ICAIET 2027 (International Conference on Artificial Intelligence and Emerging Technologies) is an academic conference held in Odisha, India on 2027-01-13. The paper submission deadline is 2026-07-31. Acceptance notifications are sent on 2026-08-30.
The International Conference on Artificial Intelligence and Emerging Technologies (ICAIET-2027) is dedicated to advanced research in Artificial Intelligence, Machine Learning, Data Science, IoT, Blockchain, Network Security, Cloud Computing, and related emerging technologies. The conference aims at bringing together the researchers, scientists, engineers and research scholars from all areas of engineering and technology, to provide an international forum to exchange their ideas, foster collaboration, practical developments experiences and cover new grounds. The conference will feature invited talks by eminent researchers from around the world, technical paper sessions, poster sessions, demos, tutorials and workshops. Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore's scope and quality requirements. Prospective authors are encouraged to submit their original research contributions in IEEE format. Papers submitted to ICAIET 2027 should contain original research/study and should not have been published or submitted for publication elsewhere. The IEEE anti-plagiarism policy is applicable to all submissions. At least one author of each accepted paper must register for the conference and present his/her paper.
Conference Tracks
(The tracks in the conference include the following - but not limited to)
Artificial Intelligence (AI) and Applications
•Generative AI and Explainable AI.
•Overview of foundational and cutting-edge AI techniques.
•Applications in healthcare, robotics, gaming, and more.
•Ethical considerations and fairness in AI implementations.
•Advanced AI algorithms and their practical implementations.
•Exploring reinforcement learning and its use cases.
•Challenges in deploying AI systems in real-world scenarios.
•Integration of AI in smart cities and transportation.
Machine Learning and Data Science
•Supervised, unsupervised, and reinforcement learning techniques.
•Feature engineering and model optimization strategies.
•Exploring clustering, classification, and regression tasks.
•Data mining methodologies for pattern discovery in large datasets.
•Application of ML in business, finance, and scientific research.
•Tools and libraries for building and training ML models.
•Real-world case studies of ML deployment.
Computer Vision and Image Processing
•Techniques for image recognition, segmentation, and classification.
•Role of deep learning in computer vision advancements.
•Applications in autonomous vehicles, surveillance, and AR/VR.
•Pre-processing techniques like filtering, edge detection, and transformation.
•Challenges in object detection, tracking, and pose estimation.
•Development of real-time vision systems.
•Integrating computer vision with IoT and robotics.
Natural Language Processing (NLP)
•Advances in sentiment analysis, text summarization, and machine translation.
•The role of transformers and attention mechanisms in NLP.
•Sentiment and emotion detection in textual data.
•Applications in chatbots, virtual assistants, and speech recognition.
•Challenges in understanding and generating human-like text.
•Addressing bias and ethical concerns in NLP systems.
•Tools and datasets for NLP research and application.
IoT and Cyber-Physical Systems
•Role of IoT in smart homes, healthcare, and industrial automation.
•Design and optimization of cyber-physical systems.
•The role of AI and ML in IoT.
•Protocols and standards in IoT connectivity and interoperability.
•Challenges in scalability and reliability of IoT networks.
•Integration of edge and fog computing with IoT systems.
•Security concerns in IoT and cyber-physical implementations.
Blockchain Technology, Network Security, and Privacy
•Cryptographic techniques for secure communication.
•Secure authentication and access control mechanisms.
•Privacy-preserving data-sharing and storage mechanisms.
•Blockchain-enabled Resilience and Applications Securing cloud, distributed, and blockchain-integrated systems.
•Intrusion detection systems (IDS) and decentralized approaches with blockchain.
•The role of AI, ML, and blockchain in enhancing cybersecurity.
Sequential, Parallel, Distributed, and Cloud Computing
•Differences between sequential, parallel, and distributed systems.
•Scalability and load balancing in distributed systems.
•Cloud architecture and service models (IaaS, PaaS, SaaS).
•Task scheduling and resource allocation in parallel systems.
•Applications of distributed computing in big data processing.
•Virtualization and containerization in cloud environments.
•Energy efficiency and optimization in computing systems.
Special Tracks
Emerging Technologies in Education
•Role of AI in personalized and adaptive learning.
•Gamification and its impact on student engagement.
•Virtual and augmented reality in immersive learning environments.
•Challenges in integrating technology with traditional education systems.
•Applications of blockchain for credentialing and record-keeping.
•Use of data analytics to predict and improve learning outcomes.
•Development of inclusive and accessible educational technologies.
AI in Finance and Business Analytics
•Predictive analytics for financial decision-making.
•AI-based fraud detection systems in banking and e-commerce.
•Optimization of investment portfolios using ML algorithms.
•Applications in credit scoring, risk assessment, and underwriting.
•Chatbots and virtual assistants for customer service in finance.
•Enhancing supply chain management using AI insights.
•Ethical concerns and transparency in AI-driven financial systems.
AI for Sustainable Development and Societal Impact
•Role of AI in addressing climate change and resource management.
•Smart agriculture through AI-powered analytics and robotics.
•Applications in healthcare accessibility and remote diagnostics.
•Addressing inequalities through AI-driven education and job matching.
•Development of sustainable urban infrastructures with AI.
•Ethical considerations in AI-driven societal changes.
•Case studies on AI applications in humanitarian efforts.
No comments yet.