AWAIS KHAN | Engineering | Best Researcher Award

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.

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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.

🌍  Research Skills On Engineering

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

Praveen Sankarasubramanian | Engineering | Best Researcher Award

Dr. Praveen Sankarasubramanian | Engineering | Best Researcher Award

Dr. Praveen Sankarasubramanian, RMD Research labs, India

Dr. Praveen Sankarasubramanian is a distinguished technologist and researcher with over 13 years of experience in software development, AI, cloud computing, and industrial safety. Currently, he serves as a Senior Software Developer at Pearson India Education Services, specializing in Java, Spring Boot, and AWS Cloud. Dr. Praveen is also the founder of RMD Research Labs, focusing on cutting-edge research in AI, NLP, and safety technologies. His academic expertise is complemented by a Ph.D. in Computer Science and Engineering from VELS University, an M.Tech. in Software Systems from Birla Institute of Technology and Science, and multiple certifications. Dr. Praveen has developed innovative solutions in various domains, including AI-driven safety mechanisms, cloud platforms, and personalized learning systems. His leadership, mentorship, and continuous drive for innovation have made a significant impact on both academic and industry landscapes.

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🎓Education:

Dr. Praveen Sankarasubramanian’s academic journey reflects his dedication to excellence in technology and engineering. He earned a Ph.D. in Computer Science and Engineering from VELS University (March 2018 – August 2023), where he focused on AI, NLP, and cloud-based technologies. His M.Tech. in Software Systems from Birla Institute of Technology and Science, Pilani (2015-2017) provided a solid foundation in advanced software development techniques. Further expanding his expertise, Dr. Praveen completed an Advanced Diploma in Industrial Safety from Bharat Sevak Samaj (2017-2018). Additionally, he pursued a Post Graduate Program in Business Administration with a focus on operations from Symbiosis (2012-2014). His academic background equips him with a diverse skill set, enabling him to tackle complex problems in software engineering, AI, and industrial safety. This foundation has played a key role in his successful integration of theoretical knowledge with practical solutions.

💼Professional Experience:

Dr. Praveen Sankarasubramanian has extensive professional experience, having held leadership roles in major global tech companies. Currently, he is a Senior Software Developer at Pearson India Education Services, where he focuses on cutting-edge technologies such as Java, AWS Cloud, and Spring Boot. Before this, Dr. Praveen was a Senior Software Engineer at Cognizant, where he managed multiple projects in personalized learning and analytics. He oversaw a cross-functional team of 48 members and led seven parallel projects, successfully meeting organizational and project goals. Dr. Praveen’s experience also spans roles at Software AG, GlobalLogic, and 8K Miles Software Services, where he developed cloud-based systems and advanced data analytics solutions. As the founder of RMD Research Labs, he continues to lead research projects in AI and NLP. His career has consistently showcased his ability to merge leadership with technical innovation to drive impactful solutions in both academia and industry.

🔬Research Skills:

Dr. Praveen Sankarasubramanian possesses a diverse and highly advanced skill set in research, combining expertise in artificial intelligence (AI), natural language processing (NLP), machine learning (ML), cloud computing, and industrial safety. His research work spans several impactful areas, such as developing AI-driven safety systems, optimizing cloud platforms, and advancing personalized learning solutions in education technology. Dr. Praveen has also contributed to bandwidth optimization for video solutions and AI for predictive maintenance. His interdisciplinary approach allows him to apply theoretical research to real-world challenges, resulting in the creation of patents and innovative software solutions. Additionally, he has honed his skills in project management, utilizing Agile, Scrum, and JIRA to lead research teams effectively. Dr. Praveen’s research has not only influenced the tech industry but also shaped academic curricula, through his mentorship and contributions to educational resources such as books and journals for students.

🏆Awards and Recognition:

Dr. Praveen Sankarasubramanian’s dedication to innovation and technology has earned him numerous accolades throughout his career. He holds a patent for a system to monitor and handle liquid sodium leakage and fire accidents using AI, which showcases his contribution to industrial safety. His work on bandwidth optimization for video solutions also demonstrates his innovative approach to solving critical tech challenges. Dr. Praveen’s leadership and expertise in cloud computing, AI, and software development have been widely recognized within the tech industry, especially during his tenure at Pearson India and Cognizant. He has also been recognized for his mentorship, having successfully onboarded and guided numerous associates and students in their professional journeys. As a researcher, his contributions have further been acknowledged in academic circles, making him a trusted mentor for the next generation of engineers. His accolades reflect his commitment to excellence, both as a researcher and as a leader.

📖Publications Titles:

  • A System and Method for Monitoring, Sensing, Analyzing, and Handling the Pre-determined Status of Liquid Metals 📊💡
  • AI-driven Safety Mechanisms for Industrial Accidents 🔥🤖
  • Bandwidth Optimization for Video Solutions in Cloud-Based Applications 🌐📹
  • Predictive Maintenance in Industrial Safety Systems Using Machine Learning 🔧🤖
  • Developing Personalized Learning Solutions in Education Technology 🎓📚
  • Cloud Architecture for Scalable SaaS Platforms ☁️💻

🌟Conclusion:

Dr. Praveen Sankarasubramanian is a highly qualified and innovative researcher whose contributions to AI, cloud computing, and industrial safety have made a significant impact. His ability to blend academic knowledge with practical solutions, demonstrated through patents and cutting-edge technologies, highlights his research excellence. With over 13 years of experience, he has successfully led teams, managed complex projects, and mentored the next generation of engineers. Dr. Praveen’s leadership, technical expertise, and dedication to continuous innovation make him a deserving candidate for the Research for Best Researcher Award, marking him as a pioneer in his field.

Top Notable Publications

  • 👤 Enhancing precision in agriculture: A smart predictive model for optimal sensor selection through IoT integration
    • Authors: Sankarasubramanian, P.
    • Citations: 0 🌟
    • Year: 2025 🎓
    • Journal: Smart Agricultural Technology 📖
  • 👤 An efficient crack detection and leakage monitoring in liquid metal pipelines using a novel BRetN and TCK-LSTM techniques
    • Authors: Sankarasubramanian, P.
    • Citations: 0 🌟
    • Year: 2024 🎓
    • Journal: Multimedia Tools and Applications 📖
  • 👤 Protection of Hazardous Places in Industries using Machine Learning
    • Authors: Sankarasubramanian, P.
    • Citations: 1 🌟
    • Year: 2023 🎓
    • Conference: 2023 International Conference on Emerging Smart Computing and Informatics (ESCI 2023) 💼
  • 👤 Artificial intelligence-based detection system for hazardous liquid metal fire
    • Authors: Sankarasubramanian, P., Ganesh, E.N.
    • Citations: 1 🌟
    • Year: 2021 🎓
    • Conference: Proceedings of the 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom 2021) 💼
  • 👤 Realtime Pipeline Fire Smoke Detection Using a Lightweight CNN Model
    • Authors: Kumar, V.K.S., Sankarasubramanian, P.
    • Citations: 5 🌟
    • Year: 2021 🎓
    • Conference: Proceedings of the 2021 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT 2021) 💼
  • 👤 IoT based prediction for industrial ecosystem
    • Authors: Sankarasubramanian, P., Ganesh, E.N.
    • Citations: 1 🌟
    • Year: 2019 🎓
    • Journal: International Journal of Engineering and Advanced Technology 📖