Welcome to the Journal of Artificial Intelligence and Robotics, a pioneering platform at the intersection of cutting-edge research, innovation, and technological advancements in the fields of artificial intelligence (AI) and robotics.
Mission Statement: At the core of our mission is the advancement of knowledge and understanding in AI and robotics. We strive to be a leading catalyst for the exchange of ideas, insights, and breakthroughs, fostering a global community of researchers, scholars, and practitioners dedicated to pushing the boundaries of intelligent systems and robotic technologies.
Our Commitment: We are committed to promoting excellence in research and scholarly contributions. The Journal of Artificial Intelligence and Robotics serves as a reputable and peer-reviewed outlet for original research articles, reviews, and discussions that shape the landscape of AI and robotics. Our commitment extends to providing a platform for diverse perspectives and methodologies, ensuring a comprehensive and inclusive dialogue in these rapidly evolving fields.
The peer-review process for the Journal of Artificial Intelligence and Robotics (JOAIR) is designed ...
Open access (OA) encompasses a set of principles and diverse practices that facilitate the ...
The Journal of Artificial Intelligence and Robotics (JOAIR) maintains a strict policy against plagiarism.
The Journal of Artificial Intelligence and Robotics (JOAIR) is a peer-reviewed scholarly publication ...
The role of Artificial Intelligence (AI) in laboratories is fundamentally changing. It is evolving from a passive data-processing tool into an active agent capable of autonomous planning, decision-making, and direct control of physical experiments. This transition from a “tool” to an “actor” represents a core, yet underrecognized, challenge for contemporary laboratory safety.
The rapid integration of Artificial Intelligence (AI), particularly generative models and large language models, is fundamentally reshaping contemporary academic research. While AI offers unprecedented capabilities for data analysis, automation, and knowledge discovery, its widespread adoption introduces significant ethical, methodological, and structural
The DISC personality framework, while widely adopted in applied settings, relies on a fixed rule-based classification method that may oversimplify individual behavioural profiles. This study explores whether machine learning can offer a more flexible, efficient, and accurate approach to DISC classification.
To design, implement, and evaluate a multilingual, voice-enabled Retrieval-Augmented Generation (RAG) chatbot that delivers personalized, clinically grounded information and answers patient questions about retinal detachment.
University of Crete, Medical School, Andrea Kalokerinou 13, Heraklion, Crete 715 00, Greece.
Research Scientist Intelligent Fusion Technology, Inc. Germantown, MD 20874, USA.
Architecture and Engineering College, Sichuan Institute of Industrial Technology, Deyang 618500, China.
Bioresource Technology Division, School of Industrial Technology, Universiti Sains Malaysia, Penang, Malaysia.
Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
Department of Control Engineering, Northeastern University, Shenyang, China.
Stroke Monitoring and Diagnostic Division, AtheroPoin, Roseville, California, USA.
Department of Electrical and Systems Engineering, Washington University, USA.
