Editorial
Open Access
Neural Computing: A New Era of Intelligent Adaptation and Learning
1
University College, Korea University, Seoul 02841, Republic of Korea
* Corresponding Author:
Munir Ahmad,
[email protected]
Volume 1, Issue 1
2025
Received: 24 February 2025
Accepted: 26 February 2025
Published: 17 March 2025
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CC BY 4.0 License
Article Information
Abstract
The inaugural editorial of the IECE Transactions on Neural Computing (IECE-TNC) presents the revolutionary influence of neural computing that incorporates artificial intelligence (AI), machine learning (ML), and next-gen computation models in cognitive systems, robotics, and healthcare. Although there have been tremendous developments, some problems remain including computational scalability, model interpretability, ethical considerations, and data security. IECE-TNC is dedicated to resolving these issues by facilitating high-impact research, interdisciplinary collaboration, and real-world applications. The magazine covers the following trends such as federated learning, explainable deep learning models, and neuromorphic computing while emphasizing transparency, reproducibility, and ethical AI practices. Simultaneously with the advantage of neural computing in terms of adaptability and efficiency, addressing the challenges of robustness, fairness, and sustainability remain critical. The journal requires consistent innovation, open-access collaboration, and industry-academia partnerships to push this area of study forward. IECE-TNC is dedicated to achieving the highest standards of research and technological advances, and we welcome the most innovative contributions that are capable of taking the field of neural computing to new heights.
Keywords
neural computing
artificial intelligence (AI)
machine learning (ML)
neuromorphic computing
brain-inspired AI
cognitive systems
federated learning
explainable AI (XAI)
deep learning
ethical AI
computational neuroscience
Data Availability Statement
Not applicable.
Funding
This work was supported without any funding.
Conflicts of Interest
The author declare no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
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APA Style
Ahmad, M. (2025). Neural Computing: A New Era of Intelligent Adaptation and Learning. ICCK Transactions on Neural Computing, 1(1), 1–10. https://doi.org/10.62762/TNC.2025.125800
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TY - JOUR AU - Ahmad, Munir PY - 2025 DA - 2025/03/17 TI - Neural Computing: A New Era of Intelligent Adaptation and Learning JO - ICCK Transactions on Neural Computing T2 - ICCK Transactions on Neural Computing JF - ICCK Transactions on Neural Computing VL - 1 IS - 1 SP - 1 EP - 10 DO - 10.62762/TNC.2025.125800 UR - https://www.icck.org/article/abs/TNC.2025.125800 KW - neural computing KW - artificial intelligence (AI) KW - machine learning (ML) KW - neuromorphic computing KW - brain-inspired AI KW - cognitive systems KW - federated learning KW - explainable AI (XAI) KW - deep learning KW - ethical AI KW - computational neuroscience AB - The inaugural editorial of the IECE Transactions on Neural Computing (IECE-TNC) presents the revolutionary influence of neural computing that incorporates artificial intelligence (AI), machine learning (ML), and next-gen computation models in cognitive systems, robotics, and healthcare. Although there have been tremendous developments, some problems remain including computational scalability, model interpretability, ethical considerations, and data security. IECE-TNC is dedicated to resolving these issues by facilitating high-impact research, interdisciplinary collaboration, and real-world applications. The magazine covers the following trends such as federated learning, explainable deep learning models, and neuromorphic computing while emphasizing transparency, reproducibility, and ethical AI practices. Simultaneously with the advantage of neural computing in terms of adaptability and efficiency, addressing the challenges of robustness, fairness, and sustainability remain critical. The journal requires consistent innovation, open-access collaboration, and industry-academia partnerships to push this area of study forward. IECE-TNC is dedicated to achieving the highest standards of research and technological advances, and we welcome the most innovative contributions that are capable of taking the field of neural computing to new heights. SN - 3068-7519 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Ahmad2025Neural,
author = {Munir Ahmad},
title = {Neural Computing: A New Era of Intelligent Adaptation and Learning},
journal = {ICCK Transactions on Neural Computing},
year = {2025},
volume = {1},
number = {1},
pages = {1-10},
doi = {10.62762/TNC.2025.125800},
url = {https://www.icck.org/article/abs/TNC.2025.125800},
abstract = {The inaugural editorial of the IECE Transactions on Neural Computing (IECE-TNC) presents the revolutionary influence of neural computing that incorporates artificial intelligence (AI), machine learning (ML), and next-gen computation models in cognitive systems, robotics, and healthcare. Although there have been tremendous developments, some problems remain including computational scalability, model interpretability, ethical considerations, and data security. IECE-TNC is dedicated to resolving these issues by facilitating high-impact research, interdisciplinary collaboration, and real-world applications. The magazine covers the following trends such as federated learning, explainable deep learning models, and neuromorphic computing while emphasizing transparency, reproducibility, and ethical AI practices. Simultaneously with the advantage of neural computing in terms of adaptability and efficiency, addressing the challenges of robustness, fairness, and sustainability remain critical. The journal requires consistent innovation, open-access collaboration, and industry-academia partnerships to push this area of study forward. IECE-TNC is dedicated to achieving the highest standards of research and technological advances, and we welcome the most innovative contributions that are capable of taking the field of neural computing to new heights.},
keywords = {neural computing, artificial intelligence (AI), machine learning (ML), neuromorphic computing, brain-inspired AI, cognitive systems, federated learning, explainable AI (XAI), deep learning, ethical AI, computational neuroscience},
issn = {3068-7519},
publisher = {Institute of Central Computation and Knowledge}
}
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