People

Professor Hani Hagras

Professor
School of Computer Science and Electronic Engineering (CSEE)
Professor Hani Hagras
  • Email

  • Telephone

    +44 (0) 1206 873601

  • Location

    5B.524, Colchester Campus

Profile

Biography

My main research interests are in Computational Intelligence (including fuzzy logic systems, neural networks and evolutionary computation). I am particularly interested in Uncertainty management, Risk Analysis and Computational Finance. I am also strongly interested in the area of Internet of Things including Intelligent Environments, ubiquitous computing, pervasive computing, ambient intelligence, intelligent buildings and embedded agents. In addition, I am also strongly interested in the areas of intelligent robotics and the intelligent control of industrial processes. I have published over 300 papers in top International Journals, Books and Conferences. I hold Six Industrial international patents in the field of computational intelligence and its applications to intelligent control, energy management, decision support and data analysis of industrial processes, financial markets and medical applications. I have strong relations with industry and major companies which allows for the dissemination of my research to the commercial and industrial sectors thus resulting in real world products and services with strong impact on the wider society. I maintain a sustained performance in winning external research funding where I was the principal investigator and co-investigator of many projects which received funding from the Innovate UK, European Commission, the UK Department of Trade and Industry (DTI), UK Technology Strategy Board (TSB), UK Engineering and Physical Sciences Research Council (EPSRC), UK Economics and Social Sciences Research Council (ESRC), the Higher Education Funding Council for England (HEFCE), the German Federal Ministry of Education and Research (IB-BMBF), the Taiwan National Science Foundation, Korea-UK Science and Technology fund and many industrial companies . I am Fellow IEEE, Fellow IET and Principal Fellow HEA. I have served as the General and Programme Chair of numerous major international conferences where I was the General co-Chair of the 2007 IEEE International Conference on Fuzzy Systems, London, UK, July 2007 and acted as the Programme Chair of the 2017 IEEE International Conference on Fuzzy Systems, Naples, Italy. I serve as an Associate Editor for the IEEE Transactions on Fuzzy Systems, the International Journal of Robotics and Automation, the Journal of Ambient Computing and Intelligence and the International Journal of Soft Computing. I was also selected to serve on the editorial board of the International Journal of Ambient Intelligence and Smart Environments. I have been invited to deliver keynote speeches in numerous major international conferences.

Qualifications

  • PhD, Computer Science University of Essex (2000)

  • Msc in Electrical Engineering University of Alexandria (1996)

  • Bsc in Electrical Engineering University of Alexandria (1994)

Appointments

University of Essex

  • Director of Research, School of Computer Science and Electronic Engineering University of Essex ( 1/7/2017 - present )

  • Director of the Computational Intelligence Centre, School of Computer Science and Electronic Engineering University of Essex ( 10/9/2007 - present )

  • Head of the Fuzzy Systems Research Lab, School of Computer Science and Electronic Engineering University of Essex ( 1/9/2007 - present )

  • Director Impact, School of Computer Science and Electronic Engineering University of Essex ( 1/10/2015 - 1/7/2017 )

  • Senior Lecturer (Associate Professor), Department of Computer Science University of Essex ( 1/8/2003 - 1/6/2006 )

  • Lecturer (Assistant Professor), Department of Computer Science University of Essex ( 1/1/2001 - 1/8/2003 )

  • Head of the Intelligent Environments Research Lab, School of Computer Science and Electronic Engineering University of Essex ( 2/10/2012 - present )

Other academic

  • Lecturer (Assistant Professor), Department of Computer Science University of Hull ( 1/3/2000 - 1/1/2001 )

Research and professional activities

Research interests

Computational Intelligence (Fuzzy Logic,Neural Networks and Evolutionary Computation )

Current research

Internet of Things

Robotics and Intelligent Control

Teaching and supervision

  • Intelligent Systems and Robotics (CE801)

  • Neural Networks and Deep Learning (CE889)

Publications

Journals (86)

Pena Rios, AC., Hagras, H., Owusu, G. and Gardner, M., (2018). Furthering Service 4.0: Harnessing Intelligent Immersive Environments and Systems. IEEE Systems, Man, and Cybernetics Magazine. 4 (1)

Antonelli, M., Bernardo, D., Hagras, H. and Marcelloni, F., (2017). Multiobjective Evolutionary Optimization of Type-2 Fuzzy Rule-Based Systems for Financial Data Classification. IEEE Transactions on Fuzzy Systems. 25 (2)

Ruiz-García, G., Hagras, H., Rojas, I. and Pomares, H., (2017). Towards a framework for singleton general forms of interval type-2 fuzzy systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10147 LNAI

Colchester, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2017). A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms. Journal of Artificial Intelligence and Soft Computing Research. 7 (1)

Almohammadi, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2017). A zSlices-based general type-2 fuzzy logic system for users-centric adaptive learning in large-scale e-learning platforms. Soft Computing. 21 (22)

Almohammadi, K., Hagras, H., Yao, B., Alzahrani, A., Alghazzawi, D. and Aldabbagh, G., (2017). A type-2 fuzzy logic recommendation system for adaptive teaching. Soft Computing. 21 (4)

Sarabakha, A., Imanberdiyev, N., Kayacan, E., Khanesar, MA. and Hagras, H., (2017). Novel Levenberg–Marquardt based learning algorithm for unmanned aerial vehicles. Information Sciences. 417

Nadeem, F., Alghazzawi, D., Mashat, A., Fakeeh, K., Almalaise, A. and Hagras, H., (2017). Modeling and predicting execution time of scientific workflows in the Grid using radial basis function neural network. Cluster Computing. 20 (3)

Almohammadi, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2016). Users-Centric Adaptive Learning System Based on Interval Type-2 Fuzzy Logic for Massively Crowded E-Learning Platforms. Journal of Artificial Intelligence and Soft Computing Research. 6 (2)

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2016). A Big Bang–Big Crunch Type-2 Fuzzy Logic System for Machine-Vision-Based Event Detection and Summarization in Real-World Ambient-Assisted Living. IEEE Transactions on Fuzzy Systems. 24 (6)

Wei, S., Hagras, H. and Alghazzawi, D., (2016). A cloud computing based Big-Bang Big-Crunch fuzzy logic multi classifier system for Soccer video scenes classification. Memetic Computing. 8 (4)

Starkey, A., Hagras, H., Shakya, S., Owusu, G., Mohamed, A. and Alghazzawi, D., (2016). A cloud computing based many objective type-2 fuzzy logic system for mobile field workforce area optimization. Memetic Computing. 8 (4)

Ruiz, G., Hagras, H., Pomares, H., Rojas, I. and Bustince, H., (2016). Join and Meet Operations for Type-2 Fuzzy Sets With Nonconvex Secondary Memberships. IEEE Transactions on Fuzzy Systems. 24 (4)

Bilgin, A., Hagras, H., van Helvert, J. and Alghazzawi, D., (2016). A Linear General Type-2 Fuzzy Logic Based Computing With Words Approach for Realising an Ambient Intelligent Platform for Cooking Recipes Recommendation. IEEE Transactions on Fuzzy Systems. 24 (2)

Bustince, H., Barrenechea, E., Pagola, M., Fernandez, J., Xu, Z., Bedregal, B., Montero, J., Hagras, H., Herrera, F. and De Baets, B., (2016). A Historical Account of Types of Fuzzy Sets and Their Relationships. IEEE Transactions on Fuzzy Systems. 24 (1)

Mendel, JM., Hagras, H., Bustince, H. and Herrera, F., (2016). Comments on: Interval Type-2 Fuzzy Sets are generalization of Interval-Valued Fuzzy Sets: Towards a Wider view on their relationship. IEEE Transactions on Fuzzy Systems. 24 (1)

Acampora, G., Alghazzawi, D., Hagras, H. and Vitiello, A., (2016). An interval type-2 fuzzy logic based framework for reputation management in Peer-to-Peer e-commerce. Information Sciences. 333

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2016). A multi-objective genetic type-2 fuzzy logic based system for mobile field workforce area optimization. Information Sciences. 329

Andreu-Perez, J., Cao, F., Hagras, H. and Yang, G., (2016). 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)

De Miguel, L., Santos, H., Sesma-Sara, M., Bedregal, B., Jurio, A., Bustince, H. and Hagras, H., (2016). Type-2 Fuzzy Entropy-Sets. IEEE Transactions on Fuzzy Systems. 25 (4)

Bilgin, A., Hagras, H., Ghelli, A., Alghazzawi, D. and Aldabbagh, G., (2015). An Ambient Intelligent and Energy Efficient Food Preparation System Using Linear General Type-2 Fuzzy Logic Based Computing with Words Framework [Application Notes]. IEEE Computational Intelligence Magazine. 10 (4)

Ghelli, A., Hagras, H. and Aldabbagh, G., (2015). A Fuzzy Logic Based Retrofit System for Enabling Smart Energy Efficient Electric Cookers. IEEE Transactions on Fuzzy Systems. 23 (6)

Sola, HB., Fernandez, J., Hagras, H., Herrera, F., Pagola, M. and Barrenechea, E., (2015). Interval Type-2 Fuzzy Sets are Generalization of Interval-Valued Fuzzy Sets: Toward a Wider View on Their Relationship. IEEE Transactions on Fuzzy Systems. 23 (5)

Sanz, JA., Bernardo, D., Herrera, F., Bustince, H. and Hagras, H., (2015). A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications With Imbalanced Data. IEEE Transactions on Fuzzy Systems. 23 (4)

Kumbasar, T. and Hagras, H., (2015). A Self-Tuning zSlices-Based General Type-2 Fuzzy PI Controller. IEEE Transactions on Fuzzy Systems. 23 (4)

Alhaddad, MJ., Mohammed, A., Kamel, M. and Hagras, H., (2015). A genetic interval type-2 fuzzy logic-based approach for generating interpretable linguistic models for the brain P300 phenomena recorded via brain–computer interfaces. Soft Computing. 19 (4)

Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2015). Employing Type-2 Fuzzy Logic Systems in the Efforts to Realize Ambient Intelligent Environments [Application Notes]. IEEE Computational Intelligence Magazine. 10 (1)

Yao, B., Hagras, H., Alhaddad, MJ. and Alghazzawi, D., (2015). A fuzzy logic-based system for the automation of human behavior recognition using machine vision in intelligent environments. Soft Computing. 19 (2)

Kumbasar, T. and Hagras, H., (2014). Big Bang–Big Crunch optimization based interval type-2 fuzzy PID cascade controller design strategy. Information Sciences. 282

Naim, S. and Hagras, H., (2014). A type 2-hesitation fuzzy logic based multi-criteria group decision making system for intelligent shared environments. Soft Computing. 18 (7)

Sahab, N. and Hagras, H., (2014). Adaptive Non-singleton Type-2 Fuzzy Logic Systems: A Way Forward for Handling Numerical Uncertainties in Real World Applications. International Journal of Computers Communications & Control. 6 (3)

Dooley, J., Hagras, H., Callaghan, V. and Henson, M., (2013). The tailored fabric of Intelligent Environments. Studies in Computational Intelligence. 460

Bernardo, D., Hagras, H. and Tsang, E., (2013). A genetic type-2 fuzzy logic based system for the generation of summarised linguistic predictive models for financial applications. Soft Computing. 17 (12)

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2013). Towards a linear general type-2 fuzzy logic based approach for computing with words. Soft Computing. 17 (12)

Lee, CS., Wang, MH., Su, MK., Wu, MH. and Hagras, H., (2013). A Type-2 FML-based meeting scheduling support system. Studies in Fuzziness and Soft Computing. 296

Huang, HD., Acampora, G., Loia, V., Lee, CS., Hagras, H., Wang, MH., Kao, HY. and Chang, JG., (2013). Fuzzy markup language for malware behavioral analysis. Studies in Fuzziness and Soft Computing. 296

Wang, MH., Lee, CS., Hagras, H., Su, MK., Tseng, YY., Wang, HM., Wang, YL. and Liu, CH., (2013). Applying FML-based fuzzy ontology to university assessment. Studies in Fuzziness and Soft Computing. 296

Wang, MH., Lee, CS., Chen, ZW., Hagras, H., Kuo, SE., Kuo, HC. and Cheng, HH., (2013). A Type-2 FML-based fuzzy ontology for dietary assessment. Studies in Fuzziness and Soft Computing. 296

Garcia-Valverde, T., Garcia-Sola, A., Hagras, H., Dooley, JA., Callaghan, V. and Botia, JA., (2013). A Fuzzy Logic-Based System for Indoor Localization Using WiFi in Ambient Intelligent Environments. IEEE Transactions on Fuzzy Systems. 21 (4)

Mendel, JM., Hagras, H. and John, RI., (2013). Guest Editorial for the special issue on type-2 fuzzy sets and systems. IEEE Transactions on Fuzzy Systems. 21 (3)

Cara, AB., Wagner, C., Hagras, H., Pomares, H. and Rojas, I., (2013). Multiobjective Optimization and Comparison of Nonsingleton Type-1 and Singleton Interval Type-2 Fuzzy Logic Systems. IEEE Transactions on Fuzzy Systems. 21 (3)

Garcia-Valverde, T., Garcia-Sola, A., Hagras, H., Dooley, JA., Callaghan, V. and Botia, JA., (2013). A Fuzzy Logic-Based System for Indoor Localization Using WiFi in Ambient Intelligent Environments. IEEE Transactions on Fuzzy Systems. 21 (4)

LEE, C-S., WANG, M-H., HAGRAS, H., CHEN, Z-W., LAN, S-T., HSU, C-Y., KUO, S-E., KUO, H-C. and CHENG, H-H., (2012). A NOVEL GENETIC FUZZY MARKUP LANGUAGE AND ITS APPLICATION TO HEALTHY DIET ASSESSMENT. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 20 (supp02)

Lee, C-S., Wang, M-H., Chen, Y-J., Hagras, H., Wu, M-J. and Teytaud, O., (2012). Genetic fuzzy markup language for game of NoGo. Knowledge-Based Systems. 34

Wagner, C., Goumopoulos, C. and Hagras, H., (2012). Emerging and adaptive fuzzy logic based behaviours in activity sphere centred ambient ecologies. Pervasive and Mobile Computing. 8 (4)

Hagras, H. and Wagner, C., (2012). Towards the Wide Spread Use of Type-2 Fuzzy Logic Systems in Real World Applications. IEEE Computational Intelligence Magazine. 7 (3)

Hagras, H. and Wagner, C., (2012). Towards the Widespread Use of Type-2 Fuzzy Logic Systems in Real World Applications. IEEE Computational Intelligence Magazine. 7 (3)

Lee, C., Wang, M., Hagras, H., Chen, Z., Lan, S., Hsu, C., Kuo, S., Kuo, H. and Cheng, H., (2012). A novel genetic fuzzy markup language and its application to healthy diet assessment. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 20 (2)

Hagras, H., Wagner, C., Kameas, A., Goumopoulos, C., Meliones, A., Seremeti, L., Heinroth, T., Minker, W., Bellik, Y. and Pruvost, G., (2012). Symbiotic Ecologies in Next Generation Ambient Intelligent Environments.. IJNGC. 3

Sahab, N. and Hagras, H., (2011). Adaptive Non-singleton Type-2 Fuzzy Logic Systems: A Way Forward for Handling Numerical Uncertainties in Real World Applications. International Journal of Computers, Communications and Control. 5 (3)

Wagner, C. and Hagras, H., (2010). Toward General Type-2 Fuzzy Logic Systems Based on zSlices. IEEE Transactions on Fuzzy Systems. 18 (4)

Duman, H., Hagras, H. and Callaghan, V., (2010). A multi-society-based intelligent association discovery and selection for ambient intelligence environments. ACM Transactions on Autonomous and Adaptive Systems. 5 (2)

Lee, C-S., Wang, M-H., Acampora, G., Hsu, C-Y. and Hagras, H., (2010). Diet assessment based on type-2 fuzzy ontology and fuzzy markup language. International Journal of Intelligent Systems. 25 (12)

Mendel, J., Zadeh, L., Trillas, E., Yager, R., Lawry, J., Hagras, H. and Guadarrama, S., (2010). What Computing with Words Means to Me [Discussion Forum. IEEE Computational Intelligence Magazine. 5 (1)

Callaghan, V. and Hagras, H., (2010). Journal of Ambient Intelligence and Smart Environments: Preface. Journal of Ambient Intelligence and Smart Environments. 2 (3)

Lee, Wang and Hagras, (2010). A Type-2 Fuzzy Ontology and its Application to Personal Diabetic Diet Recommendation. IEEE Transactions on Fuzzy Systems. 18 (2)

Rivera-illingworth, F., Callaghan, V. and Hagras, H., (2010). Detection Of Normal and Novel Behaviours In Ubiquitous Domestic Environments. The Computer Journal. 53 (2)

Lee, C., Wang, M., Acampora, G., Hsu, C. and Hagras, H., (2010). Type-2 Fuzzy Markup Language Based Ontology and Its Application to Diet Assessment. The International Journal of Intelligent Systems. 25 (12)

Hagras, H., Ramadan, R., Wanas, N., Nawito, M., Mohamed, N., Aly, S. and Moustafa, M., (2009). Egypt Chapter Report [Family Corner. IEEE Computational Intelligence Magazine. 4 (4)

Tawil, E. and Hagras, H., (2009). An Adaptive Genetic-Based Incremental Architecture for the On-Line Coordination of Embedded Agents. Cognitive Computation. 1 (4)

Jammeh, E., Fleury, M., Wagner, C., Hagras, H. and Ghanbari, M., (2009). Interval Type-2 Fuzzy Logic Congestion Control for Video Streaming Across IP Networks. IEEE Transactions on Fuzzy Systems. 17 (5)

Cook, DJ., Hagras, H., Callaghan, V. and Helal, A., (2009). Making our environments intelligent. Pervasive and Mobile Computing. 5 (5)

Hagras, H., Callaghan, V., Cook, D. and Helal, A., (2009). The fourth international conference on intelligent environments (IE 08): a report. AI Magazine. 30 (1)

Hagras, H. and Wagner, C., (2009). Introduction to Interval Type-2 Fuzzy Logic Controllers - Towards Better Uncertainty Handling in Real World Applications. The IEEE Systems, Man and Cybernetics eNewsletter (27)

Hagras, H., (2008). Employing computational intelligence to generate more intelligent and energy efficient living spaces. International Journal of Automation and Computing. 5 (1)

Duman, H., Hagras, H. and Callaghan, V., (2008). Intelligent Association Exploration and Exploitation of Fuzzy Agents in Ambient Intelligent Environments. Journal of Uncertain Systems. 2 (2)

Hagras, H., Doctor, F., Callaghan, V. and Lopez, A., (2007). An Incremental Adaptive Life Long Learning Approach for Type-2 Fuzzy Embedded Agents in Ambient Intelligent Environments. IEEE Transactions on Fuzzy Systems. 15 (1)

Hagras, H., (2007). Embedding Computational Intelligence in Pervasive Spaces. IEEE Pervasive Computing. 6 (3)

Hagras, H., (2007). Type-2 FLCs: A New Generation of Fuzzy Controllers. IEEE Computational Intelligence Magazine. 2 (1)

Duman, H., Hagras, H. and Callaghan, V., (2007). Intelligent association selection of embedded agents in intelligent inhabited environments. Pervasive and Mobile Computing. 3 (2)

Hagras, H., (2006). Comments on "Dynamical Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN). IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). 36 (5)

Hagras, H., (2006). Comments on "Dynamical optimal training for interval type-2 fuzzy neural network (THNN)". IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS. 36 (5)

Doctor, F., Hagras, H. and Callaghan, V., (2005). A Fuzzy Embedded Agent-Based Approach for Realizing Ambient Intelligence in Intelligent Inhabited Environments. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans. 35 (1)

DOCTOR, F., HAGRAS, H. and CALLAGHAN, V., (2005). A type-2 fuzzy embedded agent to realise ambient intelligence in ubiquitous computing environments. Information Sciences. 171 (4)

HAGRAS, H., CALLAGHAN, V. and COLLEY, M., (2005). Intelligent embedded agents. Information Sciences. 171 (4)

Hagras, H., Callaghan, V. and Colley, M., (2004). Learning and adaptation of an intelligent mobile robot navigator operating in unstructured environment based on a novel online Fuzzy–Genetic system. Fuzzy Sets and Systems. 141 (1)

Callaghan, V., Clarke, G., Colley, M., Hagras, H., Chin, JSY. and Doctor, F., (2004). Inhabited Intelligent Environments. BT Technology Journal. 22 (3)

Hagras, H., (2004). A Hierarchical Type-2 Fuzzy Logic Control Architecture for Autonomous Mobile Robots. IEEE Transactions on Fuzzy Systems. 12 (4)

Hagras, H., Callaghan, V., Colley, M., Clarke, G., Pounds-Cornish, A. and Duman, H., (2004). Creating an Ambient-Intelligence Environment Using Embedded Agents. IEEE Intelligent Systems. 19 (06)

Attallah, A., (2004). Utility of a novel HCV-NS4 antigen detection immunoassay for monitoring treatment of HCV-infected individuals with pegylated interferon α-2a. Hepatology Research. 28 (2)

Schlaf, M., Hagras, H. and Sands, D., (2003). Optimization strategies for parametric analysis of thin-film reflectivity spectra. IEEE Transactions on Instrumentation and Measurement. 52 (5)

Hagras, H., Colley, M., Callaghan, V. and Carr-West, M., (2002). Online learning and adaptation of autonomous mobile robots for sustainable agriculture. Autonomous Robots. 13 (1)

Hagras, H. and Sobh, T., (2002). Intelligent learning and control of autonomous robotic agents operating in unstructured environments. Information Sciences. 145 (1-2)

Hagras, H., (2001). Computational intelligence techniques applied to cooperative multi-robotics systems. International Journal of Robotics and Automation. 16 (4)

Hagras, H., Callaghan, V. and Collry, M., (2001). Outdoor mobile robot learning and adaptation. IEEE Robotics & Automation Magazine. 8 (3)

Hagras, H., Callaghan, V. and Colley, M., (1999). An embedded‐agent technique for industrial control environments where process modelling is difficult. Assembly Automation. 19 (4)

Conferences (65)

Yao, B., Hagras, H., Lepley, JJ., Peall, R. and Butler, M., (2017). An evolutionary optimization based interval type-2 fuzzy classification system for human behaviour recognition and summarisation

Nairm, S. and Hagras, H., (2013). A general type-2 fuzzy logic based multi-criteria group decision making for lighting level selection in an intelligent environment

Bosnak, M. and Blazic, S., (2012). Sparse VSLAM with Camera-Equipped Quadrocopter.

Lanza-Gutiérrez, JM., Pulido, JAG., Vega-Rodríguez, MA. and Sánchez-Pérez, JM., (2012). Relay Node Positioning in Wireless Sensor Networks by Means of Evolutionary Techniques.

Kurowski, M., Korte, H. and Lampe, BP., (2012). Search-and-Rescue-Operation with an Autonomously Acting Rescue Boat.

Idris, M., Mehrabian, A., Hamou-Lhadj, A. and Khoury, R., (2012). Pattern-Based Trace Correlation Technique to Compare Software Versions.

Golestan, K., Jundi, A., Nassar, L., Sattar, F., Karray, F., Kamel, MS. and Boumaiza, S., (2012). Vehicular Ad-hoc Networks(VANETs): Capabilities, Challenges in Information Gathering and Data Fusion.

Nassar, L., Jundi, A., Golestan, K., Sattar, F., Karray, F., Kamel, MS. and Boumaiza, S., (2012). Vehicular Ad-hoc Networks(VANETs): Capabilities, Challenges in Context-Aware Processing and Communication Gateway.

Voulkidis, AC., Livieratos, S. and Cottis, PG., (2012). Spatially Correlated Multi-modal Wireless Sensor Networks: A Coalitional Game Theoretic Approach.

Silva, A., Neves, A. and Gonçalves, T., (2012). An Heterogeneous Particle Swarm Optimizer with Predator and Scout Particles.

Mittal, A., Sofat, S. and Hancock, ER., (2012). An Efficient Scheme for Color Edge Detection in Uniform Color Space.

Wang, L., Yang, SX. and Biglarbegian, M., (2012). Bio-inspired Navigation of Mobile Robots.

Mirabdollah, MH. and Mertsching, B., (2012). Bearing Only SLAM: A New Particle Filter Based Approach.

Guedea-Elizalde, F. and Villegas-Hernandez, YS., (2012). Automatic Planning in a Robotized Cell.

Zhu, J. and Gueaieb, W., (2012). Adaptive Fuzzy Logic Control for Time-Delayed Bilateral Teleoperation.

Ven, OSVD., Yang, R., Xia, S., Schieveen, JPV., Spronck, JW., Schmidt, RHM. and Nihtianov, S., (2012). Autonomous Self-aligning and Self-calibrating Capacitive Sensor System.

Alves, FS., Dias, RA., Cabral, J. and Rocha, LA., (2012). Autonomous MEMS Inclinometer.

Abida, K., Karray, F. and Abida, W., (2012). A Novel Voting Scheme for ROVER Using Automatic Error Detection.

Teófilo, LF., Passos, N., Reis, LP. and Cardoso, HL., (2012). Adapting Strategies to Opponent Models in Incomplete Information Games: A Reinforcement Learning Approach for Poker.

Abghari, A., Abida, K. and Karray, F., (2012). Features' Weight Learning towards Improved Query Classification.

Mittal, A., Sofat, S. and Hancock, ER., (2012). Detection of Edges in Color Images: A Review and Evaluative Comparison of State-of-the-Art Techniques.

Siddiqui, R. and Lindley, C., (2012). Multi-Cue Based Place Learning for Mobile Robot Navigation.

Khaki, K. and Stonham, TJ., (2012). Face Recognition with Weightless Neural Networks Using the MIT Database.

Ripon, KSN., Glette, K., Høvin, M. and Tørresen, J., (2012). Job Shop Scheduling with Transportation Delays and Layout Planning in Manufacturing Systems: A Multi-objective Evolutionary Approach.

Filho, CFFC., Melo, RDO. and Costa, MGF., (2012). Detecting Natural Gas Leaks Using Digital Images and Novelty Filters.

Elmogy, AM., Khamis, AM. and Karray, F., (2012). Market-Based Framework for Mobile Surveillance Systems.

Frattini, F., Esposito, M. and Pietro, GD., (2012). MobiFuzzy: A Fuzzy Library to Build Mobile DSSs for Remote Patient Monitoring.

Alemzadeh, M., Abida, K., Khoury, R. and Karray, F., (2012). Enhancement of the ROVER's Voting Scheme Using Pattern Matching.

Alhaddad, MJ., Kamel, M., Malibary, H., Thabit, K., Dahlwi, F. and Hadi, A., (2012). P300 Speller Efficiency with Common Average Reference.

Sun, J., Sun, J., Abida, K. and Karray, F., (2012). A Novel Template Matching Approach to Speaker-Independent Arabic Spoken Digit Recognition.

Ibrahim, M., Khairy, A., Hagras, H., Abdel-Rahim, N., Shafei, AE. and Shaltout, A., (2011). Intelligent energy management strategy for decentralized battery storage in grid connected wind energy conversion systems

Al Mehdar, M. and Hagras, H., (2011). An Adaptive Type-2 Fuzzy Based Charging Technique for Market Design Agents in Uncertain Environments

Sahab, N. and Hagras, H., (2011). An Adaptive Type-2 Input Based Nonsingleton Type-2 Fuzzy Logic System for Real World Applications

Dooley, J., Henson, M., Callaghan, V., Hagras, H., Al-Ghazzawi, D., Malibari, A., Al-Haddad, M. and Al-Ghamdi, AA., (2011). A Formal Model for Space Based Ubiquitous Computing

Naim, S. and Hagras, H., (2011). Type-2 Fuzzy Logic in Multi-Criteria Group Decision Making with Intuitionistic Evaluation

Almeida, M., Moreira, N. and Reis, R., (2011). Incremental DFA Minimisation

Wagner, C. and Hagras, H., (2010). A collection operator for type-2 fuzzy logic systems

Hagras, H. and Hong, TP., (2010). Programme chairs - Welcome message

Wagner, C. and Hagras, H., (2010). Uncertainty and type-2 fuzzy sets and systems

Sahab, N. and Hagras, H., (2010). A hybrid approach to modeling input variables in non-singleton type-2 fuzzy logic systems

Azouz, M., Shaltout, A., Elshafei, MAL., Abdel-Rahim, M., Hagras, H., Zaher, M. and Ibrahim, M., (2010). Fuzzy Logic Control of Wind Energy Systems

Ibrahim, M., Khairy, A., Hagras, H., Zaher, M., El Shafei, A., Shaltout, A. and Rehim, NA., (2010). Studying the Effect of Decentralized Battery Storage to Smooth the Generated Power of a Grid Integrated Wind Energy Conversion System

Hagras, H., (2009). Welcome message

Wagner, C. and Hagras, H., (2009). Employing Interpolation to enable the operation High Order Fuzzy Systems on Embedded Systems

Kameas, A., Hagras, H., Goumopoulos, C., Heinroth, T., Meliones, A., Gardner, M., Economou, D., Pruvost, G., Bellik, Y. and Minker, W., (2009). Pervasive System Architecture that supports Adaptation using Agents and Ontologies

Jammeh, E., Fleury, M., Wagner, C., Hagras, H. and Ghanbari, M., (2008). Interval type-2 fuzzy logic congestion control of video streaming

Wagner, C. and Hagras, H., (2007). A Genetic Algorithm Based Architecture for Evolving Type-2 Fuzzy Logic Controllers for Real World Autonomous Mobile Robots.

Duman, H., Hagras, H. and Callaghan, V., (2007). A Fuzzy Based Architecture for Learning Relevant Embedded Agents Associations in Ambient Intelligent Environments.

Rivera-Illingworth, F., Callaghan, V. and Hagras, H., (2006). Towards the detection of temporal behavioural patterns in intelligent environments

Dooley, J., Callaghan, V., Hagras, H., Bull, P. and Rohlfing, D., (2006). Ambient intelligence - Knowledge representation, processing and distribution in intelligent inhabited environments

O'Flynn, B., Murphy, F., Buckley, J., Laffey, D., Barton, J., Hagras, H., Colley, M. and Pounds-Cornish, A., (2006). SOCIAL -Collaborative agent development

Lynch, C., Hagras, H. and Callaghan, V., (2006). Embedded Interval Type-2 Neuro-Fuzzy Speed Controller for Marine Diesel Engines

Tawil, E. and Hagras, H., (2005). Adaptive on-line co-ordination of ubiquitous computing devices with multiple objectives and constraints

Lopez, A., Alvarez, D., Doctor, F., Hagras, H. and Callaghan, V., (2005). A comparison of some data-based methods for the off-line generation of fuzzy logic controllers for an intelligent building environment

Limb, PR., Armitage, S., Chin, JSY., Kalawsky, R., Callaghan, V., Bull, PM., Hagras, H. and Colley, M., (2005). User interaction in a shared information space - A pervasive environment for the home

Hagras, H. and Colley, M., (2005). Collaborating multi robotic agents for operations in inaccessible environments

Rivera-Illingworth, F., Callaghan, V. and Hagras, H., (2005). A neural network agent based approach to activity detection in AmI environments

Chin, JSY., Callaghan, V., Colley, M., Hagras, H. and Clarke, G., (2005). Virtual appliances for pervasive computing: A deconstructionist, ontology based, programming-by-example approach

Tawil, E. and Hagras, H., (2004). An adaptive multi embedded-agent architecture for intelligent inhabited environments

Hagras, H., Callaghan, V., Colley, M., Clarke, G. and Duman, H., (2003). Online learning and adaptation for intelligent embedded agents operating in domestic environments

Hagras, H., Callaghan, V., Colley, M. and Clarke, G., (2001). A hierarchical fuzzy genetic multi-agent architecture for intelligent buildings sensing and control

Hagras, H., Callaghan, V. and Colley, M., (2000). An embedded-agent architecture for online learning & control in intelligent machines

Hagras, H., Callaghan, V. and Colley, M., (1999). Online learning of fuzzy behaviours using genetic algorithms & real-time interaction with the environment

Hagras, H., Callaghan, V., Colley, M. and Carr-West, M., (1999). A behaviour based hierarchical fuzzy control architecture for agricultural autonomous mobile robots

Hagras, H., Callaghan, V., Colley, M. and Carr-West, M., (1999). Developing an Outdoor Fuzzy Logic Controlled Agricultural Vehicle for Crop Following and Harvesting.

Chapters (13)

Starkey, AJ., Hagras, H., Shakya, S. and Owusu, G., (2016). A Genetic Algorithm Based Approach for the Simultaneous Optimisation of Workforce Skill Sets and Team Allocation. In: Research and Development in Intelligent Systems XXXIII Incorporating Applications and Innovations in Intelligent Systems XXIV. 253- 266. 978-3-319-47174-7

Kumbasar, T. and Hagras, H., (2015). Interval type-2 fuzzy pid controllers. In: Springer Handbook of Computational Intelligence. 285- 294. 9783662435052

Kumbasar, T. and Hagras, H., (2015). Interval Type-2 Fuzzy PID Controllers.. In: Handbook of Computational Intelligence. 285- 294. 978-3-662-43504-5

Wang, M-H., Lee, C-S., Hagras, H., Su, M-K., Tseng, Y-Y., Wang, H-M., Wang, Y-L. and Liu, C-H., (2013). Applying FML-Based Fuzzy Ontology to University Assessment.. In: On the Power of Fuzzy Markup Language. 133- 147. 978-3-642-35487-8

Huang, H-D., Acampora, G., Loia, V., Lee, C-S., Hagras, H., Wang, M-H., Kao, H-Y. and Chang, J-G., (2013). Fuzzy Markup Language for Malware Behavioral Analysis.. In: On the Power of Fuzzy Markup Language. 113- 132. 978-3-642-35487-8

Dooley, J., Hagras, H., Callaghan, V. and Henson, M., (2013). The Tailored Fabric of Intelligent Environments.. In: Internet of Things and Inter-cooperative Computational Technologies for Collective Intelligence. 321- 344. 978-3-642-34951-5

Wang, M-H., Lee, C-S., Chen, Z-W., Hagras, H., Kuo, S-E., Kuo, H-C. and Cheng, H-H., (2013). A Type-2 FML-Based Fuzzy Ontology for Dietary Assessment.. In: On the Power of Fuzzy Markup Language. 149- 168. 978-3-642-35487-8

Lee, C-S., Wang, M-H., Su, M-K., Wu, M-H. and Hagras, H., (2013). A Type-2 FML-Based Meeting Scheduling Support System.. In: On the Power of Fuzzy Markup Language. 169- 187. 978-3-642-35487-8

Hagras, H. and Wagner, C., (2011). Artefact Adaptation in Ambient Intelligent Environments. In: Next Generation Intelligent Environments: Ambient Adaptive Systems. 127- 151. 9781461412984

Hagras, H., (2011). Towards Online Adaptive Ambient Intelligent Environments for Multiple Occupants. In: Adaptive and Intelligent Systems. creators- Hagras=3AHani=3A=3A. 9783642238567

Kameas, A., Goumopoulos, C., Hagras, H., Callaghan, V., Heinroth, T. and Weber, M., (2009). An Architecture that Supports Task-Centered Adaptation. In: Advanced Intelligent Environments. 41- 69. 9780387764849

Hagras, H., (2006). Fuzzy logic based control mechanisms for handling the uncertainties facing mobile robots in changing unstructured environments. In: Advances in Industrial Control. 175- 189

Remagnino, P., Hagras, H., Monekosso, N. and Velastin, S., (2005). Ambient intelligence: A gentle introduction. In: Ambient Intelligence: A Novel Paradigm. 1- 14. 0387229906

Books (4)

Mendel, JM., Hagras, H., Tan, WW., Melek, WW. and Ying, H., (2014).Introduction To Type-2 Fuzzy Logic Control: Theory and Applications. 9781118886540

Kamel, M., Karray, F. and Hagras, H., (2012).Preface. 9783642313677

Minker, W., Weber, M., Hagras, H., Callagan, V. and Kameas, AD., (2009).Advanced intelligent environments. 9780387764849

Hassanien, A., Abawajy, JH., Abraham, A. and Hagras, H., (2009).Pervasive Computing: Innovations in Intelligent Multimedia and Applications. Springer. 9781848825987

Grants and funding

2016

Force Field Operations

British Telecommunications Plc

Force Field Operations

British Telecommunications Plc

2015

30% To develop computational intelligence based machine vision tools for dealing with uncertainty in descision making systems

Technology STrategy Board

70% To develop computational intelligence based machine vision tools for dealing with uncertainty in descision making systems

Leonardo MW Ltd

50% - To develop remote workforce management solutions and embed knowledge of advanced computational intelligence, intelligent environments and augmented reality

Technology STrategy Board

50% - To develop remote workforce management solutions and embed knowledge of advanced computational intelligence, intelligent environments and augmented reality

British Telecommunications Plc

2014

Jupiter & next generation forecasting models

British Telecommunications Plc

Development of a hardware demonstration platform able to monitor and detect human behaviour in a residential environment

Leonardo MW Ltd

Advanced Resource Planning System for Organisational Design

British Telecommunications Plc

2013

Rule-based optimisation for operational supply planning

British Telecommunications Plc

Type-2 Fuzzy Logic Rule-based optimisation for operational supply planning

British Telecommunications Plc

Robotics & Intelligent Environments Research Group

King Abdulaziz University

2011

Optimised Production Planning Model - Studentship

British Telecommunications Plc

An Intelligent Type-2 Fuzzy Logic Based System for Schedule Adherence of Optimised Planning Systems in BT

British Telecommunications Plc

2010

MSc. Studentship - Distributed and Fuzzy Resource Planning

British Telecommunications Plc

67% To develop embedded systems for intelligent process control

Technology STrategy Board

33% To develop embedded systems for intelligent process control

Sanctuary Personnel Ltd

2009

Intel - Michael Gardner

Intel Corporation

67% Developing Intelligent Data KTP

Technology STrategy Board

33% Developing Intelligent Data KTP

Sanctuary Personnel Ltd

Scaling Intelligent Environments

King Abdulaziz University

Contact

hani@essex.ac.uk
+44 (0) 1206 873601

Location:

5B.524, Colchester Campus