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Important Dates

CALL FOR PAPER

Timeline

Important Dates

 Call for Papers Opens

 1st December 2025


 Paper Submission Deadline

 30th March 2026


 Notification of Acceptance

 21st May 2026


 Camera-Ready Paper Submission

 25th June 2026


 Early Bird Registration Deadline

 28th June 2026


 Regular Registration Deadline

 30th July 2026


 Conference Dates

 16th - 18th October 2026

Submission Guidelines

Authors are kindly invited to submit their formatted full papers including results, tables, figures and references.

Paper submissions will be done through Microsoft CMT.

Submit Paper

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.


Author Guideline for the Paper Submission : Advisory guidelines for the author to read before the submit paper.

Paper Submission Guidelines
Tracks

Conference Tracks – LEARN 2026

LEARN 2026 features a wide range of tracks covering Artificial Intelligence, Networking, Data Science, and Emerging Technologies, but is not limited to these areas. The conference welcomes all innovative and interdisciplinary research in computing, automation, and intelligent systems. Each track provides a platform for researchers, innovators, and industry professionals to share ideas, present original work, and foster collaboration. Participants can engage through presentations, workshops, and panel discussions, contributing to a vibrant exchange of knowledge across established and emerging fields.

Track 1: Artificial Intelligence & Machine Learning

  • Deep Learning Architectures
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Transformer Models & Attention Mechanisms
  • Natural Language Processing (NLP)
  • Sentiment Analysis & Text Mining
  • Speech Recognition & Synthesis
  • Reinforcement Learning & Q-Learning
  • Generative AI & GANs
  • Explainable AI (XAI)
  • AI in Healthcare & Bioinformatics
  • AI for Industry 4.0
  • Predictive Modeling & Forecasting
  • AI in Finance & Business Analytics
  • AI for Cybersecurity
  • AI in Education & EdTech
  • Cognitive Computing & Knowledge Representation
  • Meta-Learning & AutoML
  • AI for Social Good
  • TinyML & AI on Edge Devices
  • Hybrid AI Models (Symbolic + Data-driven)

Track 2: Networking & Communication Technologies

  • 5G / 6G Mobile Networks
  • Internet of Things (IoT) Networking
  • Edge Computing & Fog Computing
  • Cloud Computing & Hybrid Systems
  • Network Security & Privacy
  • Blockchain for Networking
  • Software-Defined Networking (SDN)
  • Network Function Virtualization (NFV)
  • Wireless Sensor Networks
  • Smart Cities & Smart Grids
  • IoT Protocols & Standards
  • Network Monitoring & Management
  • Ad Hoc & Mesh Networks
  • Low-Power Wide-Area Networks (LPWAN)
  • Vehicular Ad Hoc Networks (VANETs)
  • Satellite & Space Communications
  • Network Traffic Analysis & QoS
  • Cybersecurity in Communication Networks
  • AI for Network Optimization
  • Optical Networks & High-Speed Internet
  • Quantum Networking

Track 3: Intelligent Data Computing

  • Big Data Management & Storage
  • Predictive Analytics
  • Data Mining & Knowledge Discovery
  • Data Visualization & Dashboards
  • Cloud-based Data Analytics
  • Edge Analytics
  • Real-time Data Processing
  • Streaming Data Analytics
  • IoT Data Analytics
  • Text & Social Media Analytics
  • Healthcare Data Analytics
  • Financial Data Analytics
  • Data Governance & Ethics
  • Statistical Modeling & Inference
  • Machine Learning for Data Analytics
  • Graph Analytics & Networks
  • Anomaly Detection & Fraud Detection
  • Recommendation Systems
  • Reinforcement Learning for Decision Support
  • Geospatial & Location-based Analytics
  • Data-driven Cyber-Physical Systems

Publication & Indexing 2026

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Important Downloads

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