Dr. Zhe Wang | Wireless Network | Best Researcher Award

Guangxi Minzu University, China.

Dr. Zhe Wang is an Assistant Professor at the School of Artificial Intelligence, Guangxi Minzu University. He earned his PhD in Electric Power and Intelligent Information from Guangxi University in 2019. His research focuses on Simultaneous Wireless Information and Power Transfer (SWIPT), wireless power transfer, optimization, and AI applications. Dr. Wang has contributed significantly to the field of federated learning and privacy-preserving AI techniques, with publications in high-impact journals.

Profile

Scopus

🎓 Education

Dr. Zhe Wang holds a PhD in Electric Power and Intelligent Information from Guangxi University, China, which he obtained in 2019. His academic journey has been centered on advancing research in wireless power transfer, optimization techniques, and AI applications in energy systems. With a strong foundation in electrical engineering and intelligent systems, Dr. Wang has contributed to cutting-edge innovations in Simultaneous Wireless Information and Power Transfer (SWIPT). His expertise bridges the gap between power systems and artificial intelligence, driving new methodologies for efficient and intelligent energy solutions.

💼 Experience

Dr. Zhe Wang is an Assistant Professor at the School of Artificial Intelligence, Guangxi Minzu University, a position he has held since 2021. Prior to this, he served as a Lecturer at the School of Information Engineering at the same university from 2019 to 2020. His academic contributions focus on advancing research and education in artificial intelligence and information engineering, fostering innovation in these rapidly evolving fields.

🔬 Research Interests

Simultaneous Wireless Information and Power Transfer (SWIPT)

Wireless Power Transfer

Optimization Techniques

AI Applications in Power Systems

Privacy-Preserving AI & Federated Learning

🏆 Awards & Recognitions

Outstanding Research Contribution Award – Guangxi Minzu University

Best Paper Award – International Conference on Artificial Intelligence Applications

Innovation Excellence Honor – SWIPT & Wireless Power Transfer Research

📚 Publications

1️⃣ "A Review of Privacy-Preserving Research on Federated Graph Neural Networks"

Journal: Neurocomputing (2024)

Cited by: 2 articles

2️⃣ "A Review of Secure Federated Learning: Privacy Leakage Threats, Protection Technologies, Challenges, and Future Directions"

Journal: Neurocomputing (2023).

Cited by: 22 articles

Assoc Prof Dr. Panjit Musik. Computing science, Best Researcher Award

Associate Professor at Panjit Musik walailak university, Thailand

Assoc. Prof. Dr. Panjit Musik, born on July 4, 1961, is a distinguished academic in the fields of Physics, Computational Science, and Smart Farming. He currently teaches at the School of Science, Walailak University in Thailand. His academic journey and professional accomplishments reflect a commitment to advancing education and research in scientific and technological innovations.

Author Metrics

Scopus Profile

Dr. Musik has authored numerous research papers published in international and national journals, contributing significantly to the fields of Physics, Computational Science, and Smart Farming. His works are frequently cited, reflecting his influence in these research areas.

Panjit Musik is associated with Walailak University in Tha Sala, Thailand. His academic profile on Scopus shows a modest yet emerging research output, with 4 documents and 5 citations, resulting in an h-index of 1.

Education

Dr. Musik earned his Doctor of Philosophy in Computational Science from Walailak University in 2005. He holds a Master of Science in Teaching Physics from Chiang Mai University, obtained in 1990, and a Bachelor of Education in Physics from Thaksin University, completed in 1983. This strong educational foundation underpins his extensive research and teaching career.

Research Focus

Dr. Musik’s research interests are diverse and interdisciplinary, encompassing Physics Teaching, Real-Time Physics Labs, Computational Modeling and Simulation, and Smart Farming. His work aims to integrate technological advancements with educational practices to enhance learning outcomes and develop innovative solutions for agricultural challenges.

Professional Journey

Dr. Musik’s professional journey began with a focus on physics education and has evolved to include computational modeling and smart farming technologies. He has developed numerous computer-based experimental sets and simulations, contributing to both academic and practical advancements in his fields of expertise.

Honors & Awards

Throughout his career, Dr. Musik has received several accolades for his contributions to science and education. His innovative work in developing experimental sets and integrating computational methods in education has been recognized by academic and professional institutions.

Publications Noted & Contributions

Dr. Musik has published extensively in international journals such as the Turkish Online Journal of Educational Technology and the International Journal on Smart Sensing and Intelligent Systems. His publications address key issues in computational physics, real-time experimental learning, and smart farming technologies, contributing to the academic discourse and practical applications in these areas.

Development of a Computer-Based Simple Pendulum Experiment Set for Teaching and Learning Physics

Authors: Sukmak, W., & Musik, P.
Journal: International Journal on Smart Sensing and Intelligent Systems, 2021, 14(1), pp. 1–8
Citations: 1

Abstract: This article presents the development of a computer-based experiment set designed to enhance the teaching and learning of physics through a simple pendulum experiment. The set aims to provide real-time data acquisition and analysis, making physics concepts more accessible and engaging for students. The development process, implementation, and educational benefits are discussed in detail.

Development of an Automated Water Management System in Orchards in Southern Thailand

Author: Musik, P.
Journal: International Journal on Smart Sensing and Intelligent Systems, 2020, 13(1), pp. 1–7
Citations: 2

Abstract: Dr. Musik explores the design and implementation of an automated water management system tailored for orchards in southern Thailand. This system leverages smart sensing technologies to optimize water usage, ensuring efficient irrigation and enhancing crop yields. The article details the system’s components, operational mechanisms, and the positive impact on orchard management.

Development of Computer-Based Experiment Set on Simple Harmonic Motion of Mass on Springs

Author: Musik, P.
Journal: Turkish Online Journal of Educational Technology, 2017, 16(4), pp. 1–11
Citations: 1

Abstract: This study describes the creation of an experimental set for investigating the simple harmonic motion of a mass on a spring. The set integrates computer-based tools to facilitate real-time data collection and visualization, aiming to improve students’ understanding of oscillatory motion through interactive and hands-on learning experiences.

Large-Scale Simulation Using Parallel Computing Toolkit and Server Message Block

Authors: Musik, P., & Jaroensutasinee, K.
Journal: WSEAS Transactions on Mathematics, 2007, 6(2), pp. 369–372
Citations: 1

Abstract: This paper discusses a large-scale simulation approach using a parallel computing toolkit and server message block. The simulation targets complex mathematical models, enhancing computational efficiency and accuracy. The authors highlight the methodology, computational framework, and potential applications in scientific research.

These articles reflect Dr. Panjit Musik’s extensive work in developing innovative educational tools and applying computational methods to solve practical problems in agriculture and physics education. His research contributes significantly to enhancing teaching methodologies and improving resource management in various domains.

Research Timeline

Dr. Musik’s research timeline spans over three decades, beginning with his master’s research in 1990 on computer control of humidity in experimental greenhouses. His doctoral research in 2005 focused on large-scale water flow simulation using Mathematica. In the years following, he has conducted numerous studies on integrating remote sensing data, developing computer-based experiments, and smart farming solutions.

Collaborations and Projects

Dr. Musik has collaborated with various researchers and institutions on projects aimed at developing innovative educational tools and smart farming technologies. His projects include the development of watershed and hydrologic process modeling for flood forecasting, automated water management systems in orchards, and GIS applications for agricultural water management.

Contributions to the Field

Dr. Musik’s contributions to the field include the development of computer-based experimental sets for physics education, large-scale simulations for environmental modeling, and smart farming technologies. His work has provided valuable insights and practical tools for educators, researchers, and farmers, advancing both academic knowledge and real-world applications.