The International Conference on Innovations in Computational Intelligence (ICICI-2026) invites researchers, scholars, industry professionals, and practitioners from across the globe to submit their original and unpublished research papers. The conference will focus on advancements in computational techniques with a particular emphasis on artificial intelligence, machine learning, and other cutting-edge technologies. The final accepted papers will be considered for presentation in hybrid mode. All the accepted and presented papers will be submitted to IEEE Xplore (Scopus Indexed) for possible inclusion through IEEE CIS.

ICICI-2026 offers a platform for the exchange of ideas and dissemination of innovative research across a variety of tracks. Contributors are invited to submit their work under the following seven tracks:

All the accepted, registered, and presented papers will be submitted to IEEE Xplore (Scopus Indexed) through IEEE Computational Intelligence Society (CIS) for possible inclusion.

Track 1: Artificial Intelligence and Machine Learning

This track focuses on the latest developments in AI and machine learning algorithms, methodologies, and applications.

    Deep Learning and Neural Networks
    Reinforcement Learning
    AI in Healthcare
    Transfer Learning
    Machine Learning for Autonomous Systems
    Explainable AI
    AI for Natural Language Processing
    Ethical AI and Fairness
    AI in Robotics
    AI for Edge and Cloud Computing

Track 2: Data Science and Big Data Analytics

This track explores methods and technologies that help analyze, manage, and extract insights from large datasets.

    Predictive Modeling
    Big Data Frameworks and Platforms (Hadoop, Spark)
    Data Visualization Techniques
    Data Mining and Knowledge Discovery
    Big Data in Healthcare
    Real-time Data Processing
    Sentiment Analysis and Opinion Mining
    Data Cleaning and Preprocessing
    Data Privacy and Security in Big Data
    Machine Learning on Large-scale Data

Track 3: Internet of Things (IoT) and Smart Systems

This track focuses on smart systems and IoT applications across various industries.

    IoT Architectures and Frameworks
    Smart Cities and Infrastructure
    Edge Computing and IoT
    Sensor Networks and Data Management
    IoT for Healthcare and Wearables
    Industrial IoT Applications
    Security in IoT Networks
    AI in IoT Systems
    Smart Agriculture and Environment Monitoring
    Connected Vehicles and Autonomous Systems

Track 4: Cybersecurity and Cryptography

This track addresses emerging challenges in ensuring data security, privacy, and integrity in modern computational environments.

    Cryptography and Encryption Techniques
    Intrusion Detection and Prevention Systems
    AI and Machine Learning for Cybersecurity
    Blockchain and Distributed Ledger Technologies
    Security in Cloud Computing
    Cybersecurity in IoT Systems
    Threat Modeling and Risk Analysis
    Post-Quantum Cryptography
    Secure Software Development Lifecycle (SSDLC)
    Cyber-Physical System Security

Track 5: Natural Language Processing

This track covers advances in understanding, generating, and processing human language using computational methods.

    Large Language Models (LLMs)
    Machine Translation
    Speech Recognition and Synthesis
    Question Answering Systems
    Information Extraction and Retrieval
    Text Summarization
    Named Entity Recognition (NER)
    Sentiment Analysis
    Chatbots and Conversational AI
    Multilingual NLP

Track 6: Computer Vision

This track explores techniques enabling machines to interpret and understand visual information from the world.

    Image Classification and Recognition
    Object Detection and Tracking
    Facial Recognition
    Image Segmentation
    Video Analysis
    3D Vision and Reconstruction
    Medical Image Analysis
    Autonomous Vehicles and Vision Systems
    Augmented and Virtual Reality
    Generative Models for Images

Track 7: Computational Intelligence

This track focuses on nature-inspired algorithms and intelligent systems for solving complex problems.

    Neural Networks
    Fuzzy Logic Systems
    Evolutionary Algorithms
    Swarm Intelligence
    Genetic Programming
    Hybrid Intelligent Systems
    Neuro-Fuzzy Systems
    Particle Swarm Optimization
    Ant Colony Optimization
    Artificial Immune Systems

Track 8: Interdisciplinary Applications

This track encourages submissions that apply computational intelligence to diverse fields and cross-disciplinary research.

    AI in Healthcare and Medicine
    Computational Social Sciences
    AI in Education
    Environmental Monitoring and Climate Modeling
    Smart Agriculture
    AI in Finance and Economics
    Computational Biology and Bioinformatics
    AI for Sustainability
    Human-Computer Interaction
    AI Ethics and Policy