Zhiyong Pei | Artificial Intelligence | Best Researcher Award

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Prof. Zhiyong Pei | Artificial Intelligence | Best Researcher Award

Director | Wuhan university of technology | China

Prof. Zhiyong Pei serves as the Director and Professor at the Green & Smart River-Sea-Going Ship, Cruise and Yacht Research Centre at Wuhan University of Technology. His career is defined by contributions to the advancement of green and smart ship technologies. Under his leadership, projects like the 18,000 DWT inland bulk carrier and 6,600 DWT coastal bulk carrier have achieved CCS Green Ship III certification, exemplifying eco-friendly and efficient ship design. Prof. Pei’s work embodies the “4E” philosophy—Energy conservation, Environmental friendliness, Economy, and Efficiency—pioneering innovations that redefine modern shipbuilding and contribute to sustainable maritime advancements.

Profile

Scopus

Education

Prof. Zhiyong Pei earned his doctorate from Hiroshima University in 2005, specializing in maritime engineering and environmental technologies. His academic foundation was further reinforced by hands-on research at Tsuneishi Shipbuilding Co., Ltd., where he served as a Research Fellow from 2005 to 2012. Since 2013, he has been a Professor at Wuhan University of Technology, where he continues to contribute to cutting-edge research and innovation in the field of green and intelligent maritime systems.

Experience

Prof. Pei brings over two decades of experience in ship design and maritime technology development. His tenure at Tsuneishi Shipbuilding Co., Ltd. honed his expertise in practical shipbuilding innovations, while his role at Wuhan University of Technology allows him to bridge theoretical research with real-world applications. He has led numerous state-funded projects focused on energy-efficient, eco-friendly ships, and has been instrumental in promoting green technologies in the shipping industry.

Research Interests

Prof. Pei’s research interests revolve around energy-efficient and environmentally friendly maritime technologies. He is passionate about the development of new ship types, innovative propulsion systems, and AI-driven optimization techniques. His work on neural network algorithms and genetic algorithms for ship resistance reduction has significantly contributed to the industry’s efforts in minimizing fuel consumption and emissions. Additionally, he explores the integration of hydrogen-powered systems into maritime applications.

Awards

Prof. Zhiyong Pei has been recognized for his contributions to maritime research and innovation. He is a nominee for the Distinguished Scientist Award, reflecting his impact in green and smart ship design. His work has earned accolades for pushing the boundaries of sustainable technologies in shipbuilding and fostering international collaborations that drive the industry forward.

Publications

“Development of Eco-Friendly River-Sea-Going Vessels”, Journal of Maritime Engineering (2020) – Cited by 25 articles.

“Neural Network Applications in Ship Resistance Reduction”, Marine Technology Journal (2021) – Cited by 30 articles.

“Hydrogen-Powered Ships: A Pathway to Zero Emissions”, Journal of Green Shipping (2019) – Cited by 18 articles.

“Innovations in 4E Ship Design”, Environmental Marine Systems (2022) – Cited by 15 articles.

“Energy Optimization in Bulk Carriers”, Sustainable Maritime Review (2018) – Cited by 20 articles.

“Advanced Materials for Lightweight Ships”, Shipbuilding Innovations (2023) – Cited by 10 articles.

“AI-Driven Optimization in Shipbuilding”, Journal of Smart Systems (2021) – Cited by 22 articles.

Conclusion

Prof. Zhiyong Pei exemplifies a blend of academic rigor and practical expertise, making him a leading figure in green and smart ship technologies. His contributions have significantly advanced the maritime industry, emphasizing sustainability, innovation, and efficiency. Through his dedication to research and collaboration, Prof. Pei has paved the way for a more sustainable and intelligent future in shipbuilding. His work continues to inspire advancements in maritime technology and sets a benchmark for excellence in the field.

Amir veisi | Artificial Intelligence | Best Researcher Award

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Dr. Amir veisi | Artificial Intelligence | Best Researcher Award

PhD | Bu-Ali Sina University | Iran

Amir Veisi is a dedicated PhD student specializing in Control Engineering at Bu-Ali Sina University, Hamedan, Iran, under the guidance of Dr. Hadi Delavari. With a strong academic foundation, he has cultivated expertise in nonlinear fractional-order systems, renewable energy, and artificial intelligence. His research primarily revolves around advanced control methods, such as data-driven and fault-tolerant controls, applied to renewable energy and biomedical systems. Amir is also an award-winning researcher with a notable record of publications in esteemed journals, reflecting his commitment to innovation and knowledge dissemination in control engineering.

Profile

Scholar

Education

Amir began his academic journey with a Bachelor of Science in Electronic Engineering at Islamic Azad University, Zahedan, graduating in 2017. He pursued a Master of Science in Control Engineering at Hamedan University of Technology, completing his thesis on fractional-order sliding mode control for wind turbines in 2021. Currently, he is pursuing a PhD in Control Engineering at Bu-Ali Sina University. His doctoral research focuses on developing nonlinear fractional-order data-driven controllers for complex nonlinear systems.

Experience

Amir’s academic and professional experiences highlight his deep involvement in control systems and engineering education. As a teaching assistant at Hamedan University of Technology, he contributed to courses on linear control systems, providing valuable insights to students. Additionally, Amir worked as an electronic board repair instructor at Pishtaz Electronic Company from 2013 to 2018, bridging theoretical concepts with practical applications. His work demonstrates a seamless integration of academic knowledge and hands-on expertise.

Research Interests

Amir’s research interests span a range of cutting-edge topics in control engineering and related fields. He is deeply invested in renewable energy systems, artificial intelligence, machine learning, reinforcement learning, and data-driven control. His expertise extends to fractional-order nonlinear control, fault-tolerant control, and real-time systems. Amir’s commitment to advancing knowledge in estimation and control of nonlinear dynamic systems reflects his vision for a sustainable and technologically advanced future.

Awards

Amir has received several prestigious accolades throughout his career. He was honored as the best researcher of the year at Hamedan University in 2021 and at Bu-Ali Sina University in 2022. His work on fractional-order nonlinear controllers earned him the best paper award at the 2023 International Conference on Technology and Energy Management (ICTEM). Amir also serves as a reviewer for reputed journals, including Springer Nature, Elsevier, and others, contributing significantly to the academic community.

Publications

Amir Veisi has authored several impactful papers in renowned journals and conferences:

Robust control of a permanent magnet synchronous generators based wind energy conversion
Authors: H Delavari, A Veisi
Year: 2021
Citations: 14

Adaptive fractional order control of photovoltaic power generation system with disturbance observer
Authors: A Veisi, H Delavari
Year: 2021
Citations: 11

A new robust nonlinear controller for fractional model of wind turbine based DFIG with a novel disturbance observer
Authors: H Delavari, A Veisi
Year: 2024
Citations: 10

Adaptive optimized fractional order control of doubly‐fed induction generator (DFIG) based wind turbine using disturbance observer
Authors: A Veisi, H Delavari
Year: 2024
Citations: 10

Fractional‐order backstepping strategy for fractional‐order model of COVID‐19 outbreak
Authors: A Veisi, H Delavari
Year: 2022
Citations: 8

Adaptive fractional backstepping intelligent controller for maximum power extraction of a wind turbine system
Authors: A Veisi, H Delavari
Year: 2023
Citations: 5

Maximum power point tracking in a photovoltaic system by optimized fractional nonlinear controller
Authors: A Veisi, H Delavari, F Shanaghi
Year: 2023
Citations: 5

Power Maximization of Wind Turbine Based on DFIG using Fractional Order Variable Structure Controller
Authors: H Delavari, A Veisi
Year: 2021
Citations: 5

Fuzzy-type 2 fractional fault tolerant adaptive controller for wind turbine based on adaptive RBF neural network observer
Authors: A Veisi, H Delavari
Year: 2024
Citations: 4

Fuzzy fractional-order sliding mode control of COVID-19 virus variants
Authors: H Delavari, A Veisi
Year: 2023
Citations: 4

Conclusion

Amir Veisi’s journey in control engineering exemplifies his dedication to solving complex challenges through innovative research and application-driven solutions. His contributions to renewable energy systems, artificial intelligence, and control systems reflect his commitment to addressing pressing global issues. As a scholar and practitioner, Amir continues to push boundaries, inspiring both academic and industrial advancements in his field.