The International Conference on Applications of AI and Machine Learning (ICAML-2025) invites researchers, industry experts, and scholars from around the globe to submit their original, unpublished papers. ICAML-2025 serves as a platform for disseminating cutting-edge research, pioneering concepts, and emerging applications across various domains of Artificial Intelligence and Computing. We welcome high-quality contributions that push the boundaries of AI, harnessing novel approaches, algorithms, and techniques for real-world challenges.
Topics of Interest:
Submissions are encouraged in, but not limited to, the following areas:
1. Healthcare and Biomedical Applications
Deep learning for personalized medical treatments, AI for patient-specific diagnostics and prognostics, generative models for drug synthesis, reinforcement learning in treatment optimization, energy-efficient AI models for wearable health devices, cloud-based AI platforms for remote health monitoring, soft computing techniques for uncertainty handling in medical data.
2. Smart Cities and Urban Analytics
AI for autonomous urban transport systems, predictive analytics for energy demand in smart grids, edge computing for real-time urban monitoring, AI-driven public policy optimization, distributed IoT networks for urban sustainability, cloud computing for scalable smart city applications, fuzzy logic for adaptive urban planning.
3. Agriculture and Environmental Sciences
AI-based soil quality analysis and irrigation planning, computer vision for livestock monitoring, reinforcement learning in autonomous farming robotics, scalable AI models for climate-resilient agriculture, geospatial analysis for biodiversity conservation, cloud-enabled farm management systems, evolutionary algorithms for pest and disease control.
4. Natural Language Processing (NLP)
Transformers for low-resource language processing, domain-specific language models (e.g., medical, legal), explainable AI in NLP applications, AI for multilingual conversational agents, sentiment detection for environmental and social policy insights, cloud-based NLP solutions for large-scale data processing, hybrid soft computing approaches for linguistic ambiguity resolution.
5. Computer Vision and Image Processing
GANs for medical image synthesis, real-time vision systems in robotics, multimodal learning combining vision and textual data, AI-driven content moderation systems, video analytics for crowd safety and anomaly detection, cloud-based image processing for large-scale datasets, neuro-fuzzy techniques for image enhancement and restoration.
6. Cybersecurity and Privacy
Federated learning for privacy-preserving cybersecurity, AI for real-time phishing detection, adversarial attack resilience in AI models, blockchain-enabled secure data sharing, anomaly detection in IoT networks, cloud security frameworks using AI, soft computing for intrusion detection in complex environments.