent-Perez, P., Lazaridis, G., Hummel, G., Russ, M., Monekosso, D. N., & Remagnino, P. (2014). Telemetry-Based Search Window Correction for Airborne Tracking. In G. Bebis, R. Boyle, B. Parvin, D. Koracin, R. McMahan, J. Jerald, …M. Carlson (Eds.),
• Mullen, R. J., Monekosso, D., Barman, S., & Remagnino, P. (2013). Reactive Coordination and Adaptive Lattice Formation in Mobile Robotic Surveillance Swarms. In A. Martinoli, F. Mondada, N. Correll, G. Mermoud, M. Egerstedt, M. Hsieh, …K. Stoy (Eds.),
• Kristan, M., Pflugfelder, R., Leonardis, A., Matas, J., Porikli, F., Cehovin, L., …Niu, Z. (2013). The Visual Object Tracking VOT2013 challenge results. . https://doi.org/10.1109/iccvw.2013.20
• Padilla-Lopez, J. R., Florez-Revuelta, F., Monekosso, D. N., & Remagnino, P. (2012). The ``Good'' Brother: Monitoring People Activity in Private Spaces. In S. Omatu, J. Santana, S. Gonzalez, J. Molina, A. Bernardos, & J. Rodriguez (Eds.),
• Grech, R., Monekosso, D., de Jager, D., & Remagnino, P. (2010). A Vision-Based System for Object Identification and Information Retrieval in a Smart Home. In B. DeRuyter, R. Wichert, D. Keyson, P. Markopoulos, N. Streitz, M. Divitini, …A. Gomez (Eds.),
• Bloisi, D., Iocchi, L., Marchetti, L., Monekosso, D. N., & Remagnino, P. (2009). An Adaptive Tracker for Assisted Living. . https://doi.org/10.1109/avss.2009.96
• Monekosso, D. N., & Remagnino, P. (2009). Synthetic Training Data Generation for ADL Modeling. In M. Schneider, A. Kroner, J. Alvarado, A. Higuera, J. Augusto, D. Cook, …V. Callaghan (Eds.), . https://doi.org/10.3233/978-1-60750-056-8-137
• Vallejo, D., Remagnino, P., Monekosso, D. N., Jimenez, L., & Gonzalez, C. (2009). A Multi-agent Architecture for Multi-robot Surveillance. In N. Nguyen, R. Kowalczyk, & S. Chen (Eds.),
• Bloisi, D., Iocchi, L., Monekosso, D. N., & Remagnino, P. (2009). A NOVEL SEGMENTATION METHOD FOR CROWDED SCENES.
• Monekosso, D., & Remagnino, P. (2009). Synthetic Training Data Generation for Activity Monitoring and Behavior Analysis. In M. Tscheligi, B. DeRuyter, P. Markopoulus, R. Wichert, T. Mirlacher, A. Meschtscherjakov, & W. Reitberger (Eds.),
• Monekosso, D. N. (2008). A Hierarchical Model-Based System for Discovering Atypical Behavior.
• Monekosso, D., & Remagnino, P. (2008). Detecting Activities for Assisted Living. In M. Muhlhauser, A. Ferscha, & E. Aitenbichler (Eds.), . https://doi.org/10.1007/978-3-540-85379-4%5C_28
• Mullen, R. J., Monekosso, D., Barman, S., Remagnino, P., & Wilkin, P. (2008). Artificial Ants to Extract Leaf Outlines and Primary Venation Patterns. In M. Dorigo, M. Birattari, C. Blum, M. Clerc, T. Stutzle, & A. Winfield (Eds.),

Journal Article

• Albusac, J., Herrera, V., Schez-Sobrino, S., Grande, R., Vallejo, D., & Monekosso, D. (2023). Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach. Multimedia Tools and Applications, https://doi.org/10.1007/s11042-023-17892-4
• Albusac, J., Herrera, V., Schez-Sobrino, S., Grande, R., Monekosso, D. N., & Vallejo, D. (2023). Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach. Multimedia Tools and Applications, https://doi.org/10.1007/s11042-023-17892-4
• Herrera, V., Vallejo, D., Castro-Schez, J. J., Monekosso, D. N., de los Reyes, A., Glez-Morcillo, C., & Albusac, J. (2023). Rehab-Immersive: A framework to support the development of virtual reality applications in upper limb rehabilitation. SoftwareX, 23, Article 101412. https://doi.org/10.1016/j.softx.2023.101412
• García, F. M., Moraleda, R., Schez-Sobrino, S., Monekosso, D. N., Vallejo, D., & Glez-Morcillo, C. (2023). Health-5G: A Mixed Reality-Based System for Remote Medical Assistance in Emergency Situations. IEEE Access, 11, https://doi.org/10.1109/ACCESS.2023.3285420
• Zarachoff, M. M., Sheikh-Akbari, A., & Monekosso, D. (2022). Chainlet-Based Ear Recognition Using Image Multi-Banding and Support Vector Machine. Applied Sciences, 12(4), Article 2033. https://doi.org/10.3390/app12042033
• Gmez-Portes, C., Jesus Castro-Schez, J., Albusac, J., Monekosso, D. N., & Vallejo, D. (2021). A Fuzzy Recommendation System for the Automatic Personalization of Physical Rehabilitation Exercises in Stroke Patients. Mathematics, 9(12), Article 1427. https://doi.org/10.3390/math9121427
• Schez-Sobrino, S., Vallejo, D., Monekosso, D., Glez-Morcillo, C., & Remagnino, P. (2020). A Distributed Gamified System Based on Automatic Assessment of Physical Exercises to Promote Remote Physical Rehabilitation. IEEE Access, 8, 91424-91434. https://doi.org/10.1109/access.2020.2995119
• Gu, F., Sridhar, M., Cohn, A., Hogg, D., Florez-Revuelta, F., Monekosso, D., & Remagnino, P. (2016). Weakly supervised activity analysis with spatio-temporal localisation. Neurocomputing, 216, 778-789. https://doi.org/10.1016/j.neucom.2016.08.032
• Monekosso, D. N., Florez-Revuelta, F., & Remagnino, P. (2015). Guest Editorial Special Issue on Ambient-Assisted Living: Sensors, Methods, and Applications. IEEE Transactions on Human-Machine Systems, 45(5, SI), 545-549. https://doi.org/10.1109/thms.2015.2458019
• Gu, F., Florez-Revuelta, F., Monekosso, D., & Remagnino, P. (2015). Marginalised Stacked Denoising Autoencoders for Robust Representation of Real-Time Multi-View Action Recognition. Sensors, 15(7), 17209-17231. https://doi.org/10.3390/s150717209
• Monekosso, D., Florez-Revuelta, F., & Remagnino, P. (2015). Ambient Assisted Living. IEEE Intelligent Systems, 30(4), 2-6. https://doi.org/10.1109/mis.2015.63
• Lim, M. K., Chan, C. S., Monekosso, D., & Remagnino, P. (2014). Refined particle swarm intelligence method for abrupt motion tracking. Information Sciences, 283, 267-287. https://doi.org/10.1016/j.ins.2014.01.003
• Lim, M., Chan, C., Monekosso, D., & Remagnino, P. (2014). Detection of salient regions in crowded scenes. Electronics Letters, 50(5), 363-364. https://doi.org/10.1049/el.2013.3993
• Thida, M., Eng, H., Monekosso, D. N., & Remagnino, P. (2013). A particle swarm optimisation algorithm with interactive swarms for tracking multiple targets. Applied Soft Computing, 13(6), 3106-3117. https://doi.org/10.1016/j.asoc.2012.05.019
• Mullen, R. J., Monekosso, D. N., & Remagnino, P. (2013). Ant algorithms for image feature extraction. Expert Systems with Applications, 40(11), 4315-4332. https://doi.org/10.1016/j.eswa.2013.01.020
• Monekosso, D. N., & Remagnino, P. (2013). Data reconciliation in a smart home sensor network. Expert Systems with Applications, 40(8), 3248-3255. https://doi.org/10.1016/j.eswa.2012.12.037
• Grech, R., Monekosso, D., & Remagnino, P. (2012). Building visual memories of video streams. Electronics Letters, 48(9), 487-U36. https://doi.org/10.1049/el.2011.3926
• Monekosso, D. N., & Remagnino, P. (2010). Behavior Analysis for Assisted Living. IEEE Transactions on Automation Science and Engineering, 7(4, SI), 879-886. https://doi.org/10.1109/tase.2010.2049840
• Remagnino, P., Monekosso, D. N., Kuno, Y., Trivedi, M. M., & Eng, H. (2009). Introducing Automation and Engineering for Ambient Intelligence. IEEE Transactions on Automation Science and Engineering, 6(4), 573-576. https://doi.org/10.1109/tase.2009.2022976
• Mullen, R., Monekosso, D., Barman, S., & Remagnino, P. (2009). A review of ant algorithms. Expert Systems with Applications, 36(6), 9608-9617. https://doi.org/10.1016/j.eswa.2009.01.020
• Owen, C. G., Rudnicka, A. R., Mullen, R., Barman, S. A., Monekosso, D., Whincup, P. H., …Paterson, C. (2009). Measuring Retinal Vessel Tortuosity in 10-Year-Old Children: Validation of the Computer-Assisted Image Analysis of the Retina (CAIAR) Program. Investigative Ophthalmology & Visual Science, 50(5), 2004-2010. https://doi.org/10.1167/iovs.08-3018
• Zhan, B., Monekosso, D. N., Remagnino, P., Velastin, S. A., & Xu, L. (2008). Crowd analysis: a survey. Machine Vision and Applications, 19(5-6), 345-357. https://doi.org/10.1007/s00138-008-0132-4