糖心Vlog

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

  • Academic support hours

    Thursdays 11am-1pm

Profile

Biography

Hani Hagras is a Professor of Artificial Intelligence, Director of Impact, Director of the Computational Intelligence Centre and Head of the Artificial Intelligence Research Group, in the School of Computer Science and Electronic Engineering, 糖心Vlog, UK. He is a Fellow of Institute of Electrical and Electronics Engineers (IEEE), a Fellow of the Institution of Engineering and Technology (IET), Principal Fellow of the UK Higher Education Academy (PFHEA), Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) and Fellow of the Artificial Intelligence Industry Alliance (AIIA). His main research interests are in Explainable Artificial Intelligence (XAI) and Data Science with applications to Finance, Cyber Physical Systems, Neuroscience, Life Sciences, Uncertainty Management, Intelligent Robotics and Intelligent Control of Industrial Processes. He has authored more than 500 papers in international journals, conferences and books. He is amongst the top 2% of the most-cited scientists in the World (Scopus August 2024) and he is recognised by ScholarGPS as Highly Ranked Scholar- Lifetime. His work received funding from major research councils and industry. He holds eleven industrial patents in the field of Explainable AI. His research has won numerous prestigious international awards where he was awarded by the IEEE Computational Intelligence Society (CIS), the 2010 Outstanding Paper Award in the IEEE Transactions on Fuzzy Systems and the 2004 Outstanding Paper Award in the IEEE Transactions on Fuzzy Systems. He was also awarded the 2015 and 2017 Global Telecommunications Business award for his joint project with British Telecom. In 2016, he was elected as Distinguished Lecturer by the IEEE Computational Intelligence Society. His work has also won best paper awards in several leading international conferences including the 2014 and 2006 IEEE International Conference on Fuzzy Systems, the 2012 UK Workshop on Computational Intelligence and the 2016 International Conference of the BCS SGAI International Conference on Artificial Intelligence. He was awarded by the IEEE Computational Intelligence Society (CIS) the 2011 IEEE CIS Outstanding Chapter Award. In 2017, he was awarded by the 糖心Vlog, the 2017 best Research impact award for his work with British Telecom. He acted as the Principal Investigator for a project which was awarded by the UK Technology Strategy Board, the 2011 UK Best Knowledge Transfer Partnership for London and the East Region. He also acted as the Principal Investigator for a project which was awarded the 2009 Lord Stafford Achievement in Innovation Award for East of England. In 2010, he Led a Research Students team to win the First place in the RoboCup 2010. In 2007, he was Shortlisted by the Times Higher Education supplement (THES) for the UK Young researcher of the year award. He is Associate Editor of many journals including IEEE Transactions on Fuzzy Systems, IEEE Transactions on Artificial Intelligence, Knowledge Based Systems, Cognitive Computations and others. He served as the General and Programme Chair of numerous major international conferences where he served as the General co-Chair of the 2007 IEEE International Conference on Fuzzy Systems, and Programme Chair of the 2021 and 2017 IEEE International Conference on Fuzzy Systems as well as many other conferences

Qualifications

  • PhD, Computer Science 糖心Vlog, (2000)

  • Msc in Electrical Engineering University of Alexandria, (1996)

  • Bsc in Electrical Engineering University of Alexandria, (1994)

Appointments

糖心Vlog

  • Director of Impact, School of Computer Science and Electronic Engineering, 糖心Vlog (1/7/2021 - present)

  • Director of Research, School of Computer Science and Electronic Engineering, 糖心Vlog (1/7/2017 - 1/7/2021)

  • Head of the Artificial Intelligence Research Group, School of Computer Science and Electronic Engineering, 糖心Vlog (1/6/2019 - present)

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

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

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

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

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 )

Key words: Fuzzy Logic
Open to supervise

Explainable Artificial Intelligence (XAI)

Current research

Robotics and Intelligent Control

Explainable Artificial Intelligence (XAI)

Data Science

Teaching and supervision

Current teaching responsibilities

  • Intelligent Systems and Robotics (CE801)

  • Neural Networks and Deep Learning (CE889)

Previous supervision

Liam Joseph Beasley
Liam Joseph Beasley
Thesis title: Explainable Strategic Optimisation of Grand Scale Problems
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 20/2/2024
Kabo Elliot Pule
Kabo Elliot Pule
Thesis title: Multi-Objective Resource Optimization of Unmanned Aerial Vehicles and Internet of Things Devices in Time Critical Applications Using Evolutionary Approaches
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 3/1/2024
Shreyas Jagdish Upasane
Shreyas Jagdish Upasane
Thesis title: An Incremental Self-Learning Interval Type-2 Fuzzy Logic Based Explainable Approach to Predictive Maintenance
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 6/11/2023
Hugo Leon Garza
Hugo Leon Garza
Thesis title: An Explainable Ai Approach to Process Data in Mixed Reality Environments for Field Service Operations
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 13/7/2023
Lewis Henry Frederick Veryard
Lewis Henry Frederick Veryard
Thesis title: Type 2 Fuzzy Single and Multi-Objective Optimisation Systems for Telecommunication Capacity Planning
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 16/9/2022
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
Jareth Charles Wolfe
Jareth Charles Wolfe
Thesis title: An Explainable Artificial Intelligence Approach for Decoding the Enhancer Histone Modification Code and Identification of Novel Enhancers
Degree subject: Biological Sciences
Degree type: Doctor of Philosophy
Awarded date: 11/4/2022
Ravikiran Chimatapu
Ravikiran Chimatapu
Thesis title: An Explainable Artificial Intelligence Approach Based on Deep Type-2 Fuzzy Logic System
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 21/7/2021
Emmanuel Ferreyra Olivares
Emmanuel Ferreyra Olivares
Thesis title: A Type-2 Fuzzy Logic Based Goal-Driven Simulation for Optimising Field Service Delivery
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 23/3/2021
Wei Song
Wei Song
Thesis title: A Fuzzy Logic-Based System for Soccer Video Scenes Classification
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 14/2/2019
Andrew John Starkey
Andrew John Starkey
Thesis title: Many-Objective Genetic Type-2 Fuzzy Logic Based Workforce Optimisation Strategies for Large Scale Organisational Design
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 7/3/2018
Akeem Aderibigbe Adebomehin
Akeem Aderibigbe Adebomehin
Thesis title: Ultra-Wideband Ieee802.15.4A Cognitive Localization Methods for the 5G Environment.
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 3/7/2017
Khalid Sulaiman Z Almohammadi
Khalid Sulaiman Z Almohammadi
Thesis title: Type-2 Fuzzy Logic Based Systems for Adaptive Learning and Teaching Within Intelligent E-Learning Environments
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 7/7/2016
Bo Yao
Bo Yao
Thesis title: A Big Bang Big Crunch Type-2 Fuzzy Logic System for Machine Vision-Based Event Detection and Summarization in Real-World Ambient Assisted Living
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 22/10/2015
Aysenur Bilgin
Aysenur Bilgin
Thesis title: A Linear General Type-2 Fuzzy Logic Based Computing with Words Framework Applied to Ambient Intelligent Environments
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 1/7/2015
Ahmed Mohamed Hany Abdelaziz Mohamed
Ahmed Mohamed Hany Abdelaziz Mohamed
Thesis title: An Optimised Hierarchical Type-2 Fuzzy Logic Based Dynamic Real Time Scheduling
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 13/3/2015
Dario Bernardo
Dario Bernardo
Thesis title: A Type-2 Fuzzy Logic Based System for Linguistic Summarization and Prediction for Financial Data
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 3/12/2014
Nur Syibrah Binti Muhamad Naim
Nur Syibrah Binti Muhamad Naim
Thesis title: A Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 3/3/2014
Nazanin Sahab
Nazanin Sahab
Thesis title: Adaptive Type-2 Non-Singleton Type-2 Fuzzy Logic System for Handling Numerical and Linguistic Uncertainties in Complex Processes
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 21/1/2013
Summer Mahmoud Abdelhay Kassem
Summer Mahmoud Abdelhay Kassem
Thesis title: A Type 2 Fuzzy Logic System for Workforce Management in the Telecommunications Domain
Degree subject: Computer Science
Degree type: Master of Science (by Dissertation)
Awarded date: 4/5/2012
Ahmed Mohamed Hany Abdelaziz Mohamed
Ahmed Mohamed Hany Abdelaziz Mohamed
Thesis title: A Hierarchical Fuzzy Logic Based Resource Planning System
Degree subject: Computer Science
Degree type: Master of Science (by Dissertation)
Awarded date: 2/12/2011

Publications

Publications (2)

Fumanal-Idocin, J., Andreu-Perez, J., Cord贸n, 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

Journal articles (115)

Jamalifard, M., Andreu-Perez, J., Hagras, H. and Martinez, L., (2024). . IEEE Transactions on Fuzzy Systems. 32 (5), 2987-2998

Maqsood, K., Hagras, H. and Zabet, NR., (2024). An overview of artificial intelligence in the field of genomics. Discover Artificial Intelligence. 4 (1)

Ghozzi, Y., Hamdani, TM., Hagras, H., Ouahada, K., Chabchoub, H. and Alimi, AM., (2024). . Neurocomputing. 603, 128251-128251

Fumanal-Idocin, J., Andreu-Perez, J., Cord贸n, O., Hagras, H. and Bustince, H., (2024). . IEEE Transactions on Fuzzy Systems. 32 (4), 1915-1926

Kiani, M., Andreu-Perez, J. and Hagras, H., (2023). . IEEE Transactions on Artificial Intelligence. 4 (3), 573-586

Veryard, L., Hagras, H., Conway, A. and Owusu, G., (2023). . Knowledge-Based Systems. 260, 110134-110134

Upasane, SJ., Hagras, H., Anisi, MH., Savill, S., Taylor, I. and Manousakis, K., (2023). . IEEE Transactions on Artificial Intelligence. 5 (2), 490-504

Almaraash, M., Abdulrahim, M. and Hagras, H., (2023). . IEEE Transactions on Fuzzy Systems. 32 (4), 2102-2115

Kiani, M., Andreu-Perez, J., Hagras, H., Papageorgiou, EI., Prasad, M. and Lin, C-T., (2022). . IEEE Transactions on Cognitive and Developmental Systems. 14 (1), 50-63

Yosr, G., Baklouti, N., Hagras, H., Ben ayed, M. and Alimi, AM., (2022). . IEEE Transactions on Fuzzy Systems. 30 (3), 805-817

Cherif, S., Baklouti, N., Hagras, H. and Alimi., AM., (2022). . IEEE Transactions on Fuzzy Systems. 30 (5), 1260-1271

Leon-Garza, H., Hagras, H., Pe帽a-Rios, A., Conway, A. and Owusu, G., (2022). . Information Fusion. 88, 115-125

Andreu-Perez, J., Hagras, H., Kiani, M., Rigato, S. and Filippetti, ML., (2022). . IEEE Computational Intelligence Magazine. 17 (1), 16-33

Mai, DS., Ngo, LT., Trinh, LH. and Hagras, H., (2021). . Information Sciences. 548, 398-422

Boumhidi, J., Nfaoui, EH., Hagras, H. and Vellasco, M., (2021). Special issue on Recent Advances in Computational Intelligence and Cognitive Systems (RACICS). Cognitive Systems Research. 70, 63-63

Andreu-Perez, J., Emberson, LL., Kiani, M., Filippetti, ML., Hagras, H. and Rigato, S., (2021). . Communications Biology. 4 (1), 1077-

Wolfe, JC., Mikheeva, LA., Hagras, H. and Zabet, NR., (2021). . Genome Biology. 22 (1), 308-

Mendel, JM., Chimatapu, R. and Hagras, H., (2020). . IEEE Transactions on Fuzzy Systems. 28 (4), 783-794

Veryard, L., Hagras, H., Starkey, A., Conway, A. and Owusu, G., (2020). NNIR: N-Non-Intersecting-Routing Algorithm for Multi-Path Resilient Routing in Telecommunications Applications. International Journal of Computational Intelligence Systems. 13 (1), 352-352

Jarraya, Y., Bouaziz, S., Hagras, H. and Alimi, AM., (2019). . IEEE Transactions on Fuzzy Systems. 27 (6), 1174-1188

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2019). . IEEE Transactions on Fuzzy Systems. 27 (3), 502-514

Liu, Y., Rodriguez, RM., Hagras, H., Liu, H., Qin, K. and Martinez, L., (2019). Type-2 Fuzzy Envelope of Hesitant Fuzzy Linguistic Term Set: A New Representation Model of Comparative Linguistic Expression. IEEE Transactions on Fuzzy Systems. 27 (12), 2312-2326

Ruiz-Garcia, G., Hagras, H., Pomares, H. and Ruiz, IR., (2019). Toward a Fuzzy Logic System Based on General Forms of Interval Type-2 Fuzzy Sets. IEEE Transactions on Fuzzy Systems. 27 (12), 2381-2395

(2019). Erratum. Computer. 52 (1), 57-57

Andreu-Perez, J., Cao, F., Hagras, H. and Yang, G., (2018). . IEEE Transactions on Fuzzy Systems. 26 (1), 101-116

Pena Rios, AC., Hagras, H., Owusu, G. and Gardner, M., (2018). . IEEE Systems, Man, and Cybernetics Magazine. 4 (1), 20-31

Hagras, H. and Cosby, K., (2018). HOW GREAT WAS LOTFI ZADEH?: A FUZZY TRIBUTE TO AN INFLUENTIAL FIGURE IN COMPUTING. COMPUTER. 51 (1), 100-102

Hagras, H., (2018). . Computer. 51 (9), 28-36

Starkey, AJ., Hagras, H., Shakya, S. and Owusu, G., (2018). A Genetic Algorithm Based System for Simultaneous Optimisation of Workforce Skills and Teams. KI - K眉nstliche Intelligenz. 32 (4), 245-260

Colchester, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2017). . Journal of Artificial Intelligence and Soft Computing Research. 7 (1), 47-64

Almohammadi, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2017). . Soft Computing. 21 (22), 6859-6880

Almohammadi, K., Hagras, H., Yao, B., Alzahrani, A., Alghazzawi, D. and Aldabbagh, G., (2017). . Soft Computing. 21 (4), 965-979

Ruiz-Garc铆a, G., Hagras, H., Rojas, I. and Pomares, H., (2017). . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10147 LNAI, 3-26

Antonelli, M., Bernardo, D., Hagras, H. and Marcelloni, F., (2017). . IEEE Transactions on Fuzzy Systems. 25 (2), 249-264

Sarabakha, A., Imanberdiyev, N., Kayacan, E., Khanesar, MA. and Hagras, H., (2017). . Information Sciences. 417, 361-380

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), 2805-2819

De Miguel, L., Santos, H., Sesma-Sara, M., Bedregal, B., Jurio, A., Bustince, H. and Hagras, H., (2017). . IEEE Transactions on Fuzzy Systems. 25 (4), 993-1005

Acampora, G., Siciliano, B., Hagras, H. and Herrera, F., (2017). Conference Report on 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017) [Conference Reports]. IEEE Computational Intelligence Magazine. 12 (4), 6-8

Wei, S., Hagras, H. and Alghazzawi, D., (2016). . Memetic Computing. 8 (4), 307-323

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2016). . Information Sciences. 329, 390-411

Bilgin, A., Hagras, H., van Helvert, J. and Alghazzawi, D., (2016). . IEEE Transactions on Fuzzy Systems. 24 (2), 306-329

Starkey, A., Hagras, H., Shakya, S., Owusu, G., Mohamed, A. and Alghazzawi, D., (2016). . Memetic Computing. 8 (4), 269-286

Bustince, H., Barrenechea, E., Pagola, M., Fernandez, J., Xu, Z., Bedregal, B., Montero, J., Hagras, H., Herrera, F. and De Baets, B., (2016). . IEEE Transactions on Fuzzy Systems. 24 (1), 179-194

Mendel, JM., Hagras, H., Bustince, H. and Herrera, F., (2016). . IEEE Transactions on Fuzzy Systems. 24 (1), 249-250

Ruiz, G., Hagras, H., Pomares, H., Rojas, I. and Bustince, H., (2016). . IEEE Transactions on Fuzzy Systems. 24 (4), 1000-1008

Acampora, G., Alghazzawi, D., Hagras, H. and Vitiello, A., (2016). . Information Sciences. 333, 88-107

Almohammadi, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2016). . Journal of Artificial Intelligence and Soft Computing Research. 6 (2), 81-101

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2016). . IEEE Transactions on Fuzzy Systems. 24 (6), 1307-1319

Yao, B., Hagras, H., Alhaddad, MJ. and Alghazzawi, D., (2015). . Soft Computing. 19 (2), 499-506

Alhaddad, MJ., Mohammed, A., Kamel, M. and Hagras, H., (2015). . Soft Computing. 19 (4), 1019-1035

Bilgin, A., Hagras, H., Ghelli, A., Alghazzawi, D. and Aldabbagh, G., (2015). . IEEE Computational Intelligence Magazine. 10 (4), 66-78

Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2015). . IEEE Computational Intelligence Magazine. 10 (1), 44-51

Ghelli, A., Hagras, H. and Aldabbagh, G., (2015). . IEEE Transactions on Fuzzy Systems. 23 (6), 1984-1997

Kumbasar, T. and Hagras, H., (2015). . IEEE Transactions on Fuzzy Systems. 23 (4), 991-1013

Sola, HB., Fernandez, J., Hagras, H., Herrera, F., Pagola, M. and Barrenechea, E., (2015). . IEEE Transactions on Fuzzy Systems. 23 (5), 1876-1882

Sanz, JA., Bernardo, D., Herrera, F., Bustince, H. and Hagras, H., (2015). . IEEE Transactions on Fuzzy Systems. 23 (4), 973-990

Naim, S. and Hagras, H., (2014). . Soft Computing. 18 (7), 1305-1319

Kumbasar, T. and Hagras, H., (2014). . Information Sciences. 282, 277-295

Bernardo, D., Hagras, H. and Tsang, E., (2013). . Soft Computing. 17 (12), 2185-2201

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2013). . Soft Computing. 17 (12), 2203-2222

Garcia-Valverde, T., Garcia-Sola, A., Hagras, H., Dooley, JA., Callaghan, V. and Botia, JA., (2013). . IEEE Transactions on Fuzzy Systems. 21 (4), 702-718

Mendel, JM., Hagras, H. and John, RI., (2013). . IEEE Transactions on Fuzzy Systems. 21 (3), 397-398

Cara, AB., Wagner, C., Hagras, H., Pomares, H. and Rojas, I., (2013). . IEEE Transactions on Fuzzy Systems. 21 (3), 459-476

Dooley, J., Hagras, H., Callaghan, V. and Henson, M., (2013). The Tailored Fabric of Intelligent Environments. Studies in Computational Intelligence. 460, 321-344

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. Studies in Fuzziness and Soft Computing. 296, 113-132

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. Studies in Fuzziness and Soft Computing. 296, 133-147

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. Studies in Fuzziness and Soft Computing. 296, 149-168

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. Studies in Fuzziness and Soft Computing. 296, 169-187

Garcia-Valverde, T., Garcia-Sola, A., Hagras, H., Dooley, JA., Callaghan, V. and Botia, JA., (2013). . IEEE Transactions on Fuzzy Systems. 21 (4), 702-718

Naim, S. and Hagras, H., (2013). A Big-Bang Big-Crunch Optimized General Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making. Journal of Artificial Intelligence and Soft Computing Research. 3 (2), 117-132

Hagras, H. and Wagner, C., (2012). . IEEE Computational Intelligence Magazine. 7 (3), 14-24

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). . International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 20 (supp02), 247-278

Wagner, C., Goumopoulos, C. and Hagras, H., (2012). . Pervasive and Mobile Computing. 8 (4), 500-521

Lee, C-S., Wang, M-H., Chen, Y-J., Hagras, H., Wu, M-J. and Teytaud, O., (2012). . Knowledge-Based Systems. 34, 64-80

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.. Int. J. Next Gener. Comput.. 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), 14-24

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), 247-278

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), 503-529

Sahab, N. and Hagras, H., (2011). . International Journal of Computers Communications & Control. 6 (3), 503-503

Duman, H., Hagras, H. and Callaghan, V., (2010). . ACM Transactions on Autonomous and Adaptive Systems. 5 (2), 1-34

Rivera-illingworth, F., Callaghan, V. and Hagras, H., (2010). Detection Of Normal and Novel Behaviours In Ubiquitous Domestic Environments. The Computer Journal. 53 (2), 142-151

Callaghan, V. and Hagras, H., (2010). Preface. Journal of Ambient Intelligence and Smart Environments. 2 (3), 207-209

Wagner, C. and Hagras, H., (2010). . IEEE Transactions on Fuzzy Systems. 18 (4), 637-660

Lee, Wang and Hagras, (2010). . IEEE Transactions on Fuzzy Systems. 18 (2), 374-395

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), 1187-1216

Mendel, J., Zadeh, L., Trillas, E., Yager, R., Lawry, J., Hagras, H. and Guadarrama, S., (2010). . IEEE Computational Intelligence Magazine. 5 (1), 20-26

Lee, C., Wang, M., Acampora, G., Hsu, C. and Hagras, H., (2010). . The International Journal of Intelligent Systems. 25 (12), 1187-1216

Tawil, E. and Hagras, H., (2009). . Cognitive Computation. 1 (4), 300-326

Jammeh, EA., Fleury, M., Wagner, C., Hagras, H. and Ghanbari, M., (2009). . IEEE Transactions on Fuzzy Systems. 17 (5), 1123-1142

Cook, DJ., Hagras, H., Callaghan, V. and Helal, A., (2009). . Pervasive and Mobile Computing. 5 (5), 556-557

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), 124-125

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), 13-16

Hagras, H. and Wagner, C., (2009). . The IEEE Systems, Man and Cybernetics eNewsletter (27)

Duman, H., Hagras, H. and Callaghan, V., (2008). . Journal of Uncertain Systems. 2 (2), 133-143

Hagras, H., (2008). . International Journal of Automation and Computing. 5 (1), 1-9

Hagras, H., (2007). . IEEE Pervasive Computing. 6 (3), 85-89

Hagras, H., (2007). Type-2 FLCs: A New Generation of Fuzzy Controllers. IEEE Computational Intelligence Magazine. 2 (1), 30-43

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), 41-55

Duman, H., Hagras, H. and Callaghan, V., (2007). Intelligent association selection of embedded agents in intelligent inhabited environments. Pervasive and Mobile Computing. 3 (2), 117-157

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), 1206-1209

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), 1206-1209

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), 55-65

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), 309-334

HAGRAS, H., CALLAGHAN, V. and COLLEY, M., (2005). Intelligent embedded agents. Information Sciences. 171 (4), 289-292

Callaghan, V., Clarke, G., Colley, M., Hagras, H., Chin, JSY. and Doctor, F., (2004). Inhabited Intelligent Environments. BT Technology Journal. 22 (3), 233-247

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), 12-20

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鈥揋enetic system. Fuzzy Sets and Systems. 141 (1), 107-160

Hagras, HA., (2004). A Hierarchical Type-2 Fuzzy Logic Control Architecture for Autonomous Mobile Robots. IEEE Transactions on Fuzzy Systems. 12 (4), 524-539

Attallah, A., (2004). Utility of a novel HCV-NS4 antigen detection immunoassay for monitoring treatment of HCV-infected individuals with pegylated interferon 伪-2a. Hepatology Research. 28 (2), 68-72

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), 1635-1639

Hagras, H. and Sobh, T., (2002). Intelligent learning and control of autonomous robotic agents operating in unstructured environments. Information Sciences. 145 (1-2), 1-12

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), 37-52

Hagras, H., Callaghan, V. and Collry, M., (2001). Outdoor mobile robot learning and adaptation. IEEE Robotics & Automation Magazine. 8 (3), 53-69

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 Colley, M., (1999). An embedded鈥恆gent technique for industrial control environments where process modelling is difficult. Assembly Automation. 19 (4), 323-331

Books (4)

Mendel, JM., Hagras, H., Tan, W., Melek, WW. and Ying, H., (2014). . Wiley. 9781118278390

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

(2009). . Springer US. 9780387764849

Hassanien, A., Abawajy, JH., Abraham, A. and Hagras, H., (2009). . Springer. 9781848825987

Book chapters (28)

Bilgin, A., Hagras, H. and Wagner, C., (2016). . In: Next Generation Intelligent Environments. Editors: Ultes, S., Nothdurft, F., Heinroth, T. and Minker, W., . Springer. 165- 219. 978-3-319-23451-9

Starkey, AJ., Hagras, H., Shakya, S. and Owusu, G., (2016). . In: Research and Development in Intelligent Systems XXXIII Incorporating Applications and Innovations in Intelligent Systems XXIV. Editors: Bramer, M. and Petridis, M., . Springer. 253- 266. 978-3-319-47174-7

(2016). Introduction to type-2 fuzzy logic controllers. In: Intelligent Systems. 9781439802847

Hagras, H., (2016). Introduction to type-2 fuzzy logic controllers. In: Intelligent Systems

Kumbasar, T. and Hagras, H., (2015). Interval Type-2 Fuzzy PID Controllers. In: Springer Handbook of Computational Intelligence. Editors: . Springer Berlin Heidelberg. 285- 294. 9783662435045

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

Naim, S. and Hagras, H., (2015). A Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making. In: Studies in Big Data. Springer International Publishing. 123- 164. 9783319168289

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

Dooley, J., Hagras, H., Callaghan, V. and Henson, M., (2013). . In: Internet of Things and Inter-cooperative Computational Technologies for Collective Intelligence. Editors: Bessis, N., Xhafa, F., Varvarigou, D., Hill, R. and Li, M., . Springer. 321- 344. 978-3-642-34951-5

Lee, C-S., Wang, M-H., Su, M-K., Wu, M-H. and Hagras, H., (2013). . In: On the Power of Fuzzy Markup Language. Editors: Acampora, G., Loia, V., Lee, C-S. and Wang, M-H., . Springer. 169- 187. 978-3-642-35487-8

Wang, M-H., Lee, C-S., Chen, Z-W., Hagras, H., Kuo, S-E., Kuo, H-C. and Cheng, H-H., (2013). . In: On the Power of Fuzzy Markup Language. Editors: Acampora, G., Loia, V., Lee, C-S. and Wang, M-H., . Springer. 149- 168. 978-3-642-35487-8

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). . In: On the Power of Fuzzy Markup Language. Editors: Acampora, G., Loia, V., Lee, C-S. and Wang, M-H., . Springer. 133- 147. 978-3-642-35487-8

Shakya, S., Kassem, S., Mohamed, A., Hagras, H. and Owusu, G., (2013). . In: Transforming Field and Service Operations. Editors: . Springer Berlin Heidelberg. 101- 114. 9783642449697

Wagner, C. and Hagras, H., (2013). . In: Advances in Type-2 Fuzzy Sets and Systems. Editors: Sadeghian, A., Mendel, JM. and Tahayori, H., . Springer. 65- 80. 9781461466659

Hagras, H. and Wagner, C., (2011). . In: Next Generation Intelligent Environments: Ambient Adaptive Systems. Editors: Minker, W. and Heinroth, T., . Springer. 127- 151. 9781461412984

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

Hagras, H., (2011). Introduction to Type-2 Fuzzy Logic Controllers. In: The Industrial Electronics Handbook - Five Volume Set

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. Editors: Kameas, AD., Callaghan, V., Hagras, H. and Weber, M., . Springer. 41- 69. 9780387764849

Al-Jaljouli, R. and Abawajy, J., (2009). Agents Based e-Commerce and Securing Exchanged Information. In: Computer Communications and Networks. Editors: . Springer London. 383- 404. 9781848825987

Gulrez, T., Tognetti, A. and De Rossi, D., (2009). Sensorized Garment Augmented 3D Pervasive Virtual Reality System. In: Computer Communications and Networks. Editors: . Springer London. 97- 115. 9781848825987

Haghighi, PD., Gaber, MM., Krishnaswamy, S. and Zaslavsky, A., (2009). Situation-Aware Adaptive Processing (SAAP) of Data Streams. In: Computer Communications and Networks. Editors: . Springer London. 313- 338. 9781848825987

Peters, JF., Szturm, T., Borkowski, M., Lockery, D., Ramanna, S. and Shay, B., (2009). Wireless Adaptive Therapeutic TeleGaming in a Pervasive Computing Environment. In: Computer Communications and Networks. Editors: . Springer London. 3- 28. 9781848825987

Pinz贸n, C., De Paz, Y., Bajo, J., Abraham, A. and Corchado, JM., (2009). SiC: An Agent Based Architecture for Preventing and Detecting Attacks to Ubiquitous Databases. In: Computer Communications and Networks. Editors: . Springer London. 231- 258. 9781848825987

Peterson, N., Anusuya-Rangappa, L., Shirazi, BA., Song, W., Huang, R., Tran, D., Chien, S. and LaHusen, R., (2009). Volcano Monitoring: A Case Study in Pervasive Computing. In: Computer Communications and Networks. Editors: . Springer London. 201- 230. 9781848825987

Fleury, M., Jammeh, EA., Razavi, R. and Ghanbari, M., (2009). . In: Pervasive Computing: Innovations in Intelligent Multimedia and Applications. Editors: Hassanien, A., Abawajy, JH., Abraham, A. and Hagras, H., . Springer. 47- 75. 9781848825987

Duman, H., Hagras, H. and Callaghan, V., (2007). Adding Intelligence to Ubiquitous Computing Environments. In: Studies in Computational Intelligence. Editors: . Springer Berlin Heidelberg. 61- 102. 9783540731757

Hagras, H., (2006). Fuzzy Logic Based Control Mechanisms for Handling the Uncertainties Facing Mobile Robots in Changing Unstructured Environments. In: Advances in Industrial Control. Springer London. 175- 189. 9781846284687

Remagnino, P., Hagras, H., Monekosso, N. and Velastin, S., (2005). Ambient Intelligence. In: Ambient Intelligence. Springer New York. 1- 14. 9780387229904

Conferences (243)

Andreu, J., Deep Learning Towards Intelligent Vehicle Fault Diagnosis

Andreu, J., Privacy-Preserving Gesture Recognition with Explainable Type-2 Fuzzy Logic Based Systems

Maqsood, K., Hagras, H. and Zabet, NR., (2024). A Type-2 Fuzzy Logic-Based Explainable Artificial Intelligence for the Prediction of Enhancers

Bhatia, A. and Hagras, H., (2024). A Type-2 Fuzzy Time Series Classification System with Optimized Time Period Selection

Fumanal-Idocin, J., Bustince, H., Andreu-Perez, J. and Hagras, H., (2023). On the Stability of Fuzzy Classifiers to Noise Induction

Hagras, H., (2023). Towards True Explainable Artificial Intelligence for Real World Applications

Bhatia, A. and Hagras, H., (2022). A Time Series Based Explainable Interval Type-2 Fuzzy Logic System

Leon-Garza, H., Hagras, H., Pena-Rios, A., Bahceci, O. and Conway, A., (2022). A Hand-Gesture Recognition Based Interpretable Type-2 Fuzzy Rule-based System for Extended Reality

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

Leon-Garza, H., Hagras, H., Pena-Rios, A., Conway, A. and Owusu, G., (2021). An Interval Type-2 Fuzzy-based System to Create Building Information Management Models from 2D Floor Plan Images

Leon-Garza, H., Hagras, H., Pena-Rios, A., Conway, A. and Owusu, G., (2021). A Fuzzy Rule-based System using a Patch-based Approach for Semantic Segmentation in Floor Plans

Upasane, SJ., Hagras, H., Anisi, MH., Savill, S., Taylor, I. and Manousakis, K., (2021). A Big Bang-Big Crunch Type-2 Fuzzy Logic System for Explainable Predictive Maintenance

Beasley, L., Hagras, H., Conway, A. and Owusu, G., (2021). A Type-2 Fuzzy Based Multi-Objective Optimisation for Strategic Network Planning in the Telecommunication Domain

Veryard, L., Hagras, H., Conway, A. and Owusu, G., (2021). A Type-2 Fuzzy Multi-Objective Multi-Chromosomal Optimisation for Capacity Planning within Telecommunication Networks

Chimatapu, R., Hagras, H., Kern, M. and Owusu, G., (2021). Enhanced Deep Type-2 Fuzzy Logic System For Global Interpretability

Bhatia, A. and Hagras, H., (2021). Identifying and Rectifying Rational Gaps in Fuzzy Rule Based Systems for Regression Problems

(2021). [Front matter]

Chimatapu, R., Hagras, H., Kern, M. and Owusu, G., (2020). Hybrid Deep Learning Type-2 Fuzzy Logic Systems For Explainable AI

Kiani, M., Andreu-Perez, J., Hagras, H., Filippetti, ML. and Rigato, S., (2020).

Rozman, J., Hagras, H., Andreu-Perez, J., Clarke, D., Muller, B. and Data, SF., (2020).

Leon-Garza, H., Hagras, H., Pena-Rios, A., Conway, A. and Owusu, G., (2020). A Big Bang-Big Crunch Type-2 Fuzzy Logic System for Explainable Semantic Segmentation of Trees in Satellite Images using HSV Color Space

Adams, J. and Hagras, H., (2020). A Type-2 Fuzzy Logic Approach to Explainable AI for regulatory compliance, fair customer outcomes and market stability in the Global Financial Sector

Leon-Garza, H., Hagras, H., Pena-Rios, A., Owusu, G. and Conway, A., (2020). A Fuzzy Logic Based System for Cloud-based Building Information Modelling Rendering Optimization in Augmented Reality

Veryard, L., Hagras, H., Conway, A. and Owusu, G., (2020). A Type-2 Fuzzy Genetic Approach to Uncertain & Dynamic Resilient Routing within Telecommunications Networks

Pena-Rios, A., Oplatek, T., Hagras, H., Conway, A. and Owusu, G., (2020). Work-in-Progress鈥擬easuring Engagement in Virtual Reality for Talent Attraction Purposes

Al-Zeyadi, M., Andreu-Perez, J., Hagras, H., Royce, C., Smith, D., Rzonsowski, P. and Malik, A., (2020).

Pule, KE., Anisi, MH., Doctor, F. and Hagras, H., (2020). Multiple UAV based Spatio-Temporal Task Assignment using Fast Elitist Multi Objective Evolutionary Approaches

Steffens, A., Campello, A., Ravenscroft, J., Clark, A. and Hagras, H., (2019). Deep segmentation: Using deep convolutional networks for coral reef pixel-wise parsing

Veryard, L., Hagras, H., Starkey, A. and Owusu, G., (2019). A Fuzzy Genetic System for Resilient Routing in Uncertain & Dynamic Telecommunication Networks

Ferreyra, E., Hagras, H., Kern, M. and Owusu, G., (2019). Depicting Decision-Making: A Type-2 Fuzzy Logic Based Explainable Artificial Intelligence System for Goal-Driven Simulation in the Workforce Allocation Domain

Ferreyra, E., Hagras, H., Kern, M. and Owusu, G., (2019).

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

(2019). ICDS 2019 Preface

Clift, LG., Lepley, J., Hagras, H. and Clark, A., (2018).

Pena Rios, AC., Hagras, H., Owusu, G. and Gardner, M., (2018).

Kassa, DM. and Hagras, H., (2018). An Adaptive Segmentation Technique For the Ancient Ethiopian Ge鈥檈z Language Digital Manuscripts

Chimatapu, R., Hagras, H., Starkey, A. and Owusu, G., (2018). Stacked Auto Encoder Based Hybrid Genetic Algorithm for Workforce Optimization

Chimatapu, R., Hagras, H., Starkey, A. and Owusu, G., (2018). A Big-Bang Big-Crunch Type-2 Fuzzy Logic System for Generating Interpretable Models in Workforce Optimization

Chimatapu, R., Hagras, H., Starkey, A. and Owusu, G., (2018). Interval Type-2 Fuzzy Logic Based Stacked Autoencoder Deep Neural Network For Generating Explainable AI Models in Workforce Optimization

Chimatapu, R., Hagras, H., Starkey, A. and Owusu, G., (2018). Explainable AI and Fuzzy Logic Systems

Chimatapu, R., Hagras, H., Starkey, AJ. and Owusu, G., (2018). Enhancing Human Decision Making for Workforce Optimisation Using a Stacked Auto Encoder Based Hybrid Genetic Algorithm

Bhatia, A., Hagras, H. and Lepley, JJ., (2018). Machine Learning Approach to Extracting Emotions Information from Open Source Data for Relative Forecasting of Stock Prices

Ferreyra, E., Hagras, H., Kern, M. and Owusu, G., (2018). Improving Goal-Driven Simulation Performance Using Fuzzy Membership Correlation Analysis

Yusuf, HS. and Hagras, H., (2018). Towards Image Steganography Using Type-2 Fuzzy Logic and Edge Detection

Salih, A. and Hagras, H., (2018). Towards a Type-2 Fuzzy Logic Based System for Decision Support to Minimize Financial Default in Banking Sector

Saeed, SK. and Hagras, H., (2018). Adaptive Type-2 Fuzzy Logic Based System for Fraud Detection in Financial Applications

Mohammed, HA. and Hagras, H., (2018). Towards Developing Type 2 Fuzzy Logic Diet Recommendation System for Diabetes

Chekol, BE. and Hagras, H., (2018). Employing Machine Learning Techniques for the Malaria Epidemic Prediction in Ethiopia

Alhassan, MSE. and Hagras, H., (2018). Towards Congestion Control Approach Based on Weighted Random Early Detection and Type-2 Fuzzy Logic System

Yao, B., Hagras, H., Lepley, JJ., Peall, R. and Butler, M., (2017).

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

Pena-Rios, A., Hagras, H., Gardner, M. and Owusu, G., (2017). A fuzzy logic based system for geolocated augmented reality field service support

Pena Rios, A., Hagras, H., Gardner, M. and Owusu, G., (2017). A type-2 Fuzzy Logic based System for asset geolocation within augmented reality environments

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2017). Fuzzy dominance rules for real-world many objective optimization

Ferreyra, E., Hagras, H., Mohamed, A. and Owusu, G., (2017). A type-2 fuzzy logic system for engineers estimation in the workforce allocation domain

Ruiz, G., Pomares, H., Rojas, I. and Hagras, H., (2017). The non-singleton fuzzification operation for general forms of interval type-2 fuzzy logic systems

Song, W. and Hagras, H., (2017). A type-2 fuzzy logic system for event detection in soccer videos

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2016).

Yao, B., Lepley, JJ., Peall, R., Butler, M. and Hagras, H., (2016).

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2016). A many-objective genetic type-2 fuzzy logic system for the optimal allocation of mobile field engineers

Pena-Rios, A., Hagras, H., Gardner, M. and Owusu, G., (2016).

Song, W. and Hagras, H., (2016). A big-bang big-crunch fuzzy logic based system for sports video scene classification

Song, W. and Hagras, H., (2016). A big-bang big-crunch type-2 fuzzy logic based system for soccer video scene classification

Ruiz, G., Pomares, H., Rojas, I. and Hagras, H., (2016). Towards general forms of interval type-2 fuzzy logic systems

Bilgin, A., Hagras, H., Alghazzawi, D., Malibari, A. and Alhaddad, MJ., (2015).

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2015).

Almohammadi, K., Yao, B., Alzahrani, A., Hagras, H. and Alghazzawi, D., (2015).

Kumbasar, T. and Hagras, H., (2015).

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2015). A Genetic Algorithm Based Approach for Workforce Upskilling.

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2014).

Bilgin, A., Hagras, H., Upasane, S., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2014).

Almohammadi, K., Yao, B. and Hagras, H., (2014).

Sakalli, A., Kumbasar, T., Yesil, E. and Hagras, H., (2014).

Kumbasar, T., Ozturk, C., Yesil, E. and Hagras, H., (2014).

Mohamed, A., Hagras, H., Shakya, S., Liret, A., Dorne, R. and Owusu, G., (2014). Hierarchical Type-2 Fuzzy Logic Based Real Time Dynamic Operational Planning System.

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2013).

Bilgin, A., Hagras, H., Malibari, A., Alghazzawi, D. and Mohammed, J., (2013).

Bostanci, B., Hagras, H. and Dooley, J., (2013).

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2013).

Bernardo, D., Hagras, H. and Tsang, E., (2013).

Ghelli, A., Hagras, H. and Dooley, J., (2013).

Almohammadi, K. and Hagras, H., (2013).

Mohamed, A., Hagras, H., Liret, A., Shakya, S. and Owusu, G., (2013).

Mohamed, A., Hagras, H., Shakya, S. and Owusu, G., (2013).

Almohammadi, K. and Hagras, H., (2013). An adaptive fuzzy logic based system for improved knowledge delivery within intelligent E-Learning platforms

Naim, S., Hagras, H. and Bilgin, A., (2013).

Naim, S. and Hagras, H., (2013).

Torrejon, A., Callaghan, V. and Hagras, H., (2013).

Torrejon Alfonso, Callaghan Vic and Hagras Hani, (2013). Improving Communication and Presence in Online Telepresence Systems

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2013).

Kumbasar, T. and Hagras, H., (2013).

Kumbasar, T. and Hagras, H., (2013).

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

Bilgin, A., Dooley, J., Whittington, L., Hagras, H., Henson, M., Wagner, C., Malibari, A., Al-Ghamdi, A., Alhaddad, MJ. and Alghazzawi, D., (2012).

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2012).

Kassem, S., Hagras, H., Owusu, G. and Shakya, S., (2012).

Sahab, N. and Hagras, H., (2012).

Naim, S., Hagras, H. and Garibaldi, JM., (2012).

Naim, S. and Hagras, H., (2012).

Bernardo, D., Hagras, H. and Tsang, E., (2012). An interval type-2 Fuzzy Logic based system for model generation and summarization of arbitrage opportunities in stock markets

(2012). Autonomous and Intelligent Systems

Bernardo, D., Hagras, H. and Tsang, E., (2012). An Interval Type-2 Fuzzy Logic System for the Modeling and Prediction of Financial Applications

Mohamed, A., Hagras, H., Shakya, S. and Owusu, G., (2012). Tactical Resource Planner for Workforce Allocation in Telecommunications

Yao, B., Hagras, H., Ghazzawi, DA. and Alhaddad, MJ., (2012). An Interval Type-2 Fuzzy Logic System for Human Silhouette Extraction in Dynamic Environments

Huang, H-D., Lee, C-S., Hagras, H. and Kao, H-Y., (2012).

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2012). A general type-2 fuzzy logic approach for adaptive modeling of perceptions for Computing With Words

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

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

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

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.

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

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

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

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

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.

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

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

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

Lanza-Guti茅rrez, JM., Pulido, JAG., Vega-Rodr铆guez, MA. and S谩nchez-P茅rez, 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.

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.

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

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

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

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

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

Ros, M., Delgado, M., Vila, A., Hagras, H. and Bilgin, A., (2012).

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.

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

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.

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

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

Garcia-Valverde, T., Garcia-Sola, A., Gomez-Skarmeta, A., Botia, JA., Hagras, H., Dooley, J. and Callaghan, V., (2012).

Yao, B., Hagras, H., Ghanbari, M., Alhaddad, M. and Alghazzawi, D., (2012). Type-2 Fuzzy Logic Approach for Detecting Human Related Events in Videos

Wagner, C. and Hagras, H., (2011).

Hagras, H., (2011).

Dooley James, Callaghan Vic, Hagras Hani, Gardner Michael, Ghanbari Mohammed and Al-Ghazzawi Daniyal, (2011).

Sahab, N. and Hagras, H., (2011).

Wagner, C. and Hagras, H., (2011).

Sahab, N. and Hagras, H., (2011).

Almehdar, M. and Hagras, H., (2011).

Dooley, J., Wagner, C., Hagras, H. and Pruvost, G., (2011).

Cara, AB., Rojas, I., Pomares, H., Wagner, C. and Hagras, H., (2011).

Lee, C-S., Wang, M-H., Chen, Y-J. and Hagras, H., (2011).

Dooley, J., Henson, M., Callaghan, V., Hagras, H., Al-Ghazzawi, D., Malibari, A., Al-Haddad, M. and Al-Ghamdi, AA-M., (2011).

Helal, S., Lee, JW., Hossain, S., Kim, E., Hagras, H. and Cook, D., (2011).

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).

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

Wagner, C. and Hagras, H., (2010). An approach for the generation and adaptation of zSlices based general type-2 fuzzy sets from interval type-2 fuzzy sets to model agreement with application to Intelligent Environments

Wagner, C. and Hagras, H., (2010).

Almehdar, M. and Hagras, H., (2010).

Zaher, M. and Hagras, H., (2010).

Zaher, M., Hagras, H., Khairy, A. and Ibrahim, M., (2010).

Ibrahim, M., Khairy, A., Hagras, H. and Zaher, M., (2010).

Hagras, H., Ramadan, R., Nawito, M., Gabr, H., Zaher, M. and Fahmy, H., (2010).

Elfaham, A., Hagras, H., Helal, S., Hossain, S., Lee, JW. and Cook, D., (2010).

Ramadan, RA., Hagras, H., Nawito, M., Faham, AE. and Eldesouky, B., (2010).

Dooley, J., Callaghan, V., Hagras, H. and Bull, P., (2010).

Dooley, J., Davies, M., Ball, M., Callaghan, V., Hagras, H., Colley, MJ. and Gardner, M., (2010).

Wagner, C. and Hagras, H., (2010).

(2010). [Front matter]

Wagner, C. and Hagras, H., (2010).

Sahab, N. and Hagras, H., (2010).

Azouz, M., Shaltout, A., Elshafei, MAL., Abdel-Rahim, M., Hagras, H., Zaher, M. and Ibrahim, M., (2010).

Ibrahim, M., Khairy, A., Hagras, H., Zaher, M., El Shafei, A., Shaltout, A. and Rehim, NA., (2010).

Dooley, J., Callaghan, V., Hagras, H. and Bull, P., (2009).

Dooley James, Callaghan Vic, Hagras Hani and Bull Phil, (2009). Discovering the Home

Wagner, C. and Hagras, H., (2009). zSlices based general type-2 FLC for the control of autonomous mobile robots in real world environments

Wagner, C. and Hagras, H., (2009).

Doctor, F., Hagras, H., Roberts, D. and Callaghan, V., (2009).

Doctor, F., Hagras, H., Roberts, D. and Callaghan, V., (2009).

Kameas, AD., Goumopoulos, C., Hagras, H., Callaghan, V., Heinroth, T. and Weber, M., (2009).

Lee, C-S., Wang, M-H., Hsu, C-Y. and Hagras, H., (2009).

Kameas, A., Goumopoulos, C., Hagras, H., Gardner, M., Heinroth, T., Minker, W., Meliones, A., Economou, D., Bellik, Y. and Pruvost, G., (2009).

Elkasrawy Sarah, Hagras Hani and Nawito Moustafa, (2009).

Elfaham Amr and Hagras Hani, (2009).

El-Desouky Bahaa and Hagras Hani, (2009).

Mowafey Sherief, Schmitt Alexander, Hagras Hani and Minker Wolfgang, (2009).

Bellik, Y., Kameas, A., Goumopoulos, C., Hagras, H., Heinroth, T., Pruvost, G., Meliones, A., Economou, D., Minker, W. and Gardner, M., (2009).

Heinroth, T., Kameas, A., Hagras, H. and Bellik, Y., (2009).

(2009). [Front matter]

Wagner, C. and Hagras, H., (2009).

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

Wagner, C. and Hagras, H., (2008).

Doctor, F., Hagras, H., Roberts, D. and Callaghan, V., (2008).

Hagras, H., (2008).

Hagras, H., (2008).

Hagras, H., Packharn, I., Vanderstockt, Y., McNulty, N., Vadher, A. and Doctor, F., (2008).

Goumopoulos, C., Kameas, A., Hagras, H., Callaghan, V., Gardner, M., Minker, W., Weber, Bellik, Y. and Meliones, A., (2008).

Jammeh, E., Fleury, M., Wagner, C., Hagras, H. and Ghanbari, M., (2008).

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

Wagner, C. and Hagras, H., (2007). Evolving Type-2 Fuzzy Logic Controllers for 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

Lynch, C., Hagras, H. and Callaghan, V., (2007).

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). Automated Discovery of Human Activities inside Pervasive Living Spaces

Lynch, C., Hagras, H. and Callaghan, V., (2006). Using Uncertainty Bounds in the Design of an Embedded Real-Time Type-2 Neuro-Fuzzy Speed Controller for Marine Diesel Engines

Hagras, H., Doctor, F., Lopez, A. and Callaghan, V., (2006). Evolving Type-2 Fuzzy Agents for Ambient Intelligent Environments

Tawil, E. and Hagras, H., (2006). An Adaptive Genetic-Based Architecture for the On-line Co-ordination of Fuzzy Embedded Agents with Multiple Objectives and Constraints

Doctor, F., Hagras, H. and Callaghan, V., (2006). Life Long Learning Approach for Type-2 Fuzzy Embedded Agents in Ambient Intelligent Environments

Hagras, H., Colley, M., Pounds-Cornish, A., De Souza, G., Callaghan, V., Nikiforidis, G., Argyropoulos, C., Kameas, A. and Murphy, F., (2006). A Collaborating Team of Spiking Neural Network Based Robotic Agents for Inaccessible Fluidic 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).

Chin, JSY., Callaghan, LV., Clarke, G., Hagras, H. and Colley, M., (2005). End-user programming in pervasive computing environments

Lynch, C., Hagras, H. and Callaghan, V., (2005). Embedded type-2 FLC for real-time speed control of marine & traction 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

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

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

Tawil, E. and Hagras, H., (2004). A novel multi-objective multi-constraint genetic algorithms approach for Co-ordinating embedded agents

Doctor, F., Hagras, H. and Callaghan, V., (2004). A type-2 fuzzy embedded agent for ubiquitous computing environments

Doctor, F., Hagras, H., Callaghan, V. and Lopez, A., (2004). An adaptive fuzzy learning mechanism for intelligent agents in ubiquitous computing environments

Hagras, H., (2004). A type-2 fuzzy logic controller for autonomous mobile robots

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

Colley, M., de Souza, G., Hagras, H., Pounds-Cornish, A., Clarke, G. and Callaghan, V., (2004). Towards developing micro-scale robots for inaccessible fluidic environments

Rivera-Illingworth, F., Callaghan, V. and Hagras, H., (2004). A counectionist embeddled agent approach for abnormal behaviour detection in intelligent health care environments

Hagras, H., Pounds-Cornish, A., Colley, M., Callaghan, V. and Clarke, G., (2004). Evolving spiking neural network controllers for autonomous robots

Lopez, A., Sanchez, L., Doctor, F., Hagras, H. and Callaghan, V., (2004). An evolutionary algorithm for the off-line data driven generation of fuzzy controllers for intelligent buildings

Bellis, S., Razeeb, KM., Saha, C., Delaney, K., O'Mathuna, C., Pounds-Cornish, A., de Souza, G., Colley, M., Hagras, H., Clarke, G., Callaghan, V., Argyropoulos, C., Karistianos, C. and Nikiforidis, G., (2004). FPGA implementation of spiking neural networks - an initial step towards building tangible collaborative autonomous agents

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., (2003). A hierarchical fuzzy鈥揼enetic multi-agent architecture for intelligent buildings online learning, adaptation and control

Hagras, H., Colley, M., Callaghan, V., Clarke, G., Duman, H. and Holmes, A., (2002). A fuzzy incremental synchronous learning technique for embedded-agents learning and control in intelligent inhabited environments

Hagras, H., Colley, M. and Callaghan, V., (2001). Life long learning and adaptation for embedded agents operating in unstructured 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., (2000). Online learning of the sensors fuzzy membership functions in autonomous mobile robots

Hagras, H., Callaghan, V. and Colley, M., (2000). Online learning of fuzzy behaviour co-ordination for autonomous agents using genetic algorithms & real-time interaction with the environment

Hagras, H., Callaghan, V., Colley, M. and Carr-West, M., (1999). Fuzzy-genetic based embedded-agent approach to learning & control in agricultural autonomous vehicles

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, MJ. and Carr-West, M., (1999). Developing an Outdoor Fuzzy Logic Controlled Agricultural Vehicle for Crop Following and Harvesting.

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

Patents (1)

DiCairano-Gilfedder, C., Pena Rios, A., Hagras, H. and Owusu, G., Method and apparatus for retrieving a data package

Grants and funding

2024

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)

2019

Aquatronic Group KTP

Innovate UK (formerly Technology Strategy Board)

PhD studentships with BT and DARO. 3 Overseas students.

British Telecommunications Plc

2018

Flakt Woods Ltd is the group Centre of Excellence for the design, development, manufacture, marketing and distribution of axial flow fans.

Innovate UK (formerly Technology Stategy Board)

Plextek KTP Mar 18

Innovate UK (formerly Technology Stategy Board)

BT Car Sharing Scheme optimisation and AR for training

British Telecommunications Plc

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 Strategy Board)

Flakt Woods Ltd is the group Centre of Excellence for the design, development, manufacture, marketing and distribution of axial flow fans.

Flakt Woods

Cognitran KTP 03/18

Innovate UK (formerly Technology Strategy Board)

2017

BT Car Sharing Scheme optimisation and AR for training

DARO (糖心Vlog)

Visual classification & tagging, and delivering this ability into the hands of the domain experts.

Innovate UK (formerly Technology Strategy Board)

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

Scaling Intelligent Environments

King Abdulaziz University

Contact

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

Location:

5B.524, Colchester Campus

Academic support hours:

Thursdays 11am-1pm

More about me