People

Dr Javier Andreu-Perez

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

Profile

Biography

Dr Andreu-Perez is a Malaga-born British computer scientist. He is currently a Senior Lecturer (tenured) at the University of Essex in Human-Centred Artificial Intelligence at the Centre for Computational Intelligence. He chairs the Smart Health Technologies Group at the centre. 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

  • 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 and professional activities

Research interests

Online and Adaptive Methods for AI and ML

Key words: Artificial Intelligence
Open to supervise

Health Informatics

Key words: Artificial intelligence
Open to supervise

Computational Intelligence applied to Brain Sciences

Key words: Computational Intelligence

Computer Vision and Machine Perception

Open to supervise

Deep and Transfer Learning

Open to supervise

Reasoning and Modeling Systems in Diagnosis and Prognosis

Key words: Artificial Intelligence

Natural-language understanding

Open to supervise

Generative AI

Open to supervise

Soft Computing

Open to supervise

Human Machine Interaction

Open to supervise

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 Data Science (CE207)

Previous supervision

Abbas Salami
Abbas Salami
Thesis title: Explainable Deep Learning-Based Eeg Analysis for Biomarker Discovery and its Application on Depersonalisation/Derealisation Disorder
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 4/7/2023
Mariha Tahsin
Mariha Tahsin
Thesis title: Micro and Macro Indexes of Economic Activity: Multiple Indicators and Multiple Methods Using Bangladesh as a Test Case
Degree subject: Economics
Degree type: Doctor of Philosophy
Awarded date: 11/10/2022
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

Publications

Publications (6)

Ramos-Cruz, B., Andréu-Pérez, J., Quesada, FJ. and Martínez, L., (2024). Fuzzychain: An Equitable Consensus Mechanism for Blockchain Networks.

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 (47)

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

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 (44)

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

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

Grants and funding

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)

Contact

j.andreu-perez@essex.ac.uk

Location:

5B.542, Colchester Campus

Academic support hours:

2.30-3.30pm Thursday (4285295445)

More about me
Personal Web Page: http://andreuperez.net/

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