Nilesh Kumar Jadav
Papers
4
Total Citations
74
H-Index
3
About
Nilesh Kumar Jadav is a rising researcher at the intersection of artificial intelligence, cybersecurity, and Healthcare 4.0. His work focuses on securing next-generation critical infrastructure—from IoT-enabled smart hospitals to telesurgery systems—by integrating federated learning, blockchain, and explainable AI. In his most cited paper (39 citations), Jadav pioneered an artificial neural network-driven federated learning framework for heart stroke prediction under 5G, demonstrating how privacy-preserving AI can transform remote diagnostics. He further advanced secure data dissemination for IoT-enabled critical infrastructure (28 citations) by combining AI with blockchain to protect sensitive data flows. His recent contributions include X-NET, an explainable AI-based security framework for Healthcare 4.0, and a deep learning-orchestrated garlic routing architecture that ensures secure telesurgery operations. Jadav’s work consistently addresses the dual challenge of enabling intelligent automation while maintaining robust security and transparency—a critical balance for real-world deployment in healthcare and industrial IoT. With a growing citation footprint and a clear trajectory toward high-impact, applied AI security, Jadav is establishing himself as a key voice in the future of trustworthy, AI-driven healthcare systems.
Research Focus
Key Achievements
Top Papers
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