Prof Dr. I-Shyan Hwang | Green Network Award | Best Researcher Award

Prof Dr. I-Shyan Hwang | Green Network Award | Best Researcher Award

Prof Dr. I-Shyan Hwang, Yuan Ze University, Taiwan

Prof. Dr. Hwang is a distinguished academic with a robust educational foundation, holding B.S. and M.S. degrees in Electrical and Electronic Engineering from Chung-Yuan Christian University, along with M.S. and Ph.D. degrees in Electrical and Computer Engineering from the State University of New York at Buffalo. Since 2007, he has served as a Full Professor in the Department of Computer Science and Engineering at Yuan Ze University, Taiwan. His research spans high-impact areas such as fault-tolerant computing, high-speed networks, AI green computing, and optical network infrastructures, all of which are vital to the advancement of next-generation computing systems. A recognized leader in scientific communities, Dr. Hwang has contributed to prestigious journals and served on editorial boards, underscoring his influence in photonics and optical networking. His collaborative, interdisciplinary approach is evident in his numerous joint publications, reflecting his commitment to addressing complex challenges at the intersection of AI, telecommunications, and sustainable technologies.

Professional Profile:

Orcid

Suitability for the Award:

Prof. Dr. I-Shyan Hwang’s career reflects excellence in research, teaching, and leadership in advanced technological fields. His focus on cutting-edge topics such as AI in green computing, software-defined networks, optical networks, and cloud computing infrastructure places him at the forefront of innovation. His impressive publication record and leadership in scholarly communities further solidify his qualifications for the Best Researcher Award.

Extensive Academic and Research Background:

Prof. Dr. Hwang has an impressive academic background with B.S. and M.S. degrees in Electrical and Electronic Engineering from Chung-Yuan Christian University and M.S. and Ph.D. degrees in Electrical and Computer Engineering from the State University of New York at Buffalo.

He has been a Full Professor in the Department of Computer Science and Engineering at Yuan Ze University, Taiwan, since 2007, showcasing his long-standing academic leadership and expertise.

Focus on High-Impact Research Areas:

His research interests cover a wide range of high-impact areas, including fault-tolerant computing, high-speed networks, fixed mobile convergence, heterogeneous multimedia services, AI green computing, and optical network-based infrastructure over cloud computing. These topics are highly relevant to current technological advancements and are crucial for the development of next-generation computing and networking systems.

His work on AI green computing and optical networks addresses sustainability and energy efficiency, which are pivotal areas of global concern today.

Leadership in Scientific Communities:

Dr. Hwang has served on the Editorial Board of the Springer Photonic Network Communications Journal and as a Guest Editor for special issues on Software-Defined Optical Networks. These roles demonstrate his leadership and influence within the academic community, where he has helped shape important conversations in photonics and optical networking.

Collaborative and Interdisciplinary Research:

His work involves collaborations across multiple domains, as evidenced by his joint publications with various researchers. This interdisciplinary approach highlights his ability to work on complex problems and develop solutions that cut across different fields such as AI, machine learning, and telecommunications.

Recent and Impactful Publications:

Prof. Hwang’s recent publications reflect a strong, ongoing commitment to research. The citations and publication in highly reputed journals like IEEE Access and Computers further enhance his reputation as a leading researcher in his fields of expertise.

Publication Top Notes:

  • Title: Peer-to-Peer Federated Learning on Software-Defined Optical Access Network
    • Year: 2024
  • Title: Direct Edge-to-Edge Local-Learning-Assisted Model-Based Transfer Learning
    • Year: 2024
  • Title: Feature-Selection-Based DDoS Attack Detection Using AI Algorithms
    • Year: 2024
  • Title: A Qualitative and Comparative Performance Assessment of Logically Centralized SDN Controllers via Mininet Emulator
    • Year: 2024
  • Title: Flexible Access Network Multi-Tenancy Using NFV/SDN in TWDM-PON
    • Year: 2023