Dr. Zainab Hamid
Postdoctoral Researcher (WP2, Digital Innovations)
Lahore University of Management Sciences (LUMS)
Dr. Zainab is a postdoctoral researcher in the Center for Water Informatics & Technology (WIT), LUMS. She received her Ph.D. from the Department of Mechatronics Engineering at the University of Engineering and Technology (UET), Pakistan, in 2025 and M.S. in Electrical Engineering from the Department of Electrical and Computer Engineering at COMSATS University, Lahore, Pakistan, in 2018. She has worked at the Human-Centered Robotics Lab (HCRL) at UET, funded by the Ministry of Science and Technology, Pakistan, from 2018 to 2020. She has served as a faculty member in the Department of Mechatronics Engineering at UET, Pakistan from 2019 to 2023. Her research interests include machine learning, intelligent systems, learning-based control schemes, sliding mode control, and fault-tolerant control for aircraft.
Research interests
- Precision agriculture
- Deep learning model analysis
- UAV modelling and design
- Learning based control
Work experience and education
Jan 2026 - Present
Postdoctoral Researcher, Centre for Water Informatics & Technology (WIT), LUMS Lahore, Pakistan
2023-2025
Machine Learning Developer, CodeViz Technologies, Lahore, Pakista
2019-2023
Lecturer, Department of Mechatronics Engineering, UET Lahore, Pakistan
2018
Lab Engineer, COMSATS University Islamabad (CUI) Lahore Campus, Pakistan
2018 - 2025
Ph.D. Mechatronics & Control Engineering, University of Engineering & Technology (UET), Lahore, Pakistan
2016 - 2018
M.S. Electrical Engineering, COMSATS University Lahore, Pakistan
2007 - 2011
B.Sc. Mechatronics & Control Engineering, University of Engineering & Technology, Lahore, Pakistan
Peer-reviewed publications
Mofid, O., Akhtar, Z., Mobayen, S. and Khodayar, M., 2025. Adaptive neural network-based super-twisting sliding mode control for UAV trajectory tracking under disturbances. ISA transactions.
Akhtar, Z., Naqvi, S.Z.A., Hamayun, M.T. and Ijaz, S., 2024. A multilayer neural‐network‐based fault estimation and fault tolerant control scheme for uncertain system. International Journal of Robust and Nonlinear Control, 34(18), pp.11985-12011.
Akhtar, Z., Naqvi, S.A.Z., Khan, Y.A., Hamayun, M.T. and Ijaz, S., 2024. Design and experimental validation of an adaptive multi-layer neural network observer-based fast terminal sliding mode control for quadrotor system. Aerospace, 11(10), p.788.
Akhtar, Z., Naqvi, S.A.Z., Hamayun, M.T., Ahsan, M., Nadeem, A., Muyeen, S.M. and Oshnoei, A., 2024. Incorporation of robust sliding mode control and adaptive multi-layer neural network-based observer for unmanned aerial vehicles. IEEE Access, 12, pp.98107-98120.
Conference papers
Akhtar, Z. and Ijaz, S., 2025, April. An Adaptive Neural Network-Based Fixed Allocation Scheme for a UAV Octorotor. In 2025 11th International Conference on Control, Automation and Robotics (ICCAR) (pp. 277-282). IEEE.
Akhtar, Z., Nisar, A. and Hamayun, M.T., 2019, January. Nonlinear sliding mode state estimation techniques for UAV application. In 2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST) (pp. 508-514). IEEE.
Javaid, U., Ijaz, S., Akhtar, Z. and Basin, M., 2025, October. A Composite Nonlinear Fault Tolerant Control Scheme for Octorotor UAV System. In IECON 2025–51st Annual Conference of the IEEE Industrial Electronics Society (pp. 1-6). IEEE.
Nadeem, A., Zheng, Y., Kulkarni, A., Oshnoei, A., Teodorescu, R. and Akhtar, Z., 2025, July. Temperature-Dependent Impedance Characterization of Lithium-Ion NMC Cells at Different SOH Levels. In 2025 International Conference on Electrical Engineering, Automation and Information Science (EEAIS) (pp. 313-318). IEEE.