Professor Hani Hagras

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Email
hani@essex.ac.uk -
Telephone
+44 (0) 1206 873601
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Location
5B.524, Colchester Campus
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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
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PhD, Computer Science 糖心Vlog, (2000)
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Msc in Electrical Engineering University of Alexandria, (1996)
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Bsc in Electrical Engineering University of Alexandria, (1994)
Appointments
糖心Vlog
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Director of Impact, School of Computer Science and Electronic Engineering, 糖心Vlog (1/7/2021 - present)
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Director of Research, School of Computer Science and Electronic Engineering, 糖心Vlog (1/7/2017 - 1/7/2021)
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Head of the Artificial Intelligence Research Group, School of Computer Science and Electronic Engineering, 糖心Vlog (1/6/2019 - present)
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Director of the Computational Intelligence Centre, School of Computer Science and Electronic Engineering, 糖心Vlog (10/9/2007 - present)
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Director Impact, School of Computer Science and Electronic Engineering, 糖心Vlog (1/10/2015 - 1/7/2017)
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Senior Lecturer (Associate Professor), Department of Computer Science, 糖心Vlog (1/8/2003 - 1/6/2006)
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Lecturer (Assistant Professor), Department of Computer Science, 糖心Vlog (1/1/2001 - 1/8/2003)
Other academic
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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 )
Explainable Artificial Intelligence (XAI)
Current research
Robotics and Intelligent Control
Explainable Artificial Intelligence (XAI)
Data Science
Teaching and supervision
Current teaching responsibilities
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Intelligent Systems and Robotics (CE801)
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Neural Networks and Deep Learning (CE889)
Current supervision
Previous supervision

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 20/2/2024

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 3/1/2024

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 6/11/2023

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 13/7/2023

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 16/9/2022

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 6/7/2022

Degree subject: Biological Sciences
Degree type: Doctor of Philosophy
Awarded date: 11/4/2022

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 21/7/2021

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 23/3/2021

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 14/2/2019

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 7/3/2018

Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 3/7/2017

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 7/7/2016

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 22/10/2015

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 1/7/2015

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 13/3/2015

Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 3/12/2014

Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 3/3/2014

Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 21/1/2013

Degree subject: Computer Science
Degree type: Master of Science (by Dissertation)
Awarded date: 4/5/2012

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
Academic support hours:
Thursdays 11am-1pm