About JOISS JAIML
JOISS Journal of Artificial Intelligence and Machine Learning (JOISS JAIML) is a distinguished peer-reviewed quarterly published journal dedicated to advancing the theory and practice of artificial intelligence (AI) and machine learning (ML). With a primary aim of fostering interdisciplinary collaboration and promoting innovative research, JOISS JAIML provides a platform for researchers, practitioners, and educators to explore cutting-edge developments in AI and ML technologies.
Artificial Intelligence (AI): Exploration of AI methodologies, algorithms, and applications across various domains, including natural language processing, computer vision, robotics, expert systems, and autonomous agents.
Machine Learning (ML): Advancements in ML techniques, including supervised learning, unsupervised learning, reinforcement learning, deep learning, and probabilistic graphical models, as well as their applications in data analysis, pattern recognition, and decision-making.
Double-blind Peer Review: To ensure the highest standards of quality and integrity in published research, JOISS JAIML implements a rigorous peer review process, offering unbiased evaluation and providing constructive feedback.
Interdisciplinary Perspective: To address complex research challenges and facilitate innovative solutions, collaboration across diverse disciplines is employed, integrating AI and ML methodologies.
Global Reach: To exchange ideas, share insights, and collaborate on advanced research in AI and ML technologies, the journal provides an international platform for researchers, practitioners, and educators.
JOISS JAIML is designed for a broad spectrum of users, including researchers, academics, engineers, and professionals working in the fields of artificial intelligence, machine learning, data science, computer science, and related disciplines.
Our editorial team is committed to maintain the highest of standards of excellence, integrity, and inclusiveness, so that JOISS JAIML can continue its position as a leader in the field and the profession.
Dr. Swapnil Parikh has a wealth of experience including Associate Dean for Doctoral Studies and Research. Dr. Parikh received his Doctor of Philosophy in Computer Engineering from C. U. Shah University, completed his Master of Engineering in Computer Engineering from Dharmsinh Desai University, and has a Bachelor of Engineering from Pune University. Dr. Swapnil Parikh is the recipient of the United Kingdom’s Royal Academy of Engineering research grants and has authored several research papers published by renowned journals including Springer and the Institute of Electrical and Electronics Engineers. Dr. Parikh has also published two patents and his research interests include machine learning, data science, cloud computing, IoT, and Big Data.
The primary objective of JOISS Journal of Artificial Intelligence and Machine Learning (JOISS JAIML) is to establish itself as a recognized platform for top-ranked research and the exchange of ideas concerning the latest advancements in artificial intelligence and machine learning technologies.
The scope of JOISS JAIML encompasses, but is not limited to, the following areas:
Artificial Intelligence Techniques:
Machine Learning Technologies:
Integration of Artificial Intelligence and Machine Learning:
Applications Across Diverse Domains:
Recent Advancements:
Types of Contributions Accepted
JOISS JAIML welcomes the following types of contributions:
Peer-reviewed academic research platform dedicated to scholarly research by researchers, practitioners, and students worldwide. Explore, collaborate, and share insights to enrich knowledge and enhance professional practices for a global impact
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Copyright © 2024 by JOISS Research. All Rights Reserved.
Website Design & Developed By UML Digital
