We welcome papers on topics including, but not limited to:

Mobile Data Management
- Models, representations, and knowledge graphs for mobile, location, and trajectory data
- Indexing, search, query processing, and optimization for moving objects and mobile data
- Stream and event processing, real-time analytics, and context-aware mobile services
- Mobility simulation, trajectory generation, map matching, reconstruction, and mining
- Data quality, uncertainty, provenance, semantic enrichment, and visual analytics

AI and Analytics for Mobile Data
- Foundation models, LLMs, multimodal models, RAG, and natural-language interfaces for mobile data
- Generative AI, diffusion models, and synthetic mobility, trajectory, and sensor data
- Graph, representation, reinforcement, few-shot, and self-supervised learning
- Mobility forecasting, recommendation, behavior modeling, and activity recognition
- Learned data systems and federated, explainable, robust, and privacy-preserving AI

Mobile, Edge, IoT, and Ubiquitous Systems
- Data management for IoT, sensor, wearable, and pervasive systems
- Edge-to-cloud architectures, data placement, migration, caching, and resource allocation
- Resource-efficient and on-device learning, data reduction, model compression, and MLOps
- Mobile networking, middleware, scalability, latency, fault tolerance, and energy optimization

Emerging Data Management Paradigms
- Neuromorphic, quantum, and quantum-inspired computing for mobile data processing and optimization
- AI-native and semantic communication for distributed mobile intelligence
- Novel hardware/software co-design for edge and mobile data systems
- Spatial and spatio-temporal AI, GeoAI, and geospatial foundation models
- Embodied AI and human-AI or human-robot interaction involving mobility data
- Agentic mobile data management
- Vision-language / multimodal foundation models for mobility data

Indoor and Seamless Location Intelligence
- Indoor positioning, localization, tracking, and location determination
- Indoor spatial models, maps, knowledge graphs, indexing, and query processing
- Indoor trajectory reconstruction, map matching, navigation, and behavior analytics
- Seamless indoor-outdoor positioning, mobility analytics, and context-aware services

Multimodal and Multi-sensor Data Management
- Digital twins, Physical AI, simulation, and closed-loop decision support
- Agentic and multi-agent AI for mobile, robotic, and autonomous systems
- Data management for connected vehicles, drones, robots, and mixed-reality applications

Trustworthy Data Ecosystems
- Security and privacy for mobile, location, wearable, sensor, and IoT data
- Secure data spaces, federated data management, governance, sovereignty, and interoperability
- Responsible collection and use of human mobility and behavioral data
- Data economies, incentives, reputation, game-theoretic, and distributed-ledger approaches
- Fairness in mobility data

Applications, Evaluation, and Reproducibility
- Connected and autonomous transportation, routing, MaaS, smart spaces, and logistics
- Maritime, aviation, urban, environmental, health, industrial, and public-sector applications
- Experimental insights and benchmarks (providing new comparative perspectives of existing methods and new analysis tools/approaches).

All submissions need to follow IEEE Computer Society Proceedings Manuscript Formatting Guidelines. See templates here: https://www.ieee.org/conferences/publishing/templates.html.

The conference accepts two kinds of papers: Regular and Short.
Regular papers should present mature and substantial research contributions supported by thorough evaluation, while short papers should report promising preliminary results, novel ideas, work in progress, or focused contributions of significant interest to the community.
The page limits are
- Regular Papers: 10 pages, including all figures, tables and appendix.
- Short Papers: 6 pages, including all figures, tables and appendix.

- References do not count towards the page limit.
- Papers exceeding the page limit for their respective categories may be rejected without review. If there are any appendices, they count toward the page limit.
- The Review Process will be single-blind (i.e., the reviewers are not identified, while author names are listed in the submission).
- Submitted papers must present original, previously unpublished work and must not be under review or consideration for publication elsewhere at the time of submission. Submissions that violate these requirements may be rejected without review.

The proceedings of MDM 2027 will be published by IEEE via CPS (https://www.computer.org/conferences/cps) and will be included in the IEEE Xplore® Digital Library.

The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.