Wenchao Zhang, Xi'an University of Science and Technology

Yongze Song, Curtin University

Jiaxin Li, Chongqing University of Posts and Telecommunications

Remote sensing and Earth observation are advancing through integration of multi-source satellite and UAV data with machine learning and large language models. Physical machine learning—combining physics knowledge with data-driven approaches through physics-informed constraints and neural operators—enhances consistency and generalization. Geospatial foundation models and multimodal language systems enable knowledge transfer across sensors and support open-vocabulary perception and reasoning.

This special issue seeks original research on physics-informed learning, geospatial foundation models, and language-based intelligence for remote sensing applications. Submissions should advance methodological approaches, establish benchmarks, or demonstrate applications that improve accuracy, generalization, interpretability, and operational value across environmental monitoring, resource management, and disaster response. Studies combining these complementary approaches are particularly encouraged.

Appel publié par Expert Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Physics-informed and physics-guided learning
• Hybrid physical-ML models
• Neural operators and surrogate models
• Inverse problems
• Physical constraints
• Uncertainty-aware Earth-system modeling
• Geospatial foundation models
• Self-supervised pretraining
• LLMs, VLMs, and MLLMs
• Retrieval-augmented generation
• Open-vocabulary learning
• Image-text alignment
• Geospatial reasoning
• Multimodal fusion
• Multi-source data integration
• Cross-sensor alignment
• Multi-resolution learning
• Spatio-temporal modeling
• AI agents and multi-agent systems
• Tool use and planning
• Generative and diffusion models
• Data synthesis and restoration
• Autonomous EO workflows
• Domain adaptation and generalization
• Few-shot and zero-shot learning
• Continual learning
• Model compression and edge deployment
• Robustness and uncertainty quantification
• Explainability and benchmarking
• Classification and detection
• Segmentation and change detection
• Image retrieval and captioning
• Visual question answering
• 3D reconstruction
• Digital twins

Timeline

• February 28, 2027: Submission deadline

Malek Masmoudi, University of Sharjah

Patrick Siarry, Université Paris-Est Créteil

Omar Tujjar, International Society of Medical AI (ISMAI)

This special issue focuses on the integration of large language models and agentic AI systems in healthcare. The issue invites research on how these autonomous, reasoning-capable technologies can transform clinical practice, hospital operations, and healthcare management while promoting patient-centered care and sustainability.

Healthcare organizations increasingly deploy AI agents that combine perception of diverse clinical data with capabilities like planning, tool use, and collaboration to support clinicians, patients, researchers, and administrators. As adoption grows, rigorous evaluation and trustworthiness become critical to ensure these systems remain safe, auditable, and aligned with clinical standards.

The special issue welcomes original research articles, position papers, and validated case studies on both technical topics such as architectures and algorithms, and socio-technical topics including ethics, policy, and human factors across all stages of agentic AI deployment in healthcare.

Appel publié par Expert Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Foundations, Architectures, and Frameworks for Agentic AI in Healthcare
• LLM-Based Clinical Decision Support and Diagnostic Reasoning
• Multi-Agent Systems and Collaborative Healthcare Intelligence
• Multimodal Perception in Healthcare Agents
• Patient-Centered Agents and Digital Health Engagement
• Robotic and Computer-Assisted Surgery with Agentic AI
• Healthcare Operations, Administration, and Workflow Automation
• Drug Discovery, Biomedical Research, and Clinical Trials
• Evaluation, Safety, Trust, and Explainability of Healthcare Agents
• Ethics, Regulation, Governance, and Sustainable AI Deployment

Timeline

• January 31, 2027: Submission deadline