ICCISD 2026: IEEE International Conference on Computational Intelligence Systems and Devices
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Día de Entrega:
2026-01-12
Fecha de Notificación:
2026-03-08
Fecha de Conferencia:
2026-07-23
Ubicación:
Greater Noida, India
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ICCISD 2026 (IEEE International Conference on Computational Intelligence Systems and Devices) is an academic conference held in Greater Noida, India on 2026-07-23. The paper submission deadline is 2026-01-12. Acceptance notifications are sent on 2026-03-08.
ABOUT THE CONFERENCE
The IEEE International Conference on Computational Intelligence Systems and Devices (ICCISD -2026), technically sponsored by IEEE Uttar Pradesh Section and hosted by Sharda University, Greater Noida will be held on 23rd - 24th July 2026. The conference offers a comprehensive platform for researchers, practitioners, and industry professionals to explore advancements in Computer Science, Information Technology, and Computational Intelligence. The conference focuses on leveraging emerging technologies to address global challenges in sustainability. It covers a broad spectrum of cutting-edge topics and applications, emphasizing the integration of intelligent systems and sustainable practices.It is planned to submit the peer reviewed and selected papers of conference as proceedings for possible inclusion in IEEE Xplore.
THE OBJECTIVE OF THE CONFERENCE
The conference will provide an opportunity to the students, scholars, practicing engineers, academicians, and researchers to meet in a forum to discuss various issues and its future direction of various emerging areas of science and technologies and impacts on sustainable development. The objectives of the conference are as follows.
To bring together researchers, scientists, engineers, policymakers, and industry experts to present and discuss innovative solutions leveraging computational intelligence and evolutionary computation.
Foster the development of intelligent, adaptive, and energy-efficient devices and embedded systems that enhance IoT scalability, security, and sustainability.
Support the integration of AI and computational intelligence into sustainable systems including renewable energy, smart grids, climate modelling, and sustainable urban infrastructure.
To provide a platform for showcasing successful case studies of smart cities contributing to environmental, economic, and social sustainability.
Encourage breakthroughs in signal and image processing using AI to improve healthcare, remote sensing, multimedia, and real-time analytics applications.
Facilitate interdisciplinary collaboration among academia, industry, and government to accelerate the translation of intelligent technologies into real-world sustainable solutions.
Promote ethical, explainable, and responsible AI practices to build trust, transparency, and societal acceptance in emerging intelligent systems and technologies.
Promote cutting-edge robotics, automation, and human–machine interaction technologies aimed at improving industrial efficiency, environmental conservation, and safety.
The conference will cover a wide range of topics related to Smart Cities and Urban Development, Artificial Intelligence and Machine Learning, Advance Data Communication and Edge Computing, Cyber Security and Privacy in Sustainable Systems, Renewable Energy and Smart Grids, Robotics Automation and Networking, Digital Health and Smart Health Informatics. The conference invites original research papers (not being considered for publication elsewhere) of 5 pages in standard IEEE conference template in one of the following tracks (but are not limited to):
Track 1: Neural Networks, Deep Learning, and Reinforcement Learning
Explainable AI and Interpretable Deep Models
Foundation Models and Large Language Models (LLMs)
Prompt Engineering and Retrieval Augmented Generation
Neural Architecture Search and AutoML for Devices
Federated and Distributed Deep Learning on Edge Devices
Adversarial Robustness in Deep Learning Systems
Continual and Lifelong Learning Algorithms
Reinforcement Learning in Robotics and Control Systems
Generative AI for Realistic Data and Simulation
Multi-Modal Deep Learning (vision, speech, text, sensors)
Track 2: Fuzzy Systems, Evolutionary Computation, and Hybrid Intelligence
Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
Fuzzy Logic for Real-Time Decision-Making
Swarm Intelligence and Collective Behavior Models
Genetic Algorithms and Evolutionary Strategies
Multi-Objective Evolutionary Optimization
Bio-Inspired Algorithms (PSO, ACO, GWO, DE, Firefly, etc.)
Hybrid Evolutionary-Deep Learning Models
Evolutionary Computation for IoT Device Optimization
Fuzzy Systems for Uncertainty in Healthcare and Robotics
Evolutionary Game Theory for Smart Systems
Track 3: Intelligent Devices, Embedded Systems, and IoT Applications
AI-Powered Edge and Embedded Systems
Neuromorphic and Low-Power AI Chips
IoT Protocols for Scalability and Sustainability
Digital Twins for IoT Devices and Systems
Blockchain-Enabled Secure IoT Applications
Intelligent Wearable and Implantable Devices
Embedded Systems for Autonomous Vehicles and Drones
AI in Predictive Maintenance of IoT Devices
Cloud-Edge-IoT Integration Architectures
AI-Driven Energy-Efficient Smart Devices
Track 4: Robotics, Automation, and Human–Machine Interaction
Cognitive Robotics and Autonomous Decision-Making
Human–Robot Collaboration in Industry 5.0
Swarm Robotics for Environmental and Industrial Applications
Soft Robotics for Medical and Assistive Systems
Autonomous Navigation and Path Planning in Unknown Environments
AI-Enhanced Vision and Perception in Robots
Intelligent Drones and UAV Applications
Natural Language Interfaces for Human–Machine Interaction
Robotics for Disaster Response and Climate Applications
Ethics, Trust, and Safety in Human–Robot Systems
Track 5: Signal and Image Processing using Computational Intelligence
Deep Learning for Medical Image Analysis
AI for Satellite and Remote Sensing Applications
Generative Models for Image Enhancement and Synthesis
Multimodal Fusion of Audio, Video, and Sensor Signals
Hyperspectral and Multispectral Image Processing
Real-Time Video Analytics for Smart Surveillance
Adversarial Attacks and Defenses in Image Processing
AI-Driven Speech Recognition and Language Models
Edge-AI for Low-Latency Signal Processing
Virtual, Augmented, and Mixed Reality Signal Processing
Track 6: Cybersecurity, Data Privacy, and Trustworthy Systems
Privacy-Preserving Machine Learning (Federated, Differential Privacy)
AI for Intrusion Detection and Anomaly Detection
Blockchain for Security in IoT and Devices
Quantum-Safe Cryptography for Future-Proof Security
Zero-Trust Architectures in Intelligent Systems
Cyber-Physical Security in Smart Grids and Robotics
Secure Data Sharing and Compliance (GDPR, HIPAA)
AI-Powered Threat Intelligence and Cyber Defense
Explainable and Trustworthy AI for Security Applications
Risk Management and Resilient Design for Smart Devices
Track 7: Computational Intelligence for Sustainable Systems and Devices
AI for Climate Change Modeling and Prediction
Green AI and Energy-Efficient Machine Learning Models
Computational Intelligence for Renewable Energy Optimization
Smart Grid Management with AI-Driven Decision Making
Intelligent Transportation and Mobility Systems
AI for Water Resource Management and Agriculture
Waste Management and Circular Economy Systems
Disaster Prediction and Climate-Resilient Infrastructure
AI for Smart City Governance and Citizen Engagement
Computational Intelligence for Net-Zero and Sustainability Goals