Email
j.andreu-perez@essex.ac.ukLocation
5B.542, Colchester Campus
Academic support hours
11.30am-1.30pm Wednesday (4285295445)
Biography
Dr Andreu-Perez, Reader (Associate Professor) in Human-Centred Artificial Intelligence is a British computer scientist (born in Malaga, Spain). He also chairs the Smart Health Technologies Group at the Centre for Computational Intelligence. He holds a PhD (2012) in Intelligent Systems from Lancaster University (Bowland College), United Kingdom. Javier was also awarded a Senior Talentia Fellow and an Invitational Fellowship of Japan's Society for the Promotion of Science. Before joining the University of Essex, Javier held research staff positions at Imperial College London and Lancaster University. He has also been a 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, trusts 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 and health informatics. His research work has been licensed by UK FTSE companies such as GlaxoSmithKline plc. Furthermore, he actively participates in knowledge transfer programs with SMEs to help UK companies to innovate. These companies are from various domains, such as robotics, intelligent systems and machines, 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
PhD In Intelligent Systems (Artificial Intelligence) Lancaster University,
Appointments
University of Essex
Reader, School of Computer Science and Electronic Engineeringg, University of Essex (1/3/2025 - present)
Senior Lecturer, School of Computer Science and Electronic Engineering, University of Essex (1/10/2019 - present)
Lecturer, School of Computer Science and Electronic Engineering, University of Essex (1/9/2017 - 1/10/2019)
Other academic
Research scientist, Department of Computing, Imperial College London (1/12/2012 - 1/12/2017)
Research interests
Online and Adaptive Methods for AI and ML
Health Informatics
Computational Intelligence applied to Brain Sciences
Computer Vision and Machine Perception
Deep and Transfer Learning
Reasoning and Modeling Systems in Diagnosis and Prognosis
Natural-language understanding
Generative AI
Soft Computing
Human Machine Interaction
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
Current teaching responsibilities
Introduction to Data Science (CE207)
Previous supervision
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 4/7/2023
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 (9)
Balsamo, D., Offeddu, V., Aghamohammadi, Z., Chiavenna, C., Leone, LP., D’Agnese, E., Sharma, D., Torbica, A., Shayegh, S., Andreu-Perez, J. and Melegaro, A., (2025). Public sentiment towards vaccination: characterizing global patterns and drivers of scientific research
Ramos-Cruz, B., Andréu-Pérez, J., Quesada, FJ. and Martínez, L., (2024). Fuzzychain: An Equitable Consensus Mechanism for Blockchain Networks.
Jamalifard, M., Andreu-Perez, J., Hagras, H. and López, LM., (2024). Fuzzy Norm-Explicit Product Quantization for Recommender Systems
Flores, C., Contreras, M., Macedo, I. and Andreu-Perez, J., (2024). Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data
Miranda, JA., López-Ongil, C. and Andreu-Perez, J., (2023). Personalised and Adjustable Interval Type-2 Fuzzy-Based PPG Quality Assessment for the Edge
Córdova, JC., Flores, C. and Andreu-Perez, J., (2023). EMGTFNet: Fuzzy Vision Transformer to decode Upperlimb sEMG signals for Hand Gestures Recognition
Fumanal-Idocin, J., Andreu-Perez, J., Cordón, O., Hagras, H. and Bustince, H., (2023). ARTxAI: Explainable Artificial Intelligence Curates Deep Representation Learning for Artistic Images using Fuzzy Techniques
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 (49)
Urio-Larrea, A., ANDREU-PEREZ, J. and Pereira Dimuro, G., (2025). Data stream clustering: introducing recursively extendable aggregation functions for incremental cluster fusion processes. IEEE Transactions on Cybernetics. 55 (3), 1421-1435
Gutiérrez-Serafín, B., Andreu-Perez, J., Pérez-Espinosa, H., Paulmann, S. and Ding, W., (2024). Toward assessment of human voice biomarkers of brain lesions through explainable deep learning. Biomedical Signal Processing and Control. 87B, 105457-105457
Salami, A., Andreu-Perez, J. and Gillmeister, H., (2024). Finding neural correlates of depersonalisation/derealisation disorder via explainable CNN-based analysis guided by clinical assessment scores. Artificial Intelligence in Medicine. 149, 102755-102755
Jamalifard, M., Andreu-Perez, J., Hagras, H. and Martinez, L., (2024). Fuzzy Norm-Explicit Product Quantization for Recommender Systems. IEEE Transactions on Fuzzy Systems. 32 (5), 2987-2998
Fumanal-Idocin, J., Vidaurre, C., Fernández, J., Gómez, M., Andreu-Perez, J., Prashad, M. and Bustince, H., (2024). Supervised Penalty-based Aggregation Applied to Motor-Imagery based Brain-Computer-Interface. Pattern Recognition. 145, 109924-109924
Flores, C., Contreras, M., Macedo, I. and Andreu-Perez, J., (2024). Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32, 3794-3803
Fumanal-Idocin, J. and Andreu-Perez, J., (2024). Ex-Fuzzy: A library for symbolic explainable AI through fuzzy logic programming. Neurocomputing. 599, 128048-128048
Ramos-Cruz, B., Andreu-Perez, J. and Martínez, L., (2024). The cybersecurity mesh: A comprehensive survey of involved artificial intelligence methods, cryptographic protocols and challenges for future research. Neurocomputing. 581, 127427-127427
Fumanal-Idocin, J., Andreu-Perez, J., Cordón, O., Hagras, H. and Bustince, H., (2024). ARTxAI: Explainable Artificial Intelligence Curates Deep Representation Learning for Artistic Images using Fuzzy Techniques.. IEEE Transactions on Fuzzy Systems. 32 (4), 1915-1926
Jamalifard, M., Andreu-Perez, J., Hagras, H. and Martínez-López, L., (2024). Fuzzy Norm-Explicit Product Quantization for Recommender Systems.. CoRR. abs/2412.06069
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. and Hagras, H., (2023). A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence. IEEE Transactions on Artificial Intelligence. 4 (3), 573-586
Tanveer, M., Lin, C-T., Ting, C-K. and Andreu-Perez, J., (2023). Guest Editorial: Special Issue on Emerging Computational Intelligence Techniques to Address Challenges in Biomedical Data and Imaging. IEEE Transactions on Emerging Topics in Computational Intelligence. 7 (2), 292-294
Soheil, S., Andreu-Perez, J., Akoth, C., Bosch-Capblanch, X., Dasgupta, S., Falchetta, G., Gregson, S., Hammad, AT., Herringer, M., Kapkea, F., Labella, A., Lisciotto, L., Martínez, L., Macharia, PM., Morales-Ruiz, P., Murage, N., Offeddu, V., South, A., Torbica, A., Trentini, F. and Alessia, M., (2023). Prioritizing COVID-19 vaccine allocation in resource poor settings: Towards an Artificial Intelligence-enabled and Geospatial-assisted decision support framework. PLoS One. 18 (8), e0275037-e0275037
Chaudhary, L., Girdhar, N., Sharma, D., Andreu-Perez, J., Doucet, A. and Renz, M., (2023). A Review of Deep Learning Models for Twitter Sentiment Analysis: Challenges and Opportunities. IEEE Transactions on Computational Social Systems. 11 (3), 3550-3579
Gupta, PK., Sharma, D. and Andreu-Perez, J., (2023). A Perceptual Computing Approach for Learning Interpretable Unsupervised Fuzzy Scoring Systems. IEEE Transactions on Artificial Intelligence. 5 (8), 3832-3844
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
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
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. 55 (3), 2023-2047
Gupta, PK. and Andreu-Perez, J., (2022). Enhanced Type-2 Wang-Mendel Approach. Journal of Experimental and Theoretical Artificial Intelligence. 36 (7), 1213-1238
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. 35 (31), 22989-23006
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
K. Gupta, P. and Andreu-Perez, J., (2022). A Gentle Introduction and Survey on Computing with Words (CWW) Methodologies. Neurocomputing. 500, 921-937
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
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
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
Andreu-Perez, J., Deligianni, F., Ravì, D. and Yang, G-Z., (2018). Artificial Intelligence and Robotics.. CoRR. abs/1803.10813
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 (3)
Reddy, SD., Goyal, S., Reddy, TK., Vinjamuri, R. and Andreu-Perez, J., (2024). Riemannian deep feature fusion with autoencoder for MEG depression classification in smart healthcare applications. In: Data Fusion Techniques and Applications for Smart Healthcare. Elsevier. 197- 212. 9780443132339
Yang, G., Andreu-Perez, J., Hu, X. and Thiemjarus, S., (2014). Multi-sensor fusion. In: Body sensor networks. Editors: . Springer. 301- 354. 9781447163732
Andréu, J. and Holgado, JA., (2008). Ambient Assisted-Living Platforms: The Real Issue, Challenges and Technologies
Conferences (46)
Achanccaray, D., Andreu-Perez, J. and Sumioka, H., Robot-Avatar Operator Metrics in Receptionist Roles: Performance, Behavior, and Telemetry Associations
Urio-Larrea, A., Dimuro, GP., Andreu-Pérez, J., Camargo, H. and Bustince, H., (2024). Towards Analysing Climate Change Temperature Patterns through Stream Clustering Methods
Fumanal-Idocin, J., Jamalifard, M. and Andreu-Perez, J., (2024). Interpreting Contrastive Embeddings in Specific Domains with Fuzzy Rules
Ramos-Cruz, B., Quesada-Real, FJ., Rodriguez-Garcia, M., Andreu-Pérez, J. and Martínez, L., (2024). Combining Distributed Ledger Technologies and Differentially Private Sketching Techniques for Securing Health Monitoring
Contreras, M., Flores, C. and Andreu-Perez, J., (2024). EEG-TCF2Net: A Novel Deep Interval Type-2 Fuzzy Model for Decoding SSVEP in Brain-Computer Interfaces
Miranda, JA., López-Ongil, C. and Andreu-Perez, J., (2023). Personalised and Adjustable Interval Type-2 Fuzzy-Based PPG Quality Assessment for the Edge
Fumanal-Idocin, J., Bustince, H., Andreu-Perez, J. and Hagras, H., (2023). On the Stability of Fuzzy Classifiers to Noise Induction
Miranda, JA., López-Ongil, C. and Andreu-Perez, J., (2023). Personalised and Adjustable Interval Type-2 Fuzzy-Based PPG Quality Assessment for the Edge.
Córdova, JC., Vega, CF. and Andreu-Perez, J., (2023). EMGTFNet: Fuzzy Vision Transformer to Decode Upperlimb sEMG Signals for Hand Gestures Recognition.
Córdova, JC., Flores, C. and Andreu-Perez, J., (2023). EMGTFNet: Fuzzy Vision Transformer to Decode Upperlimb sEMG Signals for Hand Gestures Recognition
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. and Andreu, J., (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., (2021). 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., (2021). 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
2024
SUGOI: System for Up-skilling in Human-Robot Symbiosis for Global Operator Interaction Training
The Royal Society
Exploring the Use of Neurofeedback for Alleviating Perimenopausal Symptoms
The Royal Society
Sortflow AI Mapper Scoping Project - Innovation Voucher
Sortflow Limited
To develop a novel Explainable AI (XAI) based support system, which will receive different information formats (free text, images, videos and acoustic signals), enabling a seamless experience of the conveyancing process.
Innovate UK (formerly Technology Strategy Board)
EyeWarn: A Large-Scale UK Study of Patterns of Eye Activity in Cognitive Strain
Biotechnology and Biological Sciences Research Council
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)
Gerald McDonald & Company Ltd KTP Project (KTP 22_23 R)
Innovate UK (formerly Technology Strategy Board)
2021
Copy me, copy you: Investigating the development of facial mimicry in infancy
Bial Foundation
2020
Frugal Technology-Assisted Neuro-rehab for Post-stroke Care in Rural Mexico
University of Essex (GCRF)
2019
Breaking Down Barriers for the Benefit of Population Health
University of Essex
2018
Develop a new service for the international solar market, 'SolarGain - High Vision
Innovate UK (formerly Technology Strategy Board)
Plextek KTP Mar 18
Innovate UK (formerly Technology Stategy Board)
Cognitran KTP 03/18
Innovate UK (formerly Technology Strategy Board)
1900
Frugal Technology-Assisted Neuro-rehab for Post-stroke Care in Rural Mexico
University of Essex (GCRF)
Academic support hours:
11.30am-1.30pm Wednesday (4285295445)
