Mr Abdullah Alsalemi

Job: PhD student

Faculty: Computing, Engineering and Media

School/department: School of Computer Science and Informatics

Research group(s): Institute of Artificial Intelligence (IAI)

Address: De Montfort University, The Gateway, Leicester, LE1 9BH

T: N/A



Personal profile

Abdullah Alsalemi received the B.Sc. degree in electrical engineering from Qatar University. From June 2016 to May 2017, he worked at the Qatar Mobility Innovations Center (QMIC) as an intern Mobile Application Developer and as a Research Assistant at the Department of Electrical Engineering in Qatar University from 2018 to 2020. He is currently a PhD student at De Montfort University. He has authored over 44 research papers in refereed journals and international conference proceedings. His current research interests include energy saving behavior, internet of energy (IoE) and medical simulator design.

Research group affiliations

Publications and outputs

Recent publications

  • A. Alsalemi et al., “A Micro-Moment System for Domestic Energy Efficiency Analysis,” IEEE SystemsJournal, vol. 15, no. 1, pp. 1256–1263, Mar. 2021, doi:10.1109/JSYST.2020.2997773.
  • A. Alsalemi et al., “Achieving Domestic Energy Recent publications Efficiency Using Micro-Moments and Intelligent Recommendations,” IEEE Access, vol. 8, pp. 15047–15055, 2020, doi: 10.1109/ACCESS.2020.2966640.
  • A. Alsalemi, F. Bensaali, A. Amira, N. Fetais, C.Sardianos, and I. Varlamis, “Smart Energy Usage and Visualization Based on Micro-moments,” in Intelligent Systems and Applications, Cham, 2020, pp. 557–566,doi: 10.1007/978-3-030-29513-4_41.
  • A. Alsalemi, C. Sardianos, F. Bensaali, I. Varlamis,A. Amira, and G. Dimitrakopoulos, “The Role of Micro-Moments: A Survey of Habitual Behavior Change and Recommender Systems for Energy Saving,” IEEE Systems Journal, vol. 13, no. 3, pp.3376–3387, Sep. 2019, doi:10.1109/JSYST.2019.2899832.
  • A. Alsalemi et al., “Endorsing domestic energysaving behavior using micro-moment classification,”Applied Energy, vol. 250, pp. 1302–1311, Sep. 2019,doi: 10.1016/j.apenergy.2019.05.089.
  • A. Alsalemi et al., “Using Thermochromic Ink for Blood Simulation in Medical Training,”WO/2019/159051, 22-Aug-2019.
  • A. Alsalemi et al., “Using thermochromic ink for blood simulation in medical training, US20190251869A1, 15-Aug-2019. 

Research interests/expertise

Edge Artificial Intelligence-Internet of Energy (IoE)- Energy Saving Behavior- Medical Simulator Design 


B.Sc. Electrical Engineering

Honours and awards

  • Best Student Paper Award (co-author) for paper entitled Energy Data Visualizations on Smartphones for Triggering Behavioral Change: Novel vs. Conventional,IEEE 2nd Global Power, Energy and Communication Conference 2020 (GPECOM2020)

  • Best Oral Presentation Award for abstract entitled Towards Domestic Energy Efficiency: Using Micro-Moments for Personalized Behavior Change Recommendations, 8th Global Conference on Global Warming (GCGW-2019).

  • 1st Place 11th QNRF UREP Competition 2019 (UREP19-062-2-026).

  • Best Poster Presentation Award for abstract entitled Using Thermochromic Ink for Medical Simulations, ELSO-SWAC 2017.

  • Best Oral Presentation Award for abstract entitled Design and Implementation of a Modular ECMO Simulator, ELSO-SWAC 2017.

  • 1st Place for Best Project in Qatar University Honors Program Project Fair 2017.

  • 1st Place for Best Electrical Engineering Senior Design Project in Qatar University College of Engineering Senior Design Contest 2017.

PhD project


Achieving Domestic Energy Efficiency using Micro-Moments and Behavioural Economics-BasedRecommender Systems


Domestic consumer behaviour is a critical driver of energy use, igniting innovations that analyse and help establish energy-efficient behaviour. The most critical step is therefore the understanding of that behaviour by collecting and analysing comprehensive information. This does not only require financial and technological resources, but a strong understanding of human behaviour and motivation, i.e., the study of behavioural economics. Therefore, in this research, we tackle this very endeavour by utilising innovative artificial intelligence(AI) techniques to automatically process end-user information on consumption behaviour, decern outliers,and generate personalised recommendations to resolve energy wastage issues.Another critical building block is the concept of micromoments,defined as short, contextual events,comprising a specific end-user behaviour. Adopted to the energy context, micro-moments represent an informational building block of a consumption action and can be considered as the missing link between behavioural economics and artificial intelligence systems. In terms of impact, urban living standards can significantly benefit from the outcomes and tools of such innovations, in addition to, the immense social value gained from utilising recommender systems in reducing energy consumption to the convenient minimum. To conclude, vast positive impact can be created when innovation meets technology, in other words, when behavioural economics, micro-moments, recommenders combined to foster transforming the epicentre of energy efficiency challenges: the behaviour of individuals.

Name of supervisor(s)

Prof. Abbes Amira, Dr. Hossein Malekmohamadi, Dr.Kegong Diao, and Prof. Faycal Bensaali (Qatar University)