Assist. Prof. Dr. AWAIS KHAN | Engineering | Best Researcher Award
Assist. Prof. Dr. AWAIS KHAN, Beijing Institute of Technology Zhuhai Campus, China
Dr. Awais Khan is an Assistant Professor at the Beijing Institute of Technology, Zhuhai Campus, specializing in advanced control systems, renewable energy technologies, and interval observers. With a PhD in Control Theory and Control Engineering from South China University of Technology, Dr. Khan has made significant contributions to mechatronics and control engineering during his tenure as a Postdoctoral Research Fellow at Shenzhen University. His research is recognized for its innovative approach, particularly in the application of control systems in energy-efficient technologies. A prolific researcher and published author, Dr. Khan has been actively involved in securing research funding and publishing in top-tier journals. His passion for both teaching and research allows him to foster a dynamic learning environment for students while contributing to the advancement of technology in engineering and energy sectors.
Professional Profile
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Summary of Suitability for the Research for Best Researcher Award
Awais Khan’s impressive academic background and research trajectory make him highly suitable for the Research for Best Researcher Award. He currently serves as an Assistant Professor at the Beijing Institute of Technology, where he leads cutting-edge research in advanced control systems, renewable energy technologies, and interval observers. His teaching excellence, combined with his groundbreaking research contributions, aligns well with the award’s criteria, which honors those making significant academic and technological advancements.
Awais Khan’s postdoctoral experience at Shenzhen University further solidifies his research prowess, particularly in mechatronics and control engineering. His work has been recognized in reputable journals, with a consistent record of impactful publications in high-impact platforms such as IEEE Transactions and the Journal of the Franklin Institute. He has demonstrated leadership in securing research funding and fostering interdisciplinary collaboration.
Education
Dr. Awais Khan holds a PhD in Control Theory and Control Engineering from the South China University of Technology (2016–2020), where his research focused on interval observers and their applications to control theory. Prior to that, he earned a Master’s degree in Electrical Engineering from the University of Engineering and Technology (UET) Lahore (2014–2016). Dr. Khan’s academic journey began with a Bachelor of Science in Electronics Engineering from UET Peshawar (2009–2013), which laid the foundation for his expertise in engineering and control systems. Throughout his academic career, he has received several scholarships, including the prestigious Chinese Government Scholarship for his PhD studies. His educational background is complemented by his active participation in various research projects, workshops, and technical conferences, enabling him to stay at the forefront of advancements in control systems, renewable energy technologies, and energy-efficient engineering solutions.
Professional Experience
Since 2022, Dr. Awais Khan has been an Assistant Professor at the Beijing Institute of Technology, Zhuhai Campus, where he teaches a range of courses, including C/C++, Probability & Statistical Analysis, Circuits & Electronics, and Physics. His role involves both delivering high-quality lectures and conducting groundbreaking research in advanced control systems, renewable energy, and interval observers. Prior to this, Dr. Khan was a Postdoctoral Research Fellow at Shenzhen University (2020–2022), where he worked on mechatronics and control engineering, developing innovative technologies in interdisciplinary research collaborations. His work on interval observers for nonlinear systems garnered attention, leading to publications in reputable journals. Dr. Khan has also contributed to National Natural Science Foundation of China projects, enhancing the understanding of control systems in uncertain environments. His teaching and research experience are central to his contributions to the field, shaping future engineers and advancing the integration of energy-efficient technologies.
Awards and Recognition
Dr. Awais Khan has been recognized for his outstanding contributions to control systems and engineering through several prestigious awards and honors. Notably, he received the Best Presentation Award at the EECR in 2018, reflecting his excellence in research communication. His doctoral research, supported by the Chinese Government Scholarship, marked a milestone in the development of interval observers for linear and nonlinear systems. In addition, Dr. Khan serves as an editor for Technological Innovations & Energy and has been an active member of professional organizations, such as the IEEE and the International Association of Engineers, since 2024. His scholarly work has been widely recognized, with numerous publications in leading journals and conferences. He continues to secure research grants, supporting the advancement of innovative technologies in control systems and energy efficiency. Dr. Khan’s contributions to both academia and the engineering community have made him a respected figure in the field.
Dr. Awais Khan possesses a deep proficiency in advanced control systems, renewable energy technologies, and interval observers. His research expertise spans control theory, nonlinear systems, and energy-efficient technologies, focusing on their applications in both academia and industry. With a strong background in mechatronics and control engineering, he has developed innovative solutions for system stability and energy optimization. Dr. Khan is skilled in designing interval observers for dynamic systems, particularly in uncertain environments, and has published extensively on the subject. His work also explores adaptive control strategies for robotics and power systems, leveraging cutting-edge technologies such as SiC and GaN. Dr. Khan is proficient in several programming languages, including Matlab, Simulink, Python, and C/C++, enabling him to implement complex models and simulations for his research. His skills in interdisciplinary collaboration and securing funding for research projects further highlight his versatility and commitment to advancing technological solutions in engineering.
Publication Top Notes
- A survey of interval observers design methods and implementation for uncertain systems
A Khan, W Xie, Z Bo, LW Liu
Journal of the Franklin Institute, 358(6), 3077-3126, 2021
Citation: 52
- Design and Applications of Interval Observers for Uncertain Dynamical Systems
A Khan, W Xie, Z Langwen, LW Liu
IET Circuits, Devices & Systems, 14(6), 721-740, 2020
Citation: 48
- Path Planning for Wheeled Mobile Robot in Partially Known Uneven Terrain
B Zhang, G Li, Q Zheng, X Bai, Y Ding, A Khan
Sensors, 22(14), 5217, 2022
Citation: 41
- Finite‐time nonsingular terminal sliding mode control of converter‐driven DC motor system subject to unmatched disturbances
A Rauf, M Zafran, A Khan, AR Tariq
International Transactions on Electrical Energy Systems, 31(11), e13070, 2021
Citation: 26
- Interval state estimation for linear time-varying (LTV) discrete-time systems subject to component faults and uncertainties
A Khan, W Xie, L Zhang, Ihsanullah
Archives of Control Sciences, 29(2), 289-305, 2019
Citation: 22
- Set-Membership Interval State Estimator Design Using Observability Matrix for Discrete-Time Switched Linear Systems
A Khan, LW Liu, W Xie
IEEE Sensors Journal, 20(11), 6121-6129, 2020
Citation: 20
- Interval State Estimator Design for Linear Parameter Varying (LPV) Systems
A Khan, X Bai, Z Bo, P Yan
IEEE Transactions on Circuits and Systems II: Express Briefs, 68(8), 2865-2869, 2021
Citation: 19
- Finite‐time functional interval observer for linear systems with uncertainties
L Liu, W Xie, A Khan, L Zhang
IET Control Theory & Applications, 14(18), 2868-2878, 2020
Citation: 14
- Fault detection and diagnosis for a class of linear time-varying (LTV) discrete-time uncertain systems using interval observers
Z Yi, W Xie, A Khan, B Xu
2020 39th Chinese Control Conference (CCC), 4124-4128, 2020
Citation: 14
- Interval State Estimator Design Using the Observability Matrix for Multiple Input Multiple Output Linear Time-Varying Discrete-Time Systems
A Khan, W Xie
IEEE Access, 7, 167566-167576, 2019
Citation: 13