AIECE-2026

The First Edition of the International Conference on AI for Electrical & Computer Engineering (AIECE-2026) provide a platform for the academicians/ researchers and policy makers to come up for exchange of research findings, analysis, information, and knowledge in areas which include but are not limited to:

I. AI in Power and Energy Systems

• Smart Grid Management using AI
• Renewable Energy Forecasting
• AI in Power Load Balancing
• Intelligent Fault Detection and Diagnostics
• Predictive Maintenance of Electrical Infrastructure

II. AI in Communication and Signal Processing

• Deep Learning in Signal Filtering and Enhancement
• AI-driven Wireless Communication Systems
• 5G/6G Network Optimization
• AI for Image and Speech Recognition
• Neural Networks in Audio and Visual Signal Processing

III. AI in Embedded Systems and VLSI

• AI-based Embedded System Design
• Intelligent FPGA and SoC Implementations
• Edge AI Architectures
• Machine Learning in Chip Design
• AI-accelerated Hardware Optimization

IV. AI in Robotics and Control Systems

• Reinforcement Learning for Autonomous Robots
• Adaptive Control Algorithms
• Swarm Intelligence in Robotics
• Human-Robot Interaction (HRI)
• Neural Network-Based Controllers

V. AI in Cybersecurity and IoT

• AI for Threat Detection and Network Security
• Intelligent Intrusion Detection Systems (IDS)
• AI in IoT Device Management
• Federated Learning in IoT Ecosystems
• Secure AI-based Blockchain Integration

VI. AI in Computer Vision and Pattern Recognition

• Real-time Object Tracking and Scene Understanding
• Facial Recognition and Emotion Analysis
• Medical Imaging and Diagnostics
• AI for Remote Sensing and Satellite Imagery
• Industrial Vision Systems

VII. AI in Education and Industry 4.0

• AI-Powered Educational Platforms
• Skill Mapping and Adaptive Learning Tools
• Predictive Analytics for Manufacturing
• Digital Twins and Smart Factories
• AI for Industrial Automation

VIII. Ethical AI, Policy & Governance

• Responsible AI in Engineering Practices
• Algorithmic Transparency
• Bias Mitigation and Fairness in AI Systems
• AI Policy Development for Engineering Applications
• Sustainable and Green AI Solutions

IX. AI in Smart Grids

• Load forecasting using AI and deep learning
• Fault detection and location using neural networks
• AI for energy theft detection and prevention
• Demand response optimization with machine learning
• AI-based distributed energy management systems

X. AI in Renewable Energy Systems

• Predictive modelling for solar and wind power generation
• AI for maximum power point tracking (MPPT) in PV systems
• Hybrid energy system optimization using AI
• Deep learning for weather and irradiance forecasting
• Intelligent control of battery energy storage systems

XI. AI in Electrical Machines and Drives

• Machine learning for fault diagnosis in induction motors
• AI-based speed control of DC and AC drives
• Predictive maintenance of electrical machines
• Intelligent torque and flux control in vector-controlled drives
• Reinforcement learning in motor control applications

X. AI in Power Electronics

• AI-based control of DC-DC and AC-DC converters
• Intelligent inverter design for grid-tied applications
• Fault detection in power electronic circuits using AI
• Predictive thermal management in power modules
• AI-optimized switching strategies to reduce harmonics

XI. AI in High Voltage Engineering

• AI for partial discharge detection and classification
• Insulation condition monitoring using ML techniques
• Expert systems for high voltage test result interpretation
• Image processing with AI for surface discharge analysisv

XII. AI in Power System Protection and Automation

• Deep learning for relay coordination and fault classification
• Adaptive protection schemes using reinforcement learningv
• AI-assisted SCADA systems for decision-making
• Intelligent islanding detection and reconfiguration

XIII. AI for Electrical Safety and Risk Management

• Predictive analytics for fire and arc flash risks
• AI models for equipment failure probability
• Smart wearables and sensors for electrical safety monitoring

XIV. AI in Power Quality Monitoring

• Harmonic analysis using ML/DL models
• AI for classification of power quality disturbances
• Load signature analysis for PQ event diagnosis

XV. AI in Electric Vehicle (EV) Power Systems

• Smart charging infrastructure using AI
• Battery State of Health (SoH) and State of Charge (SoC) prediction
• AI-based powertrain optimization
• Load management of EV charging in smart grids

XVI. AI for Grid Stability and Control

• Intelligent frequency and voltage control
• AI for dynamic load dispatch and economic operation
• Synchro phasor data analytics using AI
• Deep reinforcement learning in grid balancing