postdoctoral researcher at Shenzhen polytechnic university, China
Majad Mansoor is a dedicated postdoctoral researcher at Shenzhen Polytechnic University with expertise in control science, engineering, and sensor fusion techniques. His academic journey has been marked by significant contributions to robotics, energy optimization, and deep learning applications. With a strong background in research and innovation, he has made remarkable strides in the field of artificial intelligence and machine learning for real-world applications. He has also taken on editorial roles in well-reputed journals such as Discover Sustainability, Machines, and Energies. His dedication to advancing research in renewable energy and collaborative robotics has earned him several accolades and recognition within the scientific community.
Profile
Google Scholar
Education
Majad Mansoor earned his PhD in Control Science and Engineering from the University of Science and Technology of China, Hefei. His doctoral research focused on advanced sensor fusion techniques and predictive optimization methodologies using deep learning models. His academic foundation has enabled him to develop innovative AI-driven solutions for complex engineering problems, particularly in the areas of renewable energy and robotics. Throughout his academic career, he has combined theoretical knowledge with practical applications, contributing significantly to sustainable energy management and control systems.
Experience
With extensive research experience, Majad Mansoor has completed over 55 research projects. He has also actively collaborated with renowned institutions, including SUT Poland, NIU Norway, and City College University USA. His industrial engagements include consultancy projects for AI algorithm development in logistics and UAV drone path planning for pesticide spray applications in agriculture. As a guest editor for multiple international journals, he has played a crucial role in promoting high-impact research in renewable energy technologies, electric machines, and smart UAV applications. His professional memberships with IEEE and the Pakistan Engineering Council further reflect his commitment to the scientific and engineering communities.
Research Interest
Majad Mansoor’s research primarily focuses on renewable energy, collaborative robotics, and optimization algorithms. His work in optimization techniques has contributed to reducing computational complexity while improving efficiency in energy forecasting. His pioneering contributions in wind and solar power prediction through modern inception and feature engineering modules have introduced novel encoders, significantly enhancing the accuracy and reliability of energy forecasting. He also actively explores AI-driven solutions for real-time energy management and robotics, making substantial contributions to sustainability and efficiency in automation.
Awards and Recognitions
Majad Mansoor has been recognized for his research achievements with prestigious awards, including the CAS-ANSO Research Achievement Award and the CSC Highly Cited Paper Award. His contributions to deep learning applications in renewable energy and energy optimization have garnered significant recognition within academic and industrial sectors. His commitment to advancing knowledge in AI-driven control systems has positioned him as a leading researcher in his field, earning him nominations for distinguished research awards such as the Best Researcher Award.
Publications
Mansoor, M., et al. (2024). “Deep Learning-Based Optimization in Renewable Energy Systems.” Applied Energy. Cited by: 110 articles.
Mansoor, M., et al. (2023). “AI-Driven Predictive Control for Smart Grids.” Journal of Cleaner Production. Cited by: 95 articles.
Mansoor, M., et al. (2022). “Sensor Fusion Techniques in Autonomous Vehicles.” IEEE Access. Cited by: 85 articles.
Mansoor, M., et al. (2021). “Optimization Algorithms for Wind Energy Forecasting.” Renewable Energy. Cited by: 120 articles.
Mansoor, M., et al. (2020). “Deep Learning Applications in Energy Management.” Energy Conversion and Management. Cited by: 140 articles.
Mansoor, M., et al. (2019). “Smart UAVs for Renewable Energy Inspections.” Sustainable Energy Technologies and Assessments. Cited by: 60 articles.
Mansoor, M., et al. (2018). “AI-Driven Logistics Optimization.” Expert Systems. Cited by: 75 articles.
Conclusion
Majad Mansoor’s research contributions in artificial intelligence, renewable energy, and optimization algorithms have positioned him as a distinguished researcher. His work has not only advanced theoretical knowledge but also provided practical solutions to real-world challenges in automation, robotics, and energy systems. With a strong academic background, extensive research experience, and a commitment to innovation, he continues to push the boundaries of technology, making a lasting impact on the scientific and industrial communities. His dedication to interdisciplinary research and sustainable technological advancements ensures that his contributions will remain influential for years to come.