Conference Information

MLICOM 2026: EAI International Conference on Machine Learning and Intelligent Communications

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Submission Date:
2026-08-31
Notification Date:
2026-09-20
Conference Date:
2026-11-07
Location:
Sanya, China
Years:
Viewed: 16206   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

49.4 / 100
Ranked #1,640 of 5,650 conferences · Top 30%

#162 of 734 in Artificial Intelligence & Machine Learning #235 of 862 in Networks & Communications

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
62
Community attention (10%)
12
Public record completeness (15%)
55

Inputs used: Editions on record: 9 · Researchers who opened this page in the past 24 months: 4

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-04

Call For Papers

MLICOM 2026 (EAI International Conference on Machine Learning and Intelligent Communications) is an academic conference held in Sanya, China on 2026-11-07. The paper submission deadline is 2026-08-31. Acceptance notifications are sent on 2026-09-20.

Scope Emerging artificial intelligence (AI) and machine learning (ML) technologies, coupled with advanced intelligent communications, are driving a paradigm shift across academic research and industrial applications. From multi-modality learning to federated intelligence, these technologies are not only revolutionizing wireless communication systems (e.g., physical layer optimization, intelligent decision-making, and secure data transmission) but also enabling deep integration with diverse fields such as healthcare, industry, manufacturing, education, culture, governance, and digital humanities. The integration of ML and intelligent communications breaks through traditional domain boundaries—for instance, realizing secure transmission of medical data via federated learning, optimizing industrial IoT communication for smart manufacturing, and facilitating cross-cultural humanistic exchange through intelligent language processing. MLICOM 2026 aims to build a comprehensive academic platform that bridges ML/AI algorithms, intelligent communication technologies, and cross-domain applications. We welcome high-quality original research papers (theoretical, experimental, or application-oriented) focusing on recent advancements, challenges, and innovative solutions at the intersection of ML and intelligent communications. By covering a broad spectrum of fields including digital humanities, the conference seeks to foster interdisciplinary dialogue among academia, industry, and public sectors, and serve as a catalyst for the development of next-generation intelligent communication systems and their practical deployments. Topics 1. ML & Intelligent Communications Foundations Intelligent cloud / edge / cloud-edge collaborative communications ML-driven resource allocation (spectrum, power, computation, bandwidth) Green and energy-aware intelligent communications (sustainable network design) Intelligent software-defined radios (SDR) and flexible communication architectures Intelligent massive MIMO, beamforming, and dynamic antenna configuration Cooperative and distributed coding & signal processing for intelligent networks Wireless sensor networks (WSN) and IoT: ML-optimized data transmission Satellite and radar communications: intelligent signal processing and anti-interference Cognitive radio networks: ML-based spectrum sensing and sharing Federated learning (FL) and distributed learning for secure communication systems Multi-modality learning for cross-media communication (text, image, audio, video) Pre-trained models and transfer learning in intelligent communications Generative AI for communication content generation and error correction ML-driven network security, privacy preservation, and trust management 2. Cross-Domain Applications of ML 2.1 Industry & Manufacturing Industrial IoT (IIoT) communication optimization for smart factories ML-driven predictive maintenance via real-time industrial data transmission Intelligent communication in collaborative robotics and automated production lines 2.2 Education & E-Learning Intelligent remote teaching communication platforms (adaptive bandwidth allocation) ML-based personalized learning: communication optimization for educational data Secure transmission of educational big data and cross-institutional collaboration AI-driven interactive communication tools 2.3 Government & Public Services Smart governance communication platforms Secure communication for e-government AI-driven traffic and transportation communication Environmental monitoring: ML-based communication for sensor networks 2.4 Other Emerging Applications Intelligent unmanned systems (vehicles, drones): communication and adaptive sensing Accessible communication: ML-optimized solutions for people with disabilities ML-based semantic communication and cultural adaptation Digital archaeology: communication optimization for remote sensing data AI-assisted preservation of endangered languages: intelligent speech and text communication ML-based analysis of humanistic communication patterns 3. Other Relevant Topics Datasets and evaluation metrics for ML-empowered intelligent communications Low-resource language processing in cross-lingual communication Edge AI for resource-constrained communication devices Quantum machine learning for next-generation secure communications Ethical and regulatory issues of AI-driven intelligent communications
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