Biography
Dr Malik Haddad is an Assistant Professor in Data and Computer Science in the Centre for Apprenticeships at Northeastern University London, the Artificial Intelligence and Data Science Level 7 and the Data Science Level 6 Programme Leader
Dr Haddad received a BSc in Electronic Engineering in 2006. He went on to postgraduate study and was awarded a distinction in MSc in Electrical and Computer Engineering in 2007. Finally, he completed a PhD in Intelligent Decision Making applied to Management and Engineering in 2019.
Dr Haddad is a Fellow – HEA, a certified Project Manager Professional – PMI, a Chartered Engineer (CEng) – IET and a Senior Member of the IEEE.
Research
Dr Haddad current research interests include intelligent decision making and Multiple Criteria Decision Making, assistive technologies, robotics and obstacle avoidance, AI and machine learning, Intelligent Systems and HMI.
Selected Publications
Haddad, M. and Sanders, D. 2024. A hybrid approach to evaluate employee performance using MCDA and artificial neural networks. International Journal of Management and Decision Making. In press.
Gharavi, A., Abbas, K. A., Hassan, M. G., Haddad, M., Ghoochaninejad, H., Alasmar, R., Al-Saegh, S., et al. 2023. Unconventional Reservoir Characterization and Formation Evaluation: A Case Study of a Tight Sandstone Reservoir in West Africa. Energies, 16(22), 7572. MDPI AG.
Sanders, D., Tewkesbury, G., Haddad, M., Kyberd, P., Zhou, S. and Langner, M., 2022, April. Control of a semi-autonomous powered wheelchair. In Journal of Physics: Conference Series (Vol. 2224, No. 1, p. 012098). IOP Publishing.
Haddad M., Sanders D., Tewkesbury G., Langner M. and Keeble W. (2022). A New Collision Avoidance System for Smart Wheelchairs Using Deep Learning. In Proceedings of the 3rd International Symposium on Automation, Information and Computing – Volume 1: ISAIC.
Koklu, U., Morkavuk, S., Featherston, C., Haddad, M., Sanders, D., Aamir, M., Pimenov, D.Y. and Giasin, K., 2021. The effect of cryogenic machining of S2 glass fibre composite on the hole form and dimensional tolerances. International Journal of Advanced Manufacturing Technology 115, pp. 125-140.
Haddad, M., Sanders, D. and Tewkesbury, G., 2020. Selecting a discrete multiple criteria decision making method for Boeing to rank four global market regions. Transportation Research Part A: Policy and Practice, 134, pp.1-15.
Haddad, M.J. and Sanders, D.A., 2020. Deep Learning architecture to assist with steering a powered wheelchair. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(12), pp.2987-2994.
Haddad, M. and Sanders, D., 2020. Artificial Neural Network approach for business decision making applied to a corporate relocation problem. Archives of Business Research. 8(6), pp180-195.
Haddad, M. and Sanders, D., 2019. Selecting a best compromise direction for a powered wheelchair using PROMETHEE. IEEE Trans Neural Syst Rehabil Eng. 27(2), pp 228-235.
Haddad, M. and Sanders, D., 2018. Selection of discrete multiple criteria decision making methods in the presence of risk and uncertainty. Operations Research Perspectives, 5, pp.357-370.
Teaching
Dr Haddad is teaching Bachelor’s and Master’s courses at the Centre for Apprenticeships in the Faculty of Computing, Mathematics, Engineering, and Natural Sciences. His teaching focuses on AI, Data Science and Machine Learning.
Courses Dr Haddad leads at Northeastern University London:
- AI Capstone Project and EPA
- Data Science Synoptic Project and EPA
- Data Engineering
- Predictive Analytics using Python
- Data Synthesis
Contact
Malik Haddad
malik.haddad@nulondon.ac.uk