Jingjing Jiang | Robotics and Automation | Best Researcher Award

Published on by Popular Engineer

Dr. Jingjing Jiang | Robotics and Automation | Best Researcher Award

Loughborough University | United Kingdom

Dr Jingjing Jiang is a distinguished researcher in intelligent mobility and autonomous systems, currently a Senior Lecturer in Intelligent Mobility and Autonomous Vehicles at the Department of Aeronautical and Automotive Engineering, Loughborough University. She holds a BE in Electronic and Electrical Engineering an MSc in Control Engineering , and a PhD in Control Engineering (Imperial College London,  thesis: Shared Control for Systems with Constraints). After her doctoral work she served as a Research Associate in the Department of Electrical and Electronic Engineering at Imperial College London before joining Loughborough University as Lecturer in 2018 and being promoted to Senior Lecturer. Her research interest spans trustworthy control design and rigorous closed-loop performance analysis for intelligent systems and autonomous vehicles, combining classical control theory with modern data-driven models and algorithms, and emphasising both trial-based validation and top-down safety and reliability guarantees. Her work has been recognised for bridging fundamental research and real-world application in mobility systems. She continues to drive innovation in autonomous mobility and system safety, contributing to the future of reliable intelligent transport.

Profiles : Google Scholar | Orcid

Featured Publications

Cao, S., Sun, L., Jiang, J., & Zuo, Z. (2021). Reinforcement learning-based fixed-time trajectory tracking control for uncertain robotic manipulators with input saturation. IEEE Transactions on Neural Networks and Learning Systems, 34(8), 4584–4595.

Jiang, J., & Astolfi, A. (2018). Lateral control of an autonomous vehicle. IEEE Transactions on Intelligent Vehicles, 3(2), 228–237.

Fu, H., Jiang, J., Hu, S., Rao, J., & Theodossiades, S. (2023). A multi-stable ultra-low frequency energy harvester using a nonlinear pendulum and piezoelectric transduction for self-powered sensing. Mechanical Systems and Signal Processing, 189, 110034.

Jiang, J., & Astolfi, A. (2020). Stabilization of a class of underactuated nonlinear systems via underactuated back-stepping. IEEE Transactions on Automatic Control, 66(11), 5429–5435.

Hu, J., Lin, Y., Li, J., Hou, Z., Chu, L., Zhao, D., Zhou, Q., Jiang, J., & Zhang, Y. (2024). Performance analysis of AI-based energy management in electric vehicles: A case study on classic reinforcement learning. Energy Conversion and Management, 300, 117964.

Hacene Mellah | Electrical Engineering | Best Researcher Award

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Dr. Hacene Mellah | Electrical Engineering | Best Researcher Award

bouira university | Algeria

Dr. Hacene Mellah is an Associate Professor of Electrical Engineering at Université de Bouira, Algeria. His education includes an Ingenieur degree (2006) with a focus on electrical machine control, a Magister (2009) in electrical machines and control, a PhD (2020) in electrical machines, and his habilitation à diriger des recherches (HDR). He conducts research in estimation techniques of intrinsic machine parameters and thermal behaviour, fault diagnosis, renewable energy systems (wind, PV, hybrid), and control strategies for advanced electrical machines and drives. According to the AD Scientific Index (2025), his total h-index is 7, with about 91 citations and 24 indexed documents. A recent years his work has focused on observer design, neural networks, finite element modelling (FEM), and smart control of doubly fed induction generators among other topics. He has published in a number of peer-reviewed journals as well as international conferences. His contributions have enhanced understanding of sensorless control, fault modelling, and thermal monitoring for electrical machines, particularly under transient or non-linear conditions. Looking forward, he aims to expand his research in intelligent control, sustainable energy integration, and improved diagnostics. He seeks collaborations and impact through both theoretical development and practical applications in electrical drive systems.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Sahraoui, H., Mellah, H., Drid, S., & Chrifi-Alaoui, L. (2021). Adaptive maximum power point tracking using neural networks for photovoltaic systems according grid. Electrical Engineering & Electromechanics, (5), 57–66.

Mellah, H., Hemsas, K. E., & Taleb, R. (2016). Intelligent sensor based Bayesian neural network for combined parameters and states estimation of a brushed DC motor. International Journal of Advanced Computer Science and Applications (IJACSA), 7(7), 230–235.

Mellah, H., & Hemsas, K. E. (2013). Simulations analysis with comparative study of a PMSG performances for small WT application by FEM. International Journal of Energy Engineering, 3(2), 55–64.

Maafa, A., Mellah, H., Ghedamsi, K., & Aouzellag, D. (2022). Improvement of sliding mode control strategy founded on cascaded doubly fed induction generator powered by a matrix converter. Engineering, Technology & Applied Science Research, 12(5), 9217–9223.

Bounasla, N., Hemsas, K. E., & Mellah, H. (2015). Synergetic and sliding mode controls of a PMSM: A comparative study. Journal of Electrical and Electronic Engineering, 3(1-1), 22–26.