Call for Paper
International Conference on Artificial Intelligence and Machine Learning (AIML-2026) to be held at IIMT, Bhubaneswar, India, during 06th -07th, March, 2026 invites original papers from the academicians, researchers and industry practitioners from the fields of AI and Machine Learning. The primary goal of AIML-2026 aims at attracting scholars and professionals to present and publish up-to-date ideas and innovation in all areas related to Concurrent Engineering in various industries and in driving the new-generation economy, society, and government at large.
The scope of the conference has been kept wide but is not limited to:
Theme 1: AI & ML in Health care
- Predictive Analytics and Early Disease Detection
- Medical Imaging and Diagnostic Automation
- Personalized Medicine and Treatment Planning
- Clinical Decision Support Systems (CDSS)
- Natural Language Processing (NLP) in Healthcare
- AI in Medical Robotics and Surgery
- Remote Monitoring and Telehealth
- Healthcare Operations and Workflow Optimization
- Drug Discovery and Pharmaceutical Applications
- Ethics, Privacy, and Responsible AI in Healthcare
Theme 2: AI for Smart Cities & Urban Development
- Smart Transportation and Traffic Management
- Urban Planning and Infrastructure Optimization
- Energy Management and Sustainability
- Public Safety and Surveillance
- Environmental Monitoring and Air Quality Prediction
- Smart Governance and Citizen Services
- Water and Utility Management
- Building Automation and Smart Infrastructure
- Urban Mobility and Micromobility Solutions
- Ethical AI and Data Privacy in Smart Cities
Theme 3: AI in Media, Education & Entertainment
- Intelligent Tutoring Systems
- Automated Assessment and Grading
- Predictive Analytics for Student Performance
- AI in Educational Content Creation
- AI-Generated Media and Creative Content
- Natural Language Processing in Media
- Audience Engagement and Marketing
- AI for Non-Player Character (NPC) Behavior
- Procedural Content Generation
- Immersive Experiences with AR/VR
Theme 4: AI & ML for Social Good
- Environmental Protection and Climate Action
- Public Health and Wellbeing
- Inclusive and Accessible Education
- Poverty Alleviation and Economic Development
- Urban Planning and Smart Communities
- Justice, Human Rights, and Transparency
- Crisis Response and Humanitarian Aid
- Accessibility and Assistive Technologies
- Data Ethics and Inclusive AI for Social Good
Theme 5: AI on the Edge & IoT Integration
- Edge AI and Real-Time Decision Making
- TinyML and Low-Power Intelligence
- AI-Enabled IoT for Smart Homes and Buildings
- Smart Cities and Infrastructure Monitoring
- Industrial IoT (IIoT) and Manufacturing
- Healthcare and Remote Patient Monitoring
- Autonomous Vehicles and Mobility Systems
- Security, Privacy, and Federated Learning
- Agriculture and Environmental Monitoring
Theme 6: AI on Business Intelligence & Finance
- Predictive Analytics for Business Decision-Making
- AI in Financial Risk Management
- Intelligent Automation in Business Operations
- Customer Analytics and Personalization
- Algorithmic and Quantitative Trading
- Fraud Detection and Cybersecurity in Finance
- Financial Forecasting and Budget Planning
- Regulatory Compliance and Explainable AI (XAI)
- Sustainable Finance and ESG Analytics
Theme 7: AI & ML on Industrial Applications & Manufacturing
- Predictive Maintenance and Asset Health Monitoring
- Smart Manufacturing and Process Optimization
- AI-Powered Industrial Robotics
- Quality Control and Defect Detection
- Supply Chain and Inventory Optimization
- Digital Twins and Simulation Modeling
- Energy Efficiency and Environmental Impact
- Cybersecurity in Industrial Systems
- Industrial IoT and Edge AI Integration
- Human-Centric AI in Manufacturing
Theme 8: AI&ML on Deep Learning & Neural Networks
- Advances in Neural Network Architectures
- Natural Language Processing (NLP) and Language Models
- Computer Vision and Image Understanding
- Generative Models and Creativity
- Optimization, Training Techniques & Efficiency
- Deep Learning Applications in Industry
- Deep Learning on Edge and Mobile Devices
- Explainable and Responsible Deep Learning
- Self-Supervised, Unsupervised, and Reinforcement Learning
- Security and Robustness in Deep Learning
Theme 9: Ethics, Privacy & Responsible AI
- Fairness, Bias, and Discrimination in AI
- Explainable AI (XAI) and Interpretability
- Data Privacy and Protection in AI Systems
- Ethical Design and Deployment of AI Systems
- Governance, Accountability, and Policy
- Ethical Challenges in Generative AI
- Responsible AI in Scientific Research and Innovation
- Global Perspectives on AI Ethics
- AI Ethics Education and Awareness