Yunxiang Lu | Neural Networks | Best Researcher Award

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Dr. Yunxiang Lu | Neural Networks | Best Researcher Award

Ph.D | College of Automation & College of Artificial Intelligence | China

Dr. Yunxiang Lu is a dedicated researcher and academic currently affiliated with the College of Automation and the College of Artificial Intelligence at Nanjing University of Posts and Telecommunications, China. His work spans advanced topics in control science, neural networks, and ecological competition networks, underpinned by rigorous academic and practical experiences. Dr. Lu’s career is marked by his pursuit of ground breaking research, particularly in the realms of dynamic systems, network topology, and bifurcation analysis. Through a robust combination of theoretical exploration and simulation-based validation, he has significantly contributed to the field of artificial intelligence and control systems.

Profile

Scopus

Education

Dr. Lu embarked on a combined Master and Ph.D. program in Control Science and Engineering in 2019. As part of his academic journey, he is currently affiliated with the Polish Academy of Sciences – Institute of Systems Research for a year-long research collaboration. This academic foundation has provided him with a strong grasp of theoretical frameworks and hands-on application in control engineering, establishing him as a skilled scholar and innovator in his domain.

Experience

Dr. Lu’s professional experience includes a stint as an IT Technical Engineer at China Telecom Corporation, where he contributed to the 5G+MEC smart factory project, enhancing his expertise in telecommunications and automation. His role involved exploring the integration of 5G technologies in industrial applications, further broadening his technical horizon. Additionally, his active participation in academia includes leading research projects funded by Jiangsu Province, with notable achievements in ecological competition networks and time-delay feedback control mechanisms.

Research Interests

Dr. Lu’s research interests focus on fractional-order systems, neural networks, ecological dynamics, and the control of anomalous diffusion processes. He aims to uncover the intricate behaviors of complex networks influenced by various dynamic parameters. His work explores how time delays, fractional orders, and network topologies impact system stability and evolution, with applications ranging from neural systems to cyber-physical and ecological networks.

Awards and Honors

Dr. Lu has received numerous accolades recognizing his academic excellence and contributions. Notably, he was honored as the Excellent Graduate of Nanjing University of Posts and Telecommunications in 2022 and received the prestigious Postgraduate Academic Scholarship awards multiple times during his tenure. These distinctions underscore his dedication and consistent performance in both research and academics.

Publications

Dr. Lu has co-authored several impactful publications in esteemed journals.

Tipping prediction of a class of large-scale radial-ring neural networks

    • Authors: Lu, Y., Xiao, M., Wu, X., Cao, J., Zheng, W.X.
    • Publication Year: 2025
    • Citations: 0

Complex pattern evolution of a two-dimensional space diffusion model of malware spread

    • Authors: Cheng, H., Xiao, M., Lu, Y., Rutkowski, L., Cao, J.
    • Publication Year: 2024
    • Citations: 0

Spatiotemporal Evolution of Large-Scale Bidirectional Associative Memory Neural Networks With Diffusion and Delays

    • Authors: Lu, Y., Xiao, M., Liang, J., Wang, Z., Cao, J.
    • Publication Year: 2024
    • Citations: 1

Stability and Bifurcation Exploration of Delayed Neural Networks with Radial-Ring Configuration and Bidirectional Coupling

    • Authors: Lu, Y., Xiao, M., He, J., Wang, Z.
    • Publication Year: 2024
    • Citations: 6

Stability and Dynamics Analysis of Time-Delay Fractional-Order Large-Scale Dual-Loop Neural Network Model With Cross-Coupling Structure

    • Authors: Du, X., Xiao, M., Qiu, J., Lu, Y., Cao, J.
    • Publication Year: 2024
    • Citations: 0

QUALITATIVE ANALYSIS OF HIGH-DIMENSIONAL NEURAL NETWORKS WITH THREE-LAYER STRUCTURE AND MULTIPLE DELAYS

    • Authors: He, J., Xiao, M., Lu, Y., Sun, Y., Cao, J.
    • Publication Year: 2024
    • Citations: 0

Early warning of tipping in a chemical model with cross-diffusion via spatiotemporal pattern formation and transition

    • Authors: Lu, Y., Xiao, M., Huang, C., Wang, Z., Cao, J.
    • Publication Year: 2023
    • Citations: 8

Tipping point prediction and mechanism analysis of malware spreading in cyber–physical systems

    • Authors: Xiao, M., Chen, S., Zheng, W.X., Wang, Z., Lu, Y.
    • Publication Year: 2023
    • Citations: 10

Control of tipping in a small-world network model via a novel dynamic delayed feedback scheme

    • Authors: He, H., Xiao, M., Lu, Y., Wang, Z., Tao, B.
    • Publication Year: 2023
    • Citations: 9

Bifurcation Dynamics Analysis of A Class of Fractional Neural Networks with Mixed Delays

    • Authors: Luan, Y., Lu, Y., Xiao, M., Zhang, J.
    • Publication Year: 2023
    • Citations: 0

Conclusion

Dr. Yunxiang Lu exemplifies the synthesis of academic brilliance, practical expertise, and research acumen. His dedication to advancing knowledge in control systems and artificial intelligence positions him as a visionary scholar in his field. Through his continued exploration of dynamic networks and innovative control strategies, he remains committed to addressing complex challenges in modern science and technology.

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.