Dr Javier Andreu-Perez
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Email
j.andreu-perez@essex.ac.uk -
Location
5B.542, Colchester Campus
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Academic support hours
2.30-3.30pm Thursday (4285295445)
Profile
Biography
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.
Qualifications
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PhD In Intelligent Systems Lancaster University,
Appointments
University of Essex
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Senior Lecturer, School of Computer Science and Electronic Engineering, University of Essex (1/10/2019 - present)
Other academic
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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
Reasoning and Modeling Systems in Diagnosis and Prognosis
Health Informatics
Computational Intelligence applied to Brain Sciences
Neuroergonomics and Neuromarketing
Computer Vision and Machine Perception
Industrial Informatics
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
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Introduction to Databases (CE153)
Previous supervision
Degree subject: Economics
Degree type: Doctor of Philosophy
Awarded date: 11/10/2022
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 6/7/2022
Publications
Publications (2)
Kiani, M., Andreu-Perez, J. and Hagras, H., (2022). A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence
Filippetti, ML., Andreu-Perez, J., Klerk, CD., Richmond, C. and Rigato, S., (2022). 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
Journal articles (35)
Fumanal-Idocin, J., Vidaurre, C., Fernández, J., Gómez, M., Andreu-Perez, J., Prashad, M. and Bustince, H., Supervised Penalty-based Aggregation Applied to Motor-Imagery based Brain-Computer-Interface. Pattern Recognition
Filippetti, ML., Andreu-Perez, J., De Klerk, C. and Rigato, S., (2023). 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. 265, 119756-119756
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
Ding, W., Feng, Z., Andreu-Perez, J. and Pedrycz, W., (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, PK. and Andreu-Perez, J., (2022). Enhanced Type-2 Wang-Mendel Approach. Journal of Experimental and Theoretical Artificial Intelligence, 1-26
Kiani, M., Andreu-Perez, J. and Hagras, H., (2022). A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence. IEEE Transactions on Artificial Intelligence, 1-15
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
Gupta, A., Kumar, D., Verma, H., Tanveer, M., Andreu-Perez, J., Lin, C-T. and Prasad, M., (2022). Recognition of multi-cognitive tasks from EEG signals using EMD methods. Neural Computing and Applications
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
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 (36)
Miranda, JA., Montoro, AP., Lopez-Ongil, C. and Andreu-Perez, J., (2022). Towards Interval Type-2 Fuzzy-Based PPG Quality Assessment for Physiological Monitoring
Reddy, TK., Wang, Y-K., Lin, C-T. and Andreu-Perez, J., (2021). JOINT APPROXIMATE DIAGONALIZATION DIVERGENCE BASED SCHEME FOR EEG DROWSINESS DETECTION BRAIN COMPUTER INTERFACES
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
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
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 (3)
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
Andreu-Perez, J., Deligianni, F., Ravi, D. and Yang, G-Z., (2018). 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
Grants and funding
2022
Augmented Engagement in Sustainable Cooperative Music Production
University of Essex (ESRC IAA)
Bartech Marine Engineering Ltd (Lapline) KTP Application (June 2022 submission)
Innovate UK (formerly Technology Strategy Board)
Contact
Academic support hours:
2.30-3.30pm Thursday (4285295445)
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