Introduction
This thematic issue focuses on cutting-edge research integrating Artificial Intelligence, Quantum Computing, Deep Learning, and Ensemble Learning to address emerging challenges in Computer Science and Engineering (CSE) and Electronics and Communication Engineering (ECE). As intelligent technologies rapidly evolve, there is a growing need for scalable, efficient, and robust solutions across computing, communication, automation, and embedded systems.
AI and deep learning enable advanced capabilities in pattern recognition, signal and image processing, cybersecurity, VLSI optimization, and autonomous systems, while ensemble learning improves prediction accuracy and system reliability. Quantum computing further introduces transformative paradigms for accelerated optimization, enhanced security, and high-dimensional data processing.
The issue invites interdisciplinary contributions on quantum-enhanced AI, intelligent signal processing, hybrid ML frameworks for communication networks, AI-driven VLSI design, IoT-enabled learning systems, and deep ensemble applications, fostering innovation across CSE and ECE domains.
Keywords
AI, Deep Learning , Quantum Computing, Ensemble Frameworks, pattern recognition, VLSI optimization, IoT-enabled learning systems
Sub-topics
AI, Deep Learning & Ensemble Frameworks
-
Deep learning architectures for engineering applications
-
Ensemble learning models for robust prediction and decision-making
-
Hybrid ML/DL frameworks for complex systems
-
Explainable AI (XAI) and trustworthy AI in engineering systems
Quantum Computing & Quantum-Inspired Models
-
Quantum-enhanced machine learning and deep learning
-
Quantum-inspired optimization algorithms
-
Quantum computing applications in signal processing and communications
-
Post-quantum cryptography and security frameworks
Signal Processing & Communication Systems (ECE Focus)
-
AI-driven signal and image processing techniques
-
Intelligent wireless and 5G/6G communication networks
-
ML-based modulation, channel estimation, and interference mitigation
-
Smart antennas and cognitive radio using AI
VLSI, Embedded Systems & Hardware Acceleration
-
AI-based VLSI design and optimization
-
Neuromorphic computing and hardware-aware deep learning
-
Embedded AI systems and edge intelligence
-
FPGA/GPU/ASIC acceleration for ML and DL models
IoT, Cyber-Physical Systems & Automation
-
AI-enabled IoT architectures and smart sensors
-
Edge–cloud collaborative intelligence
-
Autonomous systems and robotics using deep learning
-
Smart manufacturing and Industry 4.0 applications
Security, Optimization & Emerging Applications
-
AI and quantum-based cybersecurity solutions
-
Deep learning for fault detection and predictive maintenance
-
Optimization of complex engineering systems using hybrid models
-
Interdisciplinary applications bridging CSE–ECE domains
