CyberC promotes the research areas covered by the following tracks:

Track 1: AI Computing

    Machine Learning, Deep Learning, Autonomy, and Intelligence
    Supervised, Unsupervised, and Reinforcement Learning
    Deep Learning Architectures (CNNs, RNNs, Transformers, GANs)
    Explainable AI (XAI) and Trustworthy AI
    Meta-Learning, Few-Shot Learning, and Self-Supervised Learning
    AI Fairness, Ethics, and Bias Mitigation
    Large Language Models (LLMs) and Multimodal AI
    Text Generation, Summarization, and Machine Translation
    Sentiment Analysis and Opinion Mining
    Conversational AI and Chatbots
    Information Retrieval and Knowledge Graphs
    AI/ML for Robotics & Autonomous Systems
    AI/ML Applications in Science & Industry
    AI/ML for Data analytics, social media, and web mining
    AI for Web computing, intelligent and knowledge based systems

Track 2: Cyber Communications

    Next-Generation Wireless Networks (5G, 6G, and Beyond)
    Massive MIMO, Beamforming, and Millimeter-Wave Technologies
    AI/ML for Wireless Communication and Network Optimization
    Terahertz (THz) Communication and Free-Space Optics
    Sensor, IoT Connectivity and Communication Protocols
    Edge, Fog Computing, and Cloud Computing
    Low-Power Wide-Area Networks (LPWAN) and Ultra-Reliable Low-Latency Communication (URLLC)
    AI-Enabled Software/Cognitive Radio Networks
    Vehicular, UAV, and Satellite Communications
    Wireless Sensing, Localization, and Positioning
    Green & Sustainable Wireless Networks
    Quantum communications, and network computing resources
    Quantum Computing
    Spectrum sensing, fusion, decision-making and allocation
    Signaling process, PHY/link layer protocols and optimization

Track 3: Computer Vision

    Image Classification, Object Detection, and Segmentation
    3D Reconstruction and Scene Understanding
    Video Analysis and Action Recognition
    Image and Video Synthesis (GANs, Diffusion Models)
    Multimodal Learning and Vision-Language Models
    Transformer Models for Vision (ViTs, Swin, DINO)
    Self-Supervised and Few-Shot Learning for Vision
    Explainable AI (XAI) for Vision Applications
    Adversarial Robustness in Deep Vision Models
    AI in Medical Imaging and Radiology
    Image-Guided Surgery and Diagnostics
    Remote Sensing and Geospatial Vision Applications
    Vision for Autonomous Vehicles and UAVs
    SLAM (Simultaneous Localization and Mapping)
    Human-Robot Interaction and Assistive Vision
    AI for Image Enhancement and Super-Resolution
    Deepfake Detection and Synthetic Media Analysis
    Computational Imaging and Light Field Processing
    Augmented reality and virtual reality
    Multispectral, and hyperspectral imaging

Track 4: Security and Privacy

    Network and System Security
    AI-Powered Cyber Threat Detection & Response
    Malware Analysis and Intrusion Detection
    Zero-Trust Architecture and Adaptive Security
    Differential Privacy and Federated Learning
    Secure Multi-Party Computation and Homomorphic Encryption
    Blockchain and Decentralized Privacy Models
    Data Anonymization and De-Identification
    Cryptographic Protocols and Key Management
    Secure Cloud Computing and Storage
    Secure Authentication and Access Control
    Adversarial Machine Learning and AI Robustness
    AI for Cyber Threat Intelligence and Incident Response
    Deepfake and Synthetic Media Detection
    AI Governance, Ethics, and Fairness in Security
    Quantum Security and Cryptanalysis
    Privacy in Metaverse and Extended Reality (XR)
    Secure AI and Privacy-Preserving Generative Models