Assistant Professor
School of CS & AI
National Institute of Technology, Jamshedpur Jharkhand
7
Wireless Sensor Network, AI and ML, Energy Harvesting based sensor network
Wireless Sensor Network, AI and ML, Energy Harvesting based sensor network, Internet of Things
Mail: raghwendra@sru.edu.in
Ph.D in Electronics and Communication Engineering from National Institute of Technology Jamshedpur Jharkhand
M.Tech in Communication Engineering from National Institute of Technology, Agartala, Tripura
B.E in Electronics and Communication Engineering from RGPV, BHOPAL
Assistant Professor in School of CS & AI at S R University, Warangal, from 2024-07-01 to .
Teaching Assistant at National Institute of Technology, Jamshedpur Jharkhand, from 2019-08-01 to 2023-11-28.
Consultant at ECIL- Rapiscan LTD, Hyderabad, from 2011-12-31 to 2013-12-31.
Ph.D
UG
Singh, Raghwendra K., et al. "Performance analysis of energy harvesting- enabled relay networks in kappa- mu fading channels." Transactions on Emerging Telecommunications Technologies 35.4 (2024): e4976.
Ahmad, Tanzeel, Arnav Talaan, Vishal Gola, Subhranil Das, and Raghwendra Kishore Singh. "Advancing Early Diagnostic Accuracy for Alzheimer's Disease Through the Integration of Machine and Deep Learning Paradigms by Applying Multisource Datasets." In Proceedings of International Conference on Intelligent Systems and New Applications, vol. 2, pp. 42-46. 2024.
Dadhich, Arushi, Subhranil Das, and Raghwendra Kishore Singh. "Empirical Evaluation of Deep Learning Architectures in the Early Detection of Alzheimer's Disease through MRI Data Analysis." In Proceedings of International Conference on Intelligent Systems and New Applications, vol. 2, pp. 27-31. 2024.
Das, Subhranil, Rashmi Kumari, and Raghwendra Kishore Singh. "BeWell: An Integrated Mental Health Application Using LSTM Neural Network Model and Vader Sentiment Analysis for Emotional Well-Being." Journal of Microsystems and IoT 2, no. 2 (2024): 556-563.
Kumari, Rashmi, Subhranil Das, and Raghwendra Kishore Singh. "Ascending Complexity Task GAN and 3D Dense Convolutional Networks for Binary Classification of Alzheimer’s Disease." In International Conference on Data Analytics & Management, pp. 241-249. Singapore: Springer Nature Singapore, 2023.
Kumari, Rashmi, Subhranil Das, Raghwendra Kishore Singh, Anvi Kohli, Arya Sunil, and Arushi Dadhich. "Getting Started With Computational Drug Discovery: A Comprehensive Guide." In Converging Pharmacy Science and Engineering in Computational Drug Discovery, pp. 235-258. IGI Global, 2024.
Das, Subhranil, Rashmi Kumari, Ankit Kumar, Abhishek Thakur, and Raghwendra Kishore Singh. "Unveiling Superior Lane Detection Techniques Through the Synergistic Fusion of Attention-Based Vision Transformers and Dense Convolutional Neural Networks." In International Conference On Innovative Computing And Communication, pp. 15-27. Singapore: Springer Nature Singapore, 2024.
Kumari, Rashmi, Subhranil Das, Abhishek Thaku, Ankit Kumar, and Raghwendra Kishore Singh. "Autonomous vehicles." In Explainable Artificial Intelligence for Autonomous Vehicles, pp. 1-24. CRC Press, 2025.
Das, Subhranil, Rashmi Kumari, Abhishek Thakur, Raghwendra Kishore Singh, and Akriti Nigam. "Path Planning for Autonomous Ground Vehicles by Applying Modified Harris Hawks Optimization Technique." In International conference on soft computing for problem-solving, pp. 161-171. Singapore: Springer Nature Singapore, 2023.
Kumari, Rashmi, Subhranil Das, and Raghwendra Kishore Singh. "Agglomeration of deep learning networks for classifying binary and multiclass classifications using 3D MRI images for early diagnosis of Alzheimer’s disease: a feature-node approach." International Journal of System Assurance Engineering and Management 15.3 (2024): 931-949.
Kumari, Rashmi, Subhranil Das, Akriti Nigam, and Raghwendra Kishore Singh. "Multimodal diagnosis of Alzheimer’s disease based on volumetric and cognitive assessments." Multimedia Tools and Applications (2024): 1-24.
Singh, Raghwendra K., Nagendra Kumar, and Dharmendra Dixit. "On the ASER performance of RF energy harvesting multiple relay networks." Physical Communication 54 (2022): 101847.
Singh, Raghwendra Kishore, et al. "Outage Probability Analysis of Energy Harvesting-Enabled Three-Phase Two-Way Relaying System Over Mixed Fading Channels." 2023 International Conference on IoT, Communication and Automation Technology (ICICAT). IEEE, 2023.
Brain-Computer Interfaces (BCIs) offer a direct communication pathway between the brain and external devices, enabling control without the need for muscular activity. One of the key areas of BCI research is motor imagery (MI) classification, where a person’s imagined movements are detected and interpreted by a system. This process involves complex signal processing techniques that translate brain signals, specifically EEG (Electroencephalography) data, into actionable commands.
The integration of artificial intelligence in healthcare has paved the way for advanced diagnostic systems that leverage deep learning models to detect and diagnose diseases with high accuracy. One promising approach is the use of autoencoder-based deep neural networks, which are designed to learn efficient representations of data, making them particularly useful for medical diagnosis.
