Chin-Shiuh Shieh Editor at IgMin Research
Our purpose is to inspire collaborative dialogue among scientific fields and foster accelerated knowledge development.
Biography
Chin-Shiuh Shieh received the M.S. degree in Electrical Engineering from the National Taiwan University, Taiwan, in 1991, and the Ph.D. degree in Computer Science and Engineering from National Sun Yat-Sen University, Taiwan in 2009.
In August 1991, he joined the faculty of the Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Taiwan, where he currently serves as a Full Professor. His research interests include computer networking, embedded systems, computational intelligence and information security.
Research Interest
Computer Networking, Wireless Communication, Information Security, Computational Intelligence, Embedded Systems, Medical Informatics.
Editor
Work Details
Professor
National Kaohsiung University of Science and Technology
Department of Electronic Engineering
Taiwan
0000-0003-3187-458X Contribution by Topic Area
Why publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
Which articles are now trending?
Research Articles
- Modeling of an Electric-fired Brick Oven, Directly Heated
- The Influence of Dynamical Downscaling and Boundary Layer Selection on Egypt’s Potential Evapotranspiration using a Calibrated Version of the Hargreaves-samani Equation: RegCM4 Approach
- Assessing Bee (Hymenoptera, Apoidea, Anthophila) Diversity and Floral Preference in Two Habitats in the Iberian Peninsula
- Clustering of Three-dimensional (3-D) Objects by Means of Phase- only Digital Holographic Information using Machine Learning
- From Traditionalism to Algorithms: Embracing Artificial Intelligence for Effective University Teaching and Learning
- Clinical MLOps: A Framework for Responsible Deployment and Observability of AI Systems in Cloud-Native Healthcare
