Dr Javier Andreu-Perez

Senior Lecturer
School of Computer Science and Electronic Engineering (CSEE)
Dr Javier Andreu-Perez



Dr Andreu-Perez is a Malaga-born British computer scientist. He is currently Senior Lecturer (tenured) at the University of Essex in Human-Centred Artificial Intelligence for Non-invasive Health at the Centre for Computational Intelligence. He chairs the Smart Health Technologies Group at the centre. He holds a Ph.D. (2012) in Intelligent Systems from Lancaster University (Bowland College), United Kingdom. Javier is also a Senior Talentia Fellow at the Simbad2 group at the University of Jaen (Jaen, Spain) and a Fellow of the Japan Society for the Promotion of Science (JSPS) at ATR (Kyoto, Japan). Prior to joining UoE, Javier held research staff positions at Imperial College London and Lancaster University. He has also been visiting academic fellow of the Faculty of Health (St Mary's Hospital) at Imperial College London. He has contributed to a number of research projects funded by the EU, NHS, the UK’s Ministry of Defence (MoD), as well as the industry. Javier's fundamental science research is actively supported by UK Governmental agencies, foundations, trust and charities. He is a Senior Member of the IEEE Society in Computational Intelligence, has co-edited special issues in the area and published highly cited papers in top journals and conferences in the area of artificial intelligence, health informatics. His research work has been licensed by UK FTSE companies such as GlaxoSmithKline plc. Javier has been awarded prestigious fellowships from the Japan Society for the Promotion of Science, and the Andalucian Knowlege Agency. Furthermore, he actively participates in knowledge transfer programs with SMEs to help UK companies to innovate. These companies are from a wide range of domains such as vehicle engineering, robotics, IoT, health and big data analytics. Beyond the financial benefits, Javier also contributes to the analysis and discussion of Responsible AI frameworks for intelligent systems that can collaborate with humans in a meaningful and safe way. Javier serves as an editorial board member of prestigious journals in artificial intelligence (AI), and he acts as associate Editor-in-Chief for the journal Neurocomputing (Elsevier). He regularly chairs special sessions at renowned world conferences (IEEE-FUZZ and WCCI). He is currently leading an International scientific IEEE Task Force on uncertainty models for computing with words. He actively participates in public engagement activities such as open days, showcases, and professional gatherings from other disciplines. His main research focus is fundamental research questions of artificial intelligence, machine learning, and their applications in engineering, bioengineering, health informatics, human-robot interaction, computer vision, smart sensing & industrial informatics. Favourite quote: “Everything is theoretically impossible, until it is done.” – Robert A. Heinlein.


  • PhD In Intelligent Systems Lancaster University,


University of Essex

  • Senior Lecturer, School of Computer Science and Electronic Engineering, University of Essex (1/10/2019 - present)

Other academic

  • Research scientist, Department of Computing, Imperial College London (1/12/2012 - 1/12/2017)

Research and professional activities

Research interests

Artificial Intelligence and Machine learning

Key words: Artificial Intelligence

Reasoning and Modeling Systems in Diagnosis and Prognosis

Key words: Artificial Intelligence

Health Informatics

Key words: Health informatics

Computational Intelligence applied to Brain Sciences

Key words: Computational Intelligence

Neuroergonomics and Neuromarketing

Key words: Artificial Intelligence

Computer Vision and Machine Perception

Industrial Informatics

Open to supervise

Deep Learning Architectures

Conferences and presentations

Competition Chair for Clinical BCI Challenge

Invited presentation, IEEE World Congress on Computational Intelligence (WCCI), 19/7/2020

Chair Special Session of Fuzzy Systems for Brain Sciences and Brain-Computer Interfaces (BCI) under uncertainty

Invited presentation, IEEE World Congres on Computational Intelligence 2020, 19/1/2020

Keynote on Developing fine-grained actigraphy’s for rheumatoid arthritis patient

Keynote presentation, 1st Digital Rheumatoid Arthritis, Lausanne, Switzerland, 1/2/2019

Teaching and supervision

Current teaching responsibilities

  • Introduction to Databases (CE153)

Previous supervision

Mehrin Kiani
Mehrin Kiani
Thesis title: Explainable Artificial Intelligence for Functional Brain Development Analysis: Methods and Applications.
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 6/7/2022


Journal articles (35)

Filippetti, ML., Andreu, J., Rigato, S. and De Klerk, C., Investigating the effects of stimulus presentation design on infant fNIRS data using a general linear model (GLM) and multivariate pattern analysis (MVPA) based approach. NeuroImage

Filippetti, ML., Andreu, J., De Klerk, C. and Rigato, S., Are advanced methods necessary to improve infant fNIRS data analysis? An assessment of baseline-corrected averaging, general linear model (GLM) and multivariate pattern analysis (MVPA) based approaches. NeuroImage

Andreu-Perez, J., Perez-Espinosa, H., Timonet, E., Kiani, M., Manuel I. Girón-Pérez and Benitez, A., A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels

Andreu-Perez, J., Developing Fine-Grained Actigraphies for Rheumatoid Arthritis Patients from a Single Accelerometer Using Machine Learning

Kiani, M., Andreu-Perez, J., Hagras, H., Papageorgiou, EI., Prasad, M. and Lin, C-T., (2022). Effective Brain Connectivity for fNIRS with Fuzzy Cognitive Maps in Neuroergonomics. IEEE Transactions on Cognitive and Developmental Systems. 14 (1), 50-63

Andreu-Perez, J., Perez-Espinosa, H., Timonet, E., Kiani, M., Giron-Perez, MI., Benitez-Trinidad, AB., Jarchi, D., Rosales, A., Gkatzoulis, N., Reyes-Galaviz, OF., Torres, A., Alberto Reyes-Garcia, C., Ali, Z. and Rivas, F., (2022). A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels. IEEE Transactions on Services Computing. 15 (3), 1220-1232

Ranjbar, E., Menhaj, MB., Suratgar, AA., Andreu-Perez, J. and Prasad, M., (2022). Modern control design for MEMS tunable capacitors in voltage reference applications: a comparative study. International Journal of Dynamics and Control. 10 (2), 483-510

Vega, CF., Quevedo, J., Escandón, E., Kiani, M., Ding, W. and Andreu-Perez, J., (2022). Fuzzy Temporal Convolutional Neural Networks in P300-based Brain-Computer Interface for Smart Home Interaction. Applied Soft Computing. 117, 108359-108359

Andreu-Perez, J., Hagras, H., Kiani, M., Rigato, S. and Filippetti, ML., (2022). Towards Understanding Human Functional Brain Development with Explainable Artificial Intelligence: Challenges and Perspectives. IEEE Computational Intelligence Magazine. 17 (1), 16-33

Salami, A., Andreu-Perez, J. and Gillmeister, H., (2022). EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery Classification. IEEE Access. 10, 36672-36685

Andreu-Perez, J., (2022). Derived Multi-population Genetic Algorithm for Adaptive Fuzzy C-Means Clustering. Neural Processing Letters

K. Gupta, P. and Andreu-Perez, J., (2022). A Gentle Introduction and Survey on Computing with Words (CWW) Methodologies. Neurocomputing. 500, 921-937

Gupta, A., Agrawal, RK., Kirar, JS., Andreu-Perez, J., Ding, W-P., Lin, C-T. and Prasad, M., (2021). On the Utility of Power Spectral Techniques With Feature Selection Techniques for Effective Mental Task Classification in Noninvasive BCI. IEEE Transactions on Systems Man and Cybernetics: Systems. 51 (5), 3080-3092

Andreu-Perez, J. and Kiani, M., (2021). Single-Trial Recognition of Video Gamer’s Expertise from Brain Haemodynamic and Facial Emotion Responses. Brain Sciences. 11 (1), 106-106

Ranjbar, E., Menhaj, MB., Suratgar, AA., Andreu-Perez, J. and Prasad, M., (2021). Design of a fuzzy PID controller for a MEMS tunable capacitor for noise reduction in a voltage reference source. SN Applied Sciences. 3 (6)

Gupta, PK., Sharma, D. and Andreu-Perez, J., (2021). Enhanced Linguistic Computational Models and Their similarity with Yager’s Computing with Words. Information Sciences. 574, 259-278

Andreu-Perez, J., Emberson, LL., Kiani, M., Filippetti, ML., Hagras, H. and Rigato, S., (2021). Explainable Artificial Intelligence Based Analysis for Developmental Cognitive Neuroscience. Communications Biology. 4 (1), 1077-

Perez-Espinosa, H., Timonet-Andreu, E. and Andreu-Perez, J., (2021). Bias and privacy in AI's cough-based COVID-19 recognition. The Lancet Digital Health. 3 (12), e760-e760

Chowdhury, A. and Andreu-Perez, J., (2021). Clinical Brain-Computer Interface Challenge 2020 (CBCIC at WCCI2020): Overview, methods and results. IEEE Transactions on Medical Robotics and Bionics. 3 (3), 661-670

del Angel Arrieta, F., Rojas Cisneros, M., Rivas, JJ., Castrejon, LR., Sucar, LE., Andreu-Perez, J. and Orihuela-Espina, F., (2021). Characterization of a Raspberry Pi as the Core for a Low-cost Multimodal EEG-fNIRS Platform. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021, 1288-1291

Akshansh, G., R. K., A., Jyoti Singh, K., Baljeet, K., Weiping, D., Chin-Teng, L., Andreu-Perez, J. and Mukesh, P., (2020). A Hierarchical Meta-model for Multi-Class Mental Task Based Brain-Computer Interfaces. Neurocomputing. 389, 207-217

Andreu-Perez, J., (2020). Fuzzy learning and its applications in neural-engineering. Neurocomputing. 389, 196-197

Jarchi, D., Andreu-Perez, J., Kiani, M., Vysata, O., Kuchynka, J., Prochazka, A. and Sanei, S., (2020). Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning. Sensors. 20 (9), 2594-2594

Salami, A., Andreu-Perez, J. and Gillmeister, H., (2020). Symptoms of depersonalisation/derealisation disorder as measured by brain electrical activity: A systematic review. Neuroscience and Biobehavioral Reviews. 118, 524-537

Andreu-Perez, J., Cao, F., Hagras, H. and Yang, G., (2018). A Self-Adaptive Online Brain Machine Interface of a Humanoid Robot through a General Type-2 Fuzzy Inference System. IEEE Transactions on Fuzzy Systems. 26 (1), 101-116

Ravi, D., Wong, C., Deligianni, F., Berthelot, M., Andreu-Perez, J., Lo, B. and Yang, G-Z., (2017). Deep Learning for Health Informatics. IEEE Journal of Biomedical and Health Informatics. 21 (1), 4-21

Andreu-Perez, J., Garcia-Gancedo, L., McKinnell, J., Van der Drift, A., Powell, A., Hamy, V., Keller, T. and Yang, G-Z., (2017). Developing Fine-Grained Actigraphies for Rheumatoid Arthritis Patients from a Single Accelerometer Using Machine Learning. Sensors. 17 (9), 2113-2113

Andreu-Perez, J., Leff, DR., Shetty, K., Darzi, A. and Yang, G-Z., (2016). Disparity in Frontal Lobe Connectivity on a Complex Bimanual Motor Task Aids in Classification of Operator Skill Level. Brain Connectivity. 6 (5), 375-388

Andreu-Perez, J., Solnais, C. and Sriskandarajah, K., (2016). EALab (Eye Activity Lab): a MATLAB Toolbox for Variable Extraction, Multivariate Analysis and Classification of Eye-Movement Data. Neuroinformatics. 14 (1), 51-67

Andreu-Perez, J., Leff, DR., Ip, HMD. and Yang, G-Z., (2015). From Wearable Sensors to Smart Implants-–Toward Pervasive and Personalized Healthcare. IEEE Transactions on Biomedical Engineering. 62 (12), 2750-2762

Andreu-Perez, J., Poon, CCY., Merrifield, RD., Wong, STC. and Yang, G-Z., (2015). Big Data for Health. IEEE Journal of Biomedical and Health Informatics. 19 (4), 1193-1208

Solnais, C., Andreu-Perez, J., Sánchez-Fernández, J. and Andréu-Abela, J., (2013). The contribution of neuroscience to consumer research: A conceptual framework and empirical review. Journal of Economic Psychology. 36, 68-81

Andreu, J. and Angelov, P., (2013). An evolving machine learning method for human activity recognition systems. Journal of Ambient Intelligence and Humanized Computing. 4 (2), 195-206

Sadeghi-Tehran, P., Andreu, J., Angelov, P. and Zhou, X., (2011). Intelligent leader-follower behaviour for unmanned ground-based vehicles. Journal of Automation Mobile Robotics and Intelligent Systems. 5, 36-46

Andréu, J. and Holgado, JA., (2004). Wireless Sensor Networks applied to Ambient Assisted-Living Environments

Book chapters (2)

Yang, G., Andreu-Perez, J., Hu, X. and Thiemjarus, S., (2014). Multi-sensor fusion. In: Body sensor networks. Springer. 301- 354. 9781447163732

Andréu, J. and Holgado, JA., (2008). Ambient Assisted-Living Platforms: The Real Issue, Challenges and Technologies

Conferences (34)


Sharma, D., Gupta, PK., Andreu-Perez, J., Mendel, JM. and Lopez, LM., (2021). A Python Software Library for Computing with Words and Perceptions

Rozman, J., Hagras, H., Andreu-Perez, J., Clarke, D., Muller, B. and Fitz, S., (2021). A Type-2 Fuzzy Logic Based Explainable AI Approach for the Easy Calibration of AI models in IoT Environments

Cortez, S., Flores, C. and Andreu-Perez, J., (2020). Improving Speller BCI performance using a cluster-based under-sampling method

Salami, A., Andreu-Perez, J. and Gillmeister, H., (2020). Towards Decoding of Depersonalisation Disorder Using EEG: A Time Series Analysis Using CDTW

Malik, A., de Frein, R., Al-Zeyadi, M. and Andreu-Perez, J., (2020). Intelligent SDN Traffic Classification Using Deep Learning: Deep-SDN

Cortez, SA., Flores Vega, C. and Andreu-Perez, J., (2020). Under-sampling and Classification of P300 Single-Trials using Self-Organized Maps and Deep Neural Networks for a Speller BCI

Cortez, SA., Flores, C. and Andreu-Perez, J., (2020). Single-trial P300 classification using deep belief networks for a BCI system

Kiani, M., Andreu-Perez, J., Hagras, H., Filippetti, ML. and Rigato, S., (2020). A Type-2 Fuzzy Logic Based Explainable Artificial Intelligence System for Developmental Neuroscience

Al-Zeyadi, M., Andreu-Perez, J., Hagras, H., Royce, C., Smith, D., Rzonsowski, P. and Malik, A., (2020). Deep Learning Towards Intelligent Vehicle Fault Diagnosis

Rozman, J., Hagras, H., Andreu-Perez, J., Clarke, D., Muller, B. and Data, SF., (2020). Privacy-Preserving Gesture Recognition with Explainable Type-2 Fuzzy Logic Based Systems

Cortez, SA., Flores, C. and Andreu-Perez, J., (2020). A Smart Home Control Prototype Using a P300-Based Brain–Computer Interface for Post-stroke Patients

Kiani, M., Andreu-Perez, J., Hagras, H., Andreu, AR., Pinto, M., Andreu, J., Reddy, P. and Izzetoglu, K., (2019). Towards Gamers’ Experience Level Decoding with Optical Brain Imaging

Achanccaray, D., Mylonas, G. and Andreu-Perez, J., (2019). An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy

Achanccaray, D., Flores, C., Fonseca, C. and Andreu-Perez, J., (2018). A Fuzzy Genetic Algorithm for Optimal Spatial Filter Selection for P300-Based Brain Computer Interfaces

Flores, C., Fonseca, C., Achanccaray, D. and Andreu-Perez, J., (2018). Performance Evaluation of a P300 Brain-Computer Interface Using a Kernel Extreme Learning Machine Classifier

Flores, C., Flores, V., Achanccaray, D. and Andreu-Perez, J., (2018). A Convolutional Neural Network Approach for a P300-based Brain-Computer Interface for Disabled and Healthy Subjects

Achanccaray, D., Flores, C., Fonseca, C. and Andreu-Perez, J., (2017). A P300-based brain computer interface for smart home interaction through an ANFIS ensemble

Kiani, M., Andreu-Perez, J. and Papageorgiou, EI., (2017). Improved estimation of effective brain connectivity in functional neuroimaging through higher order fuzzy cognitive maps

Achanccaray, D., Acuna, K., Carranza, E. and Andreu-Perez, J., (2017). A virtual reality and brain computer interface system for upper limb rehabilitation of post stroke patients

Pacheco, K., Acuna, K., Carranza, E., Achanccaray, D. and Andreu-Perez, J., (2017). Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation

Kiani, M., Andreu-Perez, J., Leff, DR., Darzi, A. and Yang, GZ., (2014). Shedding Light on Surgeons' Cognitive Resilience: A Novel Method of Topological Analysis for Brain Networks

Angelov, P., Andreu, J. and Vuong, T., (2012). Automatic mobile photographer and picture diary

Sadeghi-Tehran, P., Behera, S., Angelov, P. and Andreu, J., (2012). Autonomous visual self-localization in completely unknown environment

Andreu, J., Baruah, RD. and Angelov, P., (2011). Real time recognition of human activities from wearable sensors by evolving classifiers

Andreu, J., Baruah, RD. and Angelov, P., (2011). Automatic scene recognition for low-resource devices using evolving classifiers

Baruah, RD., Angelov, P. and Andreu, J., (2011). Simpl_eClass: simplified potential-free evolving fuzzy rule-based classifiers

Baruah, RD., Angelov, P., Andreu, J. and IEEE, (2011). Simpl_eClass: Simplified Potential-free Evolving Fuzzy Rule-Based Classifiers

Andreu, J. and Angelov, P., (2010). Real-time human activity recognition from wireless sensors using evolving fuzzy systems

Andreu, J. and Angelov, P., (2010). Forecasting time-series for NN GC1 using Evolving Takagi-Sugeno (eTS) Fuzzy Systems with on-line inputs selection

Andréu, J., Viúdez, J. and Holgado, JA., (2009). An ambient assisted-living architecture based on wireless sensor networks

Pérez, JA., Álvarez, JA., Fernández-Montes, A. and Ortega, JA., (2009). Service-oriented device integration for ubiquitous ambient assisted living environments

Andréu, J., Viudez, J. and Holgado, J., (2008). A Survey of Wireless Sensor Networks

Viúdez, J., Andréu, J. and Holgado, JA., (2008). An OSGi Experience for Home Automation Applications

Reports and Papers (1)

Andreu-Perez, J., Deligianni, F., Ravi, D. and Yang, G-Z., Artificial Intelligence and Robotics

Other (1)

Andreu, J. and Angelov, P., (2013).Towards generic human activity recognition for ubiquitous applications. Journal of Ambient Intelligence and Humanized Computing. 4(2),Springer



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2.30-3.30pm Thursday (4285295445)

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