Dr. Narendra Kumar

About

Dr. Narendra Kumar completed his M.Tech(Computer Science) from BIT Mesra Ranchi, and Ph.D.(Computer Science) from D.D.U Gorakhpur University. Narendra Kumar has more than 16 years’ rich experience in Computer Science & Engineering /Information Technology field. He is working at Amity University Jharkhand, Ranchi as an Associate Professor in the Department of Computer Science , His research area includes image processing, Optimizations techniques and the internet of things. Narendra is Editor of two books including publication like CRC Press, Taylor & Francis Group and Springer publication. He has published numerous research papers in international journals and conferences including IEEE, Springer, and Elsevier

Employment

• Amity University Jharkhand
  2023 - Present

Education

• Deen Dayal Upadhyaya Gorakhpur University Ph.D
  2013 - 2017

Projects & Funding

Projects & funding information is unavailable.

Publications (115)

• Saudi Arabia as a case of water-smart critical minerals: integrating desalination brine recovery with electric vehicle policy
  Sustainable Energy Technologies and Assessments 2026 DOI: 10.1016/j.seta.2026.105263
  +Save
• Adaptive Spatio-Temporal Deep Learning for Robust Cyber Threat Detection Across IoT Environments
  EAI Endorsed Transactions on Internet of Things 2026 DOI: 10.4108/eetiot.10791
  +Save
• Enhancing Cyber-Physical Resilience in Critical Infrastructure: A Low-Latency, AI-Driven Anomaly Detection Framework for the GERD
  Ssrn 2026 DOI: 10.2139/ssrn.6602743
  +Save
• Enhancing IoT Cybersecurity with Multi-Layer Deep Transfer Learning Approach for Intrusion Detection
  Journal of ICT Research and Applications 2026 DOI: 10.5614/itbj.ict.res.appl.2026.19.3.4
  +Save
• Interferometric synthetic aperture radar-artificial intelligence-based approach for groundwater level prediction in arid regions
  Hydrological Insights Synergizing Groundwater Models Remote Sensing and AI for Water Sustainability 2026 DOI: 10.1016/B978-0-443-36394-8.00004-2
  +Save
• Machine Unlearning for Trustworthy AI: A Systematic Review of Techniques, Challenges, and Applications
  Archives of Computational Methods in Engineering 2026 DOI: 10.1007/s11831-025-10436-z
  +Save
• Polyhistidine-Functionalized Ti–V–N Nanorod Interfaces for High-Sensitivity Solid-State pH Sensing: Mechanism and Stability Assessment
  IEEE Sensors Journal 2026 DOI: 10.1109/JSEN.2026.3722219
  +Save
• Real-Time Traffic Density Estimation Using YOLO-Based Deep Learning Models on Urban Surveillance Datasets
  Ssrn 2026 DOI: 10.2139/ssrn.6582140
  +Save
• Sustainable Wastewater Management in the Middle East: Energy Recovery and Aquifer Recharge Solutions
  Ssrn 2026 DOI: 10.2139/ssrn.6168271
  +Save
• Sustainable Wastewater Management in the Middle East: Energy Recovery and Aquifer Recharge Solutions
  Ssrn 2026 DOI: 10.2139/ssrn.6385989
  +Save