ACTIVE
Updated 31st January, 2026
Conference
ICINCI 2026 : 4th International Conference on Inventive Computing and Informatics
Conference Dates
June 10-12, 2026
Venue Location
Bangalore, India
About the Conference
Innovations including Machine Learning, Deep Learning, Neural Network, Autonomous Learning Systems, Internet of Things (IoT), and Blockchain have transformed how enterprises and businesses use data. The 4th International Conference on Inventive Computing and Informatics, ICICI 2026, provides a global platform for exchanging knowledge and findings in the methodology and applications of intelligent computing and informatics. Researchers/academicians/industrialists are invited to contribute to the conference by submitting novel and unpublished research contributions that illustrate novel research results, new initiatives, surveys, and industry experiences describing major breakthroughs in computing and Informatics.
Track 1: Machine Learning and AI for Data Analysis
Deep Learning for Time Series Analysis
Reinforcement Learning for Big Data Decision Making
Federated Learning for Privacy-Preserving AI in Healthcare
Explainable AI (XAI) for Data-Driven Decision Making
Generative Adversarial Networks (GANs) for Data Augmentation in Healthcare
Transfer Learning for Efficient Data Analysis
Graph Neural Networks (GNNs) for Complex Data Analysis
AutoML for Data Analysis Automation
Track 2: Neural Networks and Fuzzy Systems
Deep Reinforcement Learning for Complex Decision Making
Spiking Neural Networks (SNNs) for Energy-Efficient Computing
Hybrid Neural-Fuzzy Systems for Uncertainty Handling
Generative Adversarial Networks (GANs) for Data Synthesis and Augmentation
Convolutional Neural Networks (CNNs) for Image and Video Analysis
Recurrent Neural Networks (RNNs) for Sequential Data Analysis
Self-Supervised Learning for Pre-Training Neural Networks
Attention Mechanisms in Neural Networks
Track 3: Intelligent Agent Technologies
Multi-Agent Systems for Collaborative Problem-Solving
Agent-Based Modeling for Complex Systems
Reinforcement Learning for Agent-Based Systems
Explainable AI for Intelligent Agents
Human-Agent Interaction
Autonomous Agents for Robotics
Agent-Based Learning from Human Demonstrations
Track 1: Machine Learning and AI for Data Analysis
Deep Learning for Time Series Analysis
Reinforcement Learning for Big Data Decision Making
Federated Learning for Privacy-Preserving AI in Healthcare
Explainable AI (XAI) for Data-Driven Decision Making
Generative Adversarial Networks (GANs) for Data Augmentation in Healthcare
Transfer Learning for Efficient Data Analysis
Graph Neural Networks (GNNs) for Complex Data Analysis
AutoML for Data Analysis Automation
Track 2: Neural Networks and Fuzzy Systems
Deep Reinforcement Learning for Complex Decision Making
Spiking Neural Networks (SNNs) for Energy-Efficient Computing
Hybrid Neural-Fuzzy Systems for Uncertainty Handling
Generative Adversarial Networks (GANs) for Data Synthesis and Augmentation
Convolutional Neural Networks (CNNs) for Image and Video Analysis
Recurrent Neural Networks (RNNs) for Sequential Data Analysis
Self-Supervised Learning for Pre-Training Neural Networks
Attention Mechanisms in Neural Networks
Track 3: Intelligent Agent Technologies
Multi-Agent Systems for Collaborative Problem-Solving
Agent-Based Modeling for Complex Systems
Reinforcement Learning for Agent-Based Systems
Explainable AI for Intelligent Agents
Human-Agent Interaction
Autonomous Agents for Robotics
Agent-Based Learning from Human Demonstrations
Topics of Interest
Research papers are invited in, but not limited to, the following areas: