About the Journal
The Newark Journal of Human-Centric AI and Robotics Interaction (NJHCAIR) is a peer-reviewed, open-access journal that explores the intersection of artificial intelligence, robotics, and human-centered design. Published biannually, NJHCAIR is dedicated to advancing research that prioritizes the seamless integration of intelligent systems and robotics into human environments, ensuring they are ethical, accessible, and beneficial to society.
The journal focuses on innovative approaches to designing AI and robotic systems that enhance human experiences, improve quality of life, and foster meaningful interactions.
NJHCAIR emphasizes interdisciplinary research, bridging the gap between computer science, robotics, cognitive science, psychology, and design. By promoting human-centric approaches, the journal aims to ensure that technological advancements align with human values, needs, and societal goals.
We welcome submissions from researchers, practitioners, and innovators worldwide, encouraging both theoretical insights and practical applications. Join us in shaping a future where AI and robotics empower and enrich human lives.
Journal Snapshot
Journal Name: Newark Journal of Human-Centric AI and Robotics Interaction (NJHCAIR)
ISSN: 1562-9570
Journal Initials: NJHCAIR
Research Scope: Human-robot interaction (HRI) and collaboration, Ethical AI and responsible robotics design, Social robotics and emotional intelligence, Assistive technologies for healthcare, education, and accessibility, User experience (UX) design for AI-driven systems, Trust, transparency, and explainability in AI and robotics, Multimodal interaction (voice, gesture, touch) in intelligent systems, AI and robotics in smart cities and urban environments
Publication Mode: Digital (On this Website)
Frequency: Annual (1 Volume a year)
Launch Year: 2021
Review Mode: Double Blind Peer Review
Plagiarism Allowed: 10% (as per Turnitin)
Coverage: Worldwide
Language: English
Current Issue
Articles
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Self-Supervised Learning for Real-World Data Scarcity in Industrial AI
Abstract Views 428PDF Downloads 5 -
AI-Optimized Distributed Caching for Ultra-Low-Latency Authorization Networks
Abstract Views 322PDF Downloads 8 -
Self-Healing Metadata Catalog via Graph Neural Anomaly Detection
Abstract Views 266PDF Downloads 1 -
Self-Supervised Session-Anomaly Detection for Password-less Wallet Logins
Abstract Views 271PDF Downloads 2 -
Zero-Touch Continuous Audit with Hybrid Symbolic-Neural Reasoning
Abstract Views 262PDF Downloads 2 -
Streaming Feature Stores and Real-Time ML Inference on Cloud-Native Infrastructure
Abstract Views 246PDF Downloads 2 -
Explainable Big Data Pipelines: Trust and Transparency in AI-Augmented ETL
Abstract Views 249PDF Downloads 2 -
Explainable Outlier Detection Systems for Fraudulent Financial Activity in Health Insurance Pipelines
Abstract Views 157PDF Downloads 0 -
A Trust-Aware Authentication Framework for Preventing Account Takeover Attacks in E-Commerce Platforms
Abstract Views 47PDF Downloads 0 -
Graph Neural Network-Based Detection of Organized Fraud in Insurance Claim Networks
Abstract Views 49PDF Downloads 0