Ahmad Lotfi is a Professor of Computational Intelligence and Head of Department of Computing and Technology at Nottingham Trent University, where he is also leading Computational Intelligence and Applications (CIA) research group. He is also a Visiting Professor at Tokyo Metropolitan University.
Professor Ahmad Lotfi received his BSc. and MTech. in control systems from Isfahan University of Technology, Iran and Indian Institute of Technology, India respectively. He received his PhD degree in Learning Fuzzy Systems from University of Queensland, Australia in 1995.
Professor Ahmad Lotfi joined Nottingham Trent University in December 2000 as a lecturer and was promoted to a Reader and Professor in 2011 and 2015 respectively. He has acted as the Postgraduate Research Tutor for SST from 2007 until 2019. He also leads the Computational Intelligence and Applications research group.
More information about Professor Lotfi's research and teachings are available from his personal page.
Professor Ahmad Lotfi's research interest is mainly in the area of computational intelligence, ambient intelligence, robotics and machine learning. Specific areas of interest include learning fuzzy systems, evolutionary fuzzy systems, neuro computing, data mining, sensors network, smart homes, intelligent environments and intelligent mobile robot navigation strategies.
His works have been recognised internationally for significant contributions to the application of computational intelligence techniques in condition monitoring, control systems and intelligent environments. My strong communications and decision-making skills with a “make-it-happen” capability have helped me to meet targeted research objectives. Furthermore, my extensive background in the supervision and teaching of undergraduate and research students and the development of research programs in the theory and application of computational intelligence has helped me to contribute to the field of research.
His current research focuses on the identification of progressive changes in behaviour of elderly people suffering from Dementia or any other cognitive impairments. Accurate identification of progressive changes through utilisation of unobtrusive sensor network and/or robotics platform will enable carers (formal and informal) to intervene when deemed necessary.
Opportunities to carry out postgraduate research towards an MPhil /PhD exist in all of the areas identified above. Further information may be obtained from the NTU Doctoral School.
- Proposal Evaluator and Panel Member for Horizon 2020; SCI-PM-15-2017: Personalised coaching for well-being and care of people as they age.
- Member of EPSRC Peer Review College (2016)
- Expert Evaluator for EU Framework Research Programmes, Decrease of cognitive decline, malnutrition and sedentariness by elderly empowerment in lifestyle management and social inclusion, 2014.
- Member of IEEE Computational Intelligence Society (CIS), Emergent Technologies Technical Committee (ETTC). The committee identifies, promotes, and nurtures new and emergent approaches, concepts, and areas that relate or are within the scope of the CIS.
- Chair of the organising committee, UKCI2018, Nottingham, 5-7 September 2018.
- Chair of the Smart Industry Workshop 2019, Nottingham, 9-11 January 2019.
- Member of the organising committee and program committee chair, The PErvasive Technologies Related to Assistive Environments (PETRA) conference, Rhodes, 5-7 June 2019.
- Member of the organising committee and programme chair, UKRAS19: Robotics and Autonomous Systems Conference, Loughborough, Jan 24th 2019.
- Member of the editorial board and Associate Editor, Soft Computing (Springer) [IF:1.3] [2012 – Present]
- Member of the editorial board, Journal of Ambient Intelligence and Smart Environments [IF: 1.1][2013 – Present]
- Editorial Board of International Journal of Computational Intelligence.
Research Students Supervision and Examination
- PhD supervision of 17 PhD students to successful completion. There are currently 10 PhD students under supervision.
- Acted as the PhD external examiner for 15 and internal examiner for over 10 candidates.
Sponsors and collaborators
Current and recent research is being conducted with the collaboration, funding and/or support of:
- Alcuris Ltd.
- Engineering and Physical Sciences Research Council
- Innovate UK
- Just Checking Ltd.
- Knowledge Transfer Partnerships
- Nottingham City Homes Ltd.
- Tunstall Healthcare (UK) Ltd.
Recent research funding includes:
- Community-centric system for elderly care and information support (IEC\R3\170114) Funded by The Royal Society - (£12,000)[2018-2020]
- TekChef (74559-501461)(£276,910) funded by Innovate UK [2017-2018] (Principal Investigator)
- iCarer (AAL-2012-5-239) (£254,624 [€318,281]) funded jointly by Innovate UK and EPSRC [2013-2016] (Principal Investigator)
- Nottingham City Homes (SKTP-100712) (£48,450) funded by Technology Strategy Board [2012-2013] (Principal Investigator)
ALRAWAHI, A.S., LEE, K. and LOTFI, A., 2019. A multiobjective QoS model for trading Cloud of Things resources. IEEE Internet of Things Journal, Volume: 6 , Issue: 6 (IF: 9.5)
YAHAYA, S.W., LOTFI, A. and MAHMUD, M., 2019. A consensus novelty detection ensemble approach for anomaly detection in activities of daily living. Applied Soft Computing, 83: 105613. (IF: 4.9)
ORTEGA ANDEREZ, D., LOTFI, A. and POURABDOLLAH, A., 2019. Eating and drinking gesture spotting and recognition using a novel adaptive segmentation technique and a gesture discrepancy measure. Expert Systems with Applications. (IF: 4.3)
HOWEDI, A., LOTFI, A. and POURABDOLLAH, A., 2019. Exploring entropy measurements to identify multi-occupancy in activities of daily living. Entropy, 21 (4): 416. (IF: 2.4)
ELBAYOUDI, A., LOTFI, A. and LANGENSIEPEN, C., 2019. The human behaviour indicator: a measure of behavioural evolution. Expert Systems with Applications, 118, pp. 493-505. (IF: 4.3)
CANT, R., REMI-OMOSOWON, A., LANGENSIEPEN, C. and LOTFI, A., 2018. An entropy-guided Monte Carlo tree search approach for generating optimal container loading layouts. Entropy, 20 (11): 866. (IF: 2.4)
ORTEGA-ANDEREZ, D., LOTFI, A., LANGENSIEPEN, C. and APPIAH, K., 2018. A multi-level refinement approach towards the classification of quotidian activities using accelerometer data. Journal of Ambient Intelligence and Humanized Computing. (IF: 1.9)
ADAMA, D.A., LOTFI, A., LANGENSIEPEN, C., LEE, K. and TRINDADE, P., 2018. Human activity learning for assistive robotics using a classifier ensemble. Soft Computing: Vol.22, Issue 21, pp 7027–7039. (IF: 2.8)
LOTFI, A., ALBAWENDI, S., POWELL, H., APPIAH, K. and LANGENSIEPEN, C., 2018. Supporting independent living for older adults; employing a visual based fall detection through analysing the motion and shape of the human body. IEEE Access, 6, pp. 70272-70282. (IF:4.1)See all of Ahmad Lotfi's publications...
Professor Lotfi is able to talk to the press regarding the following:
- Assistive technology
- Smart devices
- Smart city
- Assistive robots
- Ambient assisted living
- Dementia and assistive technologies
- Intelligent environments
- Artificial intelligence
- Computational intelligence
- Machine learning