Dr. Santosh Kumar

About

Dr. Santosh Kumar is an Associate Professor in the Computer Science and Engineering discipline. Prior to joining IIIT-NR, Dr. Santosh Kumar was a Ph.D. scholar in the Department of Computer Science and Engineering, IIT (B.H.U.), Varanasi, Uttar Pradesh, India. He is an active member of the Computer Society and the Association for Computing Machinery.
He has published over 45 journals (SCI-index journals) and conference papers (including 2 tier-1 international conferences (ACM Multimedia-2016 and Mobisys-2016); filed 1 patent; and written 14 book chapters in edited books (Springer publication and IGI publication).


His research interests include Blockchain, Federated Learning, Quantum AI, Computer vision, Pattern recognition, Digital image processing, Video processing, Swarm Intelligence, bio-inspired computing, artificial intelligence, operating systems, and theoretical computer science.

Employment

• Dr Shyama Prasad Mukherjee International Institute of Information Technology Assistant Professor
  2017 - 2021

Education

• Birla Institute of Technology Master of Engineering (M.E.)
  2010 - 2012
• Ajay Kumar Garg Engineering College B.Tech.
  2004 - 2008
• IIT (B.H.U) Varanasi Ph.D.
  ? - 2017

Projects & Funding

Projects & funding information is unavailable.

Publications (83)

• MyoCI: Computational Intelligence for Early Detection of Myocardial Infarction Using Text Analysis Through Clinical Data
  2026 DOI: 10.1007/978-3-031-93709-5_20
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• A Lightweight Deep Neural Network Framework for Early Diagnosis of Multivariate Respiratory Diseases
  2026 DOI: 10.1007/978-981-96-6941-7_15
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• Empowering Remote Healthcare With Federated Learning for Early Diagnosis of Pulmonary Disease
  IEEE Internet of Things Journal 2025 DOI: 10.1109/JIOT.2025.3553999
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• FuzzyGuard: A Novel Multimodal Neuro-Fuzzy Framework for COPD Early Diagnosis
  IEEE Internet of Things Journal 2025 DOI: 10.1109/JIOT.2024.3467176
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• Wireless Power Transfer Technologies, Applications, and Future Trends: A Review
  IEEE Transactions on Sustainable Computing 2025 DOI: 10.1109/TSUSC.2024.3380607
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• A Deep Learning Approach for Early Stress Detection Using Electrodermal Activity Through Wearable Devices
  2025 DOI: 10.1007/978-3-031-87657-8_4
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• Adaptive Node-Oriented Data Placement for Heterogeneous Hadoop Clusters
  IEEE Access 2025 DOI: 10.1109/ACCESS.2025.3565759
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• Advanced Framework for Early Congestive Heart Failure Detection Using Electrocardiogram Data and Ensemble Learning Models
  2025 DOI: 10.1007/978-3-031-78195-7_25
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• Deep Learning Framework for Early Diagnosis of COPD and Respiratory Diseases Using Lung Sound Analysis
  2025 DOI: 10.1007/978-3-031-81821-9_17
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• Hybrid CNN-LSTM Framework for Enhanced Congestive Heart Failure Diagnosis: Integrating GQRS Detection
  2025 DOI: 10.1007/978-3-031-78398-2_28
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