Call for Papers

Important Dates

• Paper submission deadline: November 17, 2025 23:59:59 EST
• Paper notification:January 5, 2026
• Camera-ready submissions deadline: TBA

Call for Papers

The PeRConAI workshop aims at fostering the development and circulation of new ideas and research directions on pervasive and resource-constrained machine learning bringing together practitioners and researchers working on the intersection between pervasive computing and machine learning, stimulating the cross-fertilization between the two communities. The PeRConAI workshop solicits contributions on, but not limited to, the following topics:

• Foundations of Advanced Machine learning algorithms and methods for pervasive systems subject to resource limitations addressing the following open challenges:
  • Distributed/decentralized and collaborative ML for resource-constrained devices (e.g., resource-efficient federated learning, imbalanced data distribution among devices);
  • Brain- and bio-inspired ML algorithms for pervasive computing (e.g., Echo State Networks, Liquid State Machines, Spiking Neural networks);
  • State-Space Models (SSMs) for resource-constrained devices; Learning Foundation models at the edge;
  • Physics-informed ML for efficient training in pervasive computing, Continual learning for distributed edge contexts;
  • Efficient compression of deep learning models for real-time inference;
  • Privacy-preserving and robust ML in distributed/decentralized learning for pervasive and resource-constrained scenarios;
  • Self- and Semi-supervised learning in pervasive and resource-constrained scenarios (e.g., energy efficient generative models);
  • Contrastive learning in distributed edge environments;
  • Split learning and Over-the-air computing for distributed/decentralized learning systems in pervasive and resource-constrained scenarios;
  • Pervasive and distributed unlearning methods;
• Applications of Advanced Machine learning algorithms, methods and approaches for pervasive computing under resource-limitations applied to the following application domains:
  • Health and well-being applications (e.g., activity recognition, health monitoring);
  • Anomaly/Novelty detection (e.g., Industry 4.0, predictive maintenance, condition monitoring, intrusion detection, privacy, and security);
  • Audio signal processing (e.g., sound event detection, speech recognition/processing). Wireless sensing (e.g., mm-wave radars);
  • Video streams processing on resource-constrained devices;
  • Natural Language Processing and Information Retrieval (e.g., conversational applications running on resource-constrained, mobile, or edge devices);
  • Intersection between mobile computing and ML/DL on resource-constrained devices. Remote sensing and Earth observation (resource-efficient satellite edge computing);
  • AI applications in UAV, e.g., agriculture, logistics, disaster relief, surveillance, and infrastructure inspection;
  • Any other real-world applications and case studies wherein the pervasiveness of resource-constrained devices is central for knowledge extraction.

Papers, written in IEEE LaTeX or Microsoft Word templates, must adhere to the formatting instructions specified here, must be 6 pages (10pt font, 2-column format), including text, figures, and tables.

All papers should be submitted electronically through the EDAS submission system: https://edas.info/N34025.