Research
Dr. Munish Bhatia's research focuses on the development of intelligent, secure, and scalable computational frameworks for next-generation systems, with a strong emphasis on Digital Twin technologies, Internet of Things (IoT), Artificial Intelligence, and Cloud-Fog Computing.
Research Overview
His work aims to bridge the gap between theoretical models and real-world industrial and societal applications. His research particularly explores AI-driven decision-making, secure data processing, and predictive analytics in cyber-physical systems. A significant portion of his work is dedicated to Digital Twin-based modeling and simulation, enabling real-time monitoring, optimization, and intelligent control of complex infrastructures such as smart cities, healthcare systems, and industrial environments.
He is also actively working on quantum computing-inspired optimization techniques and game-theoretic models to enhance system efficiency, security, and resilience in distributed environments. His research integrates simulation tools, machine learning models, and scalable architectures to address emerging challenges in sustainable and intelligent computing.
With a strong publication record in leading journals such as IEEE, Elsevier, Springer, and ACM, Dr. Bhatia is committed to advancing data-driven, secure, and adaptive systems for future technologies including Industry 4.0, 5G/6G networks, and smart infrastructure.
Research Interests
- Digital Twin Systems for Smart Infrastructure and Industry 4.0
- Artificial Intelligence and Machine Learning for IoT Applications
- Secure Cloud-Fog and Edge Computing Architectures
- Quantum Computing-inspired Optimization Techniques
- Game-Theoretic Models for Cyber-Physical Systems
- Data-driven Predictive Analytics for Smart Healthcare and Cities
Research Vision
The core vision of his research is to design adaptive, intelligent, and secure computational ecosystems that can respond to real-time challenges, optimize performance, and support sustainable innovation across industrial, urban, and healthcare domains.
Research Projects
Game-Theoretic Decision-Making in Digital Twin-Inspired Industry 4.0
Funding: ANRF (MATRICS)
Budget: ₹30,00,000
Status: Ongoing
AI-assisted Cloud Framework for Early Flood Prediction
Funding: Microsoft (AI for Earth)
Support: $6000 Azure Credits
Focus: AI-based environmental prediction using cloud infrastructure
Quantum Computing-inspired Vehicular Route Optimization
Funding: MeitY, Government of India
Support: $10,000 Amazon Quantum Credits
Focus: Optimization techniques for industrial and transport systems