Dr. Bhawani Sankar Panigrahi

@gitam.edu

Assistant Professor , Department of Computer Science and System Engineering
GITAM University

Dr. Bhawani Sankar Panigrahi


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https://researchid.co/bspanigrahi.cse
Sankar Panigrahi, Assistant Professor in department of Computer Science & System Engineering at GITAM School of Computer Science & Engineering, GITAM University, Vishakhapatnam, India. He received his B.Sc. in Computer Science from Berhampur University in 2001 with distinction, M.Sc. Computer Science from University of Madras in 2003, M.Tech. Degree in Computer Science & Engineering from KIIT University Bhubaneswar in 2006 and PhD from Kalinga University, Raipur. He is currently member of different professional society like IEEE Photonics Society, ISTE, IE, CSTA and many more. He is having more than 20 Years of UG and PG teaching experience and has published 4 Indian and 1 International Patents(Granted), and 54 research papers in international and national journals and conferences. His research areas includes Machine learning, Biometrics security systems, IOT, Digital Image processing, Data Minning and Pattern clustering. He Received Education Excellence AWARD by SIMATS Univ

EDUCATION

Post Doctorate, Ph.D, Mtech

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems
47

Scopus Publications

529

Scholar Citations

13

Scholar h-index

15

Scholar i10-index

Scopus Publications

  • Explainable Artificial Intelligence With Cloud and Blockchain-as-a-Service Model for Consumer Electronics in Connected Healthcare
    Sirisha Potluri, Bhawani Sankar Panigrahi, Sachi Nandan Mohanty, Awad Albalawi
    IEEE Transactions on Consumer Electronics, 2026
    Smart and connected wearables, Internet of Things-enabled devices, intelligent health equipment, and mobile applications are significant in connected healthcare by empowering smart and real-time patient monitoring, predictive and forecasting analytics, tailored and customized treatments. While these practices deliver valuable and substantial insights, constraints associated with security, privacy, scalability, availability, and transparency in artificial intelligence-based decision-making persist as considerable barriers to adoption in healthcare provision. To deal with these limitations, this research presents an explainable federated learning model combined with Cloud, Blockchain, explainable artificial intelligence, and optimization techniques to design secure, transparent, decentralized, and resilient-enabled healthcare. The cloud platform offers scalable and available data storage with low-latency real-time analytics. Blockchain guarantees decentralized, secured, tamper-proof block management and privacy-preserving access management. The proposed framework is a robust healthcare ecosystem and is a trio of cloud, blockchain, and explainable artificial intelligence with interpretable deep learning, a parallelized inference pipeline, data integrity, and compliance. The proposed system validates measurable enhancements, achieving 93% prediction accuracy, 30% enhanced interpretability, 25% lowered latency, and 40% higher data integrity, assessed relative to the existing intelligent healthcare systems. By integrating availability, explainability, privacy, security, latency, and scalability, this system provided a functional path for implementing transparent, secure, and connected healthcare ecosystems driven by consumer electronics.
  • Corrigendum to “A new method for prediction of Vigna mungo millet disease based on deep learning” (Current Plant Biology, (2025), 44, C, (100562), (S2214662825001306), 10.1016/j.cpb.2025.100562)
    Raghvendra Kumar, Chandrakanta Mahanty, Bhawani Sankar Panigrahi, S. Gopal Krishna Patro, Tran Manh Tuan, Le Hoang Son
    Current Plant Biology, 2026
  • Integrating User Relationships and Features for Intelligence of Social Things Aware Information Diffusion Prediction
    Bhawani Sankar Panigrahi, Mohammed E. Seno, Balasubramani Murugesan, Omar Isam, Vemula Jasmine Sowmya, K.D.V. Prasad, Deepak Gupta, Jumaniyazov Inomjon Turayevich, Richard Rivera
    IEEE Transactions on Computational Social Systems, 2026
    In the intelligence of social things (IoST) paradigm, where interconnected devices and social networks create a dynamic ecosystem, understanding information diffusion is essential. IoST integrates user interactions, device behaviors, and contextual factors, adding complexity to information networks and necessitating accurate prediction models. This work analyses user behavior in terms of both group and individual relationships and presents an information propagation prediction model that combines information propagation topology features with user relationship representations. Information diffusion prediction analyzes patterns of spread in networks to understand and forecast propagation processes. Existing studies emphasize social and dynamic influence relationships within user groups but often neglect user similarity in group relations and intrinsic factors affecting individual sharing decisions. To address these gaps, a novel model is proposed, combining user relationship representations and diffusion topological features. At the group level, a user cooccurrence graph captures similarity relationship, integrating these with diffusion topology to analyze group interactions. At the individual level, user-specific feature representations and influence factor vectors address intrinsic motivations for sharing. Experimental results validate the model’s efficacy, achieving performance improvements on public datasets. On the Memetracker dataset, the model increased MAP@k by 6.54% and hits@k by 2.75%, demonstrating its ability to capture both group and individual dynamics for enhanced diffusion prediction.
  • A new method for prediction of Vigna mungo millet disease based on deep learning
    Raghvendra Kumar, Chandrakanta Mahanty, Bhawani Sankar Panigrahi, S. Gopal Krishna Patro, Tran Manh Tuan, Le Hoang Son
    Current Plant Biology, 2025
    Various viral illnesses impact plant development, causing farmers to lose a lot of revenue. Early diagnosis and prediction of these viral infections can help farmers take preventive measures and mitigate the impacts on crop productivity and quality. As a result, there is a need to develop automated tools for identifying viral infections in crops that analyze symptoms at various parts of the plant. The prediction of Vigna Mungo millet disease is critical for food security and agricultural sustainability. In this article, a practical and reproducible pipeline is proposed for the automatic detection of leaf diseases in Vigna mungo, which combines ImageNet-pretrained CNN backbones (GoogleNet, MobileNetV2, Xception) with a lightweight recurrent classifier. Our original contribution is to treat convolutional feature maps as ordered spatial sequences and to use a single-layer LSTM to model spatial dependencies across the leaf surface. This design more effectively captures the diffuse and irregular lesion patterns characteristic of viral infections. To address the modest dataset size (660 images, with 220 images per class), we freeze the backbones, apply augmentation on the fly, and utilize dropout, gradient clipping, and early stopping. The models were evaluated with stratified 5-fold cross-validation and statistical tests. It has been revealed that the Xception with LSTM attained the best mean performance (98.34% ± 0.34% across folds; peak 98.48% on the test split). Vigna Mungo/ Black gram plant leaf diseases can significantly reduce crop yields, leading to lower food production and higher food prices. By detecting and identifying these diseases early on, farmers can take appropriate measures to control the spread of the disease and prevent crop losses. • We proposed a hybrid Deep Learning for leaf disease detection of Vigna Mungo plant. • A hybrid Deep Learning model (GoogleNet, MobileNetV2, and Xception) with RNN is designed. • The Xception-RNN network achieved the highest accuracy of 98.48%. • The suggested approach forecasts the health of a plant's leaves and categorizes them into healthy, anthracnose, and yellow mosaic.
  • Designing an empirical grid-connected PV system based on FLC-MPPT approach for local community use
    S. Sathea Sree, M. Muthalakshmi, Prasath Alias Surendhar S, A. Satya Sai Kumar, Bhawani Sankar Panigrahi, R. Gomalavalli, R. Vinodhini
    International Journal of Information Technology Singapore, 2025
    Photovoltaic (PV) systems play a vital role in mitigating renewable energy issues ranging from the oil crisis to environmental concerns. The given paper proposes a grid-connected PV power system with high voltage gain (VG) and a high-speed multiphase buck-boost converter. With this converter, PV panels can be integrated in any fashion as per varying climatic conditions without affecting the switching stress. Also, the proposed system makes use of maximum power point tracking (MPPT) concept with fuzzy logic control (FLC) algorithm in order to reduce losses and complexities associated with the system. For validation of the system, an annual dataset related to global solar irradiance across three locations in Tamil Nadu is taken into consideration. The proposed system is validated and compared with traditional MPPT methods based on power output (W) and energy efficiency (%). It includes the computation of predicted mean (PM) values and comparing them with actual mean (AM) values of solar radiation for each of the locations. The results show a good correlation between the predicted and actual values and higher efficiency, thereby making the proposed system suitable for forecasting solar irradiance.
  • Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment
    C. Labesh Kumar, Suresh Betam, Denis Pustokhin, E. Laxmi Lydia, Kanchan Bala, Rajanikanth Aluvalu, Bhawani Sankar Panigrahi
    Scientific Reports, 2025
    The Software Defined Networking (SDN) method has evolved to project future systems and collect novel application needs for several years. SDN delivers sources for enhancing management and system control by splitting data and control plane, and the control logic is federal in a controller. Conversely, the central logical control is a perfect objective for malicious assaults, chiefly Distributed Denial of Service (DDoS) threats. Deep Learning (DL) is one of the influential models useful in cyber-security, and numerous Network Intrusion Detection (NIDS) were developed in current studies. Some researchers have specified that deep neural networks (DNN) subtly perceive adversarial assaults. These attacks are examples of definite worries that cause DNNs to misclassify. Therefore, this manuscript develops a novel Cybersecurity in Software-Defined Networking utilizing Hybrid Deep Learning Models and a Binary Narwhal Optimizer (CSSDN-HDLBNO) approach. The presented CSSDN-HDLBNO approach provides a scalable and effective solution to safeguard against evolving cyber threats in DDoS attacks within the SDN environment. Initially, the CSSDN-HDLBNO approach utilizes min-max normalization to scale the features within a uniform range using data normalization. Furthermore, the binary narwhal optimizer (BNO)-based feature selection is accomplished to classify the most related features. For the DDoS attack classification process, the attention mechanism with convolutional neural network and bidirectional gated recurrent units (CNN-BiGRU-AM) is employed. To ensure optimal performance of the CNN-BiGRU-AM model, hyperparameter tuning is performed by utilizing the seagull optimization algorithm (SOA) model to enhance the efficiency and robustness of the detection system. A wide range of simulation analyses is implemented to certify the improved performance of the CSSDN-HDLBNO technique under the DDoS SDN dataset. The performance validation of the CSSDN-HDLBNO technique portrayed a superior accuracy value of 99.40% over existing models in diverse evaluation measures.
  • Hybrid AI models for predicting heat distribution in complex tissue structures with bioheat transfer simulation
    Bhawani Sankar Panigrahi, Srigitha S. Nath, Pankaj Agarwal, B. Muthu kumar, Syed Karimunnisa, M. Neeladri
    Journal of Thermal Biology, 2025
  • Reducing the environmental impact of cloud data centres achieved through renewable energy sources under power grid energy trading with enhanced VM consolidation techniques
    R. Karthikeyan, Ulligaddala Srinivasarao, Shanmugasundaram Hariharan, Prakash Kumar Sarangi, Bhawani Sankar Panigrahi
    International Journal of Services Economics and Management, 2025
    In this article, we focus on the problems of cost-effective green scheduling for cloud data centres through power trading and power grid transactions. Energy utilised to power the data centres can either be self-generated or it can be acquired from a renewable power plant. In order to partially offset the high-energy costs of data centres, they can either be directly powered by renewable energy sources or their excess electricity can be deposited in energy storage devices (ESD). This article is focused on the following two problem statements that have been identified: 1) cutting down on the total amount of energy by carefully organising users' needs, infrastructure, and the application of different types of energy sources; 2) lowering overall carbon discharges through an effective plan for energy use our tryouts prove that our methodology can significantly cut cloud data centres' carbon emissions by 15% compared to the existing methodology.
  • Interpretable Temporal-Spatial Graph Attention Network with Hyperbolic Sine Optimizer Algorithm for Alzheimer’s Disease Diagnosis Through Multiscale Feature Modeling
    Biswajit Brahma, Gorli L Aruna Kumari, Bhawani Sankar Panigrahi, Sanjay Kumar Sen, Susanta Kumar Sahoo
    Biomedical Materials and Devices, 2025
  • Computational Diagnosis Application of Cervical Cancer Using Deep Learning Application
    R. Kishore Kanna, Bhawani Sankar Panigrahi, Soujanya Duvvi, Ponnaganti Rama Devi, Susanta Kumar Sahoo, Jhum Swain
    Artificial Intelligence in Oncology Cancer Diagnosis and Treatment Medical Imaging and Personalized Medicine, 2025
  • Innovative edge computing-driven recognition of cardiac monitoring application
    R. Kishore Kanna, Rajendar Sandiri, Biswajit Brahma, Bhawani Sankar Panigrahi, Susanta Kumar Sahoo, Rajitha Ala
    International Journal of Grid and Utility Computing, 2025
  • EXPLORING QUANTUM ALGORITHMS AND THEIR IMPACT ON CRYPTOGRAPHY AND INFORMATION SECURITY IN THE AGE OF QUANTUM SUPREMACY
    Journal of Environmental Protection and Ecology, 2025
  • Precise Pharmaceuticals: Computational Intelligence in Drug Manufacturing
    Akriti Dogra, Bhargavi Posinasetty, Bhawani Sankar Panigrahi, Susanta Kumar Sahoo, S. Jailani, G. S. Gayathri
    Computational Intelligence Solutions for Real Life Problems, 2025
  • Emotion Detection Using Physiological Signals: A Comparative Study of LSTM, Random Forest, and Hybrid Models with Environmental Context Integration
    Ch. Kethan, Bhawani Sankar Panigrahi, K. Sriram, V. Boopathi, N. Ramachandra Reddy, Biswajit Brahma, Shibani Tripathy, Chandrakanta Mahanty
    2025 International Conference on Next Generation of Green Information and Emerging Technologies Giet 2025, 2025
  • Smart Patient Monitoring for Heart Disease Prediction using IOT and Deep Learning
    Nithin Sai Ram Nalla, Udayan. L. R, Ch Laxmi Praneeth, T. Sathvik Varma, Shibani Tripathy, Chandrakanta Mahanty, Biswajit Brahma, Bhawani Sankar Panigrahi
    2nd International Conference on Cognitive Green and Ubiquitous Computing IC Cgu 2025, 2025
  • Enhancing Financial Forecasting with a Hybrid LSTM-Graph Neural Network Model
    Chinnakamanam Ranjith Kumar, Bhawani Sankar Panigrahi, Abdul Sattar, Puttagunta Karthikeya, A Para Brama Reddy, Biswajit Brahma, Shibani Tripathy, S. Gopal Krishna Patro
    2025 International Conference on Next Generation of Green Information and Emerging Technologies Giet 2025, 2025
  • Novel nature-inspired optimization approach-based svm for identifying the android malicious data
    Bhawani Sankar Panigrahi, Nagabhooshanam Nagarajan, Kanaka Durga Veera Prasad, Sathya, Satish Sampatrao Salunkhe, Pilli. Dharmendra Kumar, Muthevi Anil Kumar
    Multimedia Tools and Applications, 2024
  • CNN Based Face Emotion Recognition System for Healthcare Application
    R Kishore Kanna, Bhawani Sankar Panigrahi, Susanta Kumar Sahoo, Anugu Rohith Reddy, Yugandhar Manchala, Nirmal Keshari Swain
    Eai Endorsed Transactions on Pervasive Health and Technology, 2024
  • Enhancing Audio Accessory Selection through Multi-Criteria Decision Making using Fuzzy Logic and Machine Learning
    Sagar Mousam Parida, Sagar Dhanraj Pande, Nagendra Panini Challa, Bhawani Sankar Panigrahi
    Eai Endorsed Transactions on Internet of Things, 2024
  • Identification of Breast Cancer Using an Ensemble of Deep Learning Techniques
    Bhawani Sankar Panigrahi, S Gopal Krishna Patro, Pravallika Dannana, Chandrakanta Mahanty
    International Conference on Parallel Distributed and Grid Computing Pdgc, 2024
  • A Hybrid Approach for Mobile Phone Recommendation using Content-Based and Collaborative Filtering
    B V Chandrahaas, Bhawani Sankar Panigrahi, Sagar Dhanraj Pande, Nirmal Keshari Swain
    Eai Endorsed Transactions on Internet of Things, 2024
  • Machine Learning Based Stroke Predictor Application
    R Kishore Kanna, Ch. Venkata Rami Reddy, Bhawani Sankar Panigrahi, Naliniprava Behera, Sarita Mohanty
    Eai Endorsed Transactions on Internet of Things, 2024
  • Machine Learning Based Intelligent Management System for Energy Storage Using Computing Application
    Bhawani Sankar Panigrahi, R. Kishore Kanna, Pragyan Paramita Das, Susanta Kumar Sahoo, Tanusree Dutta
    Eai Endorsed Transactions on Energy Web, 2024
  • A Comparative Analysis of Different Machine Learning Techniques For Medical Insurance Premium Prediction
    Satyabrata Dash, Bhawani Sankar panigrahi, Vijay Venkata Bhaskar Reddy Sanikommu, B K Madhavi, Susanta Kumar Sahoo
    2024 1st International Conference on Cognitive Green and Ubiquitous Computing IC Cgu 2024, 2024
  • Smart Assist System Module for Paralysed Patient Using IoT Application
    R Kishore Kanna, Nihar Ranjan Pradhan, Bhawani Sankar Panigrahi, Santi Swarup Basa, Sarita Mohanty
    Eai Endorsed Transactions on Internet of Things, 2024
  • Brain Tumor Classification using Hybrid K-means and PSO Approach
    Konda Sowmya, Bhawani Sankar Panigrahi, Sadala Sreya, B K Madhavi, Sahithi Kota
    2024 Opju International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4 0 Otcon 2024, 2024
  • Emotional Intelligence-Based Music Recommendation System Using Hybrid Deep Neural Network
    Bhawani Sankar Panigrahi, K J Hannah Joyce, Tejasri Punna, Baby Keerthana Varala, B K Madhavi
    2024 1st International Conference on Cognitive Green and Ubiquitous Computing IC Cgu 2024, 2024
  • Signature Forgery Detection using Siamese-Convolutional Neural Network
    M.Sowmya Reddy, A.Anagha Lakshmi, G.Siddarth Reddy, B.Koustubha Madhavi, Bhawani Sankar Panigrahi, V Mohan
    2024 1st International Conference on Cognitive Green and Ubiquitous Computing IC Cgu 2024, 2024
  • Reinforcement Learning for Dynamic Power Management in Embedded Systems
    Bhawani Sankar Panigrahi, Balachandra Pattanaik, Ojasvi Pattanaik, S. B G Tilak Babu, Pavithra G, Bazani Shaik
    5th International Conference on Recent Trends in Computer Science and Technology Icrtcst 2024 Proceedings, 2024
  • Deep Learning Techniques for Fault Detection in Industrial Machinery
    Bhawani Sankar Panigrahi, Thiyagarajan T, M. Tamilselvi, S. B G Tilak Babu, Pavithra G, Bazani Shaik
    5th International Conference on Recent Trends in Computer Science and Technology Icrtcst 2024 Proceedings, 2024
  • Artificial Neural Networks for Weld Joint Strength Prediction in Various Welding Techniques
    Bhawani Sankar Panigrahi, Manjunath H R, Amar Chipade, S. B G Tilak Babu, Pavithra G., Beporam Iftekhar Hussain
    5th International Conference on Recent Trends in Computer Science and Technology Icrtcst 2024 Proceedings, 2024
  • Artificial Intelligence in Astrophysics: Automated Detection of Celestial Objects and Anomaly Detection
    Bhawani Sankar Panigrahi, S. Artheeswari, Wasim Khan, Pavithra G, Dr. Sushil Kumar Pathak, R Bharanidharan
    5th International Conference on Recent Trends in Computer Science and Technology Icrtcst 2024 Proceedings, 2024
  • Detection of Brain Tumour based on Optimal Convolution Neural Network
    R Kishore Kanna, Susanta Kumar Sahoo, B K Mandhavi, V Mohan, G Stalin Babu, Bhawani Sankar Panigrahi
    Eai Endorsed Transactions on Pervasive Health and Technology, 2024
  • IoT Applications in Cold Chain Management for Pharmaceuticals: Ensuring Product Integrity and Safety
    Bhawani Sankar Panigrahi, A. Vanitha, Manesh R. Palav, S. B G Tilak Babu, Amrutha Muralidharan Nair, Nagaraju Bogiri
    5th International Conference on Recent Trends in Computer Science and Technology Icrtcst 2024 Proceedings, 2024
  • Big Data and AI in Natural Product Drug Discovery: Uncovering Hidden Medicinal Chemistry Gems
    Bhawani Sankar Panigrahi, Akriti Dogra, K. Sivakumar, Shreni Diwakar, Yudhishther Singh Bagal, Mohini Upadhye
    Proceedings of 9th International Conference on Science Technology Engineering and Mathematics the Role of Emerging Technologies in Digital Transformation Iconstem 2024, 2024
  • Real-Time Remote-Controlled Human Manipulation Medical Robot Using IoT Module
    R. Kishore Kanna, Bhawani Sankar Panigrahi, Swati Sucharita, B Pravallika, Susanta Kumar Sahoo
    Eai Endorsed Transactions on Internet of Things, 2024
  • OPTIMISING PULMONARY DISEASE DETECTION WITH ENHANCED X-RAY IMAGING: A MULTI-STAGE FRAMEWORK USING WEIGHTED MEDIAN FILTERING, FUZZY C-MEANS CLUSTERING, AND YOLOv4-AUGMENTED MULTI-COLUMN CNNS
    Journal of Environmental Protection and Ecology, 2024
  • Deep Learning-Based Image Recognition for Electronic Components Identification
    Bhawani Sankar Panigrahi, Angelina Royappa, Dr Sandeep Monga, H. Geetha, Pavithra G, Bazani Shaik
    5th International Conference on Recent Trends in Computer Science and Technology Icrtcst 2024 Proceedings, 2024
  • Detection of Covid-19 Using AI Application
    Kishore Kanna Ravikumar, Mohammed Ishaque, Bhawani Sankar Panigrahi, Chimaya Ranjan Pattnaik
    Eai Endorsed Transactions on Pervasive Health and Technology, 2023
  • An Emotion Aware Music Recommendation System Using Flask and Convolutional Neural Network
    Shashank Gajula, Tigulla Hruthika Goud, Bhawani Sankar Panigrahi, M.A. Jabbar
    7th IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions Csitss 2023 Proceedings, 2023
  • Optimal Convolutional Neural Network Model for Early Detection of Lung Cancer on CT Images
    Dugyala Vignesh kumar, Guttula Nookaraju, T. Sreeja Reddy, B. S. Panigrahi, S. N. Mohanty
    Lecture Notes in Electrical Engineering, 2023
  • Improving Data Centre Power Efficiency by Applying the VM Consolidation Approach
    R. Karthikeyan, Ulligaddala Srinivasarao, Shanmugasundaram Hariharan, Prakash Kumar Sarangi, Bhawani Sankar Panigrahi
    Lecture Notes in Networks and Systems, 2023
  • Face Mask Detection: An Application of Artificial Intelligence
    Poonam Mittal, Ashlesha Gupta, Bhawani Sankar Panigrahi, Ruqqaiya Begum, Sanjay Kumar Sen
    Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2023
  • Design and implementation of iot integrated monitoring and control system of renewable energy in smart grid for sustainable computing network
    NP G. Bhavani, Ravi Kumar, Bhawani Sankar Panigrahi, Kishore Balasubramanian, B. Arunsundar, Zulkiflee Abdul-Samad, Abha Singh
    Sustainable Computing Informatics and Systems, 2022
  • Enhanced Movie Recommendation and Sentiment Analysis Model Achieved by Similarity Method through Cosine and Jaccard Similarity algorithms
    Ulligaddala Srinivasarao, R Karthikeyan, Prakash Kumar Sarangi, Bhawani Sankar Panigrahi
    3rd IEEE 2022 International Conference on Computing Communication and Intelligent Systems Icccis 2022, 2022
  • Automatic Crop Securing System Using IoT
    Adepu Sai Aashrith, Chakka Manaswini, Gundu Preetham, Bhawani Sankar Panigrahi, Prakash Kumar Sarangi
    Proceedings International Conference on Computational Intelligence and Networks, 2022
  • A palmprint classification scheme using heart line feature extraction
    Atul Negi, B. Panigrahi, M.V.N. K. Prasad, Madhabananda Das
    Proceedings 9th International Conference on Information Technology Icit 2006, 2006

RECENT SCHOLAR PUBLICATIONS

  • Explainable AI frameworks using SHAP and LIME enhance interpretable defect classification in additive manufacturing
    BS Panigrahi, M Vanitha, M Ashraf, RVS Lalitha, D Haritha, A Sundaram
    Nondestructive Testing and Evaluation, 1-26 , 2026
    2026
    Citations: 1
  • Corrigendum to “A new method for prediction of Vigna mungo millet disease based on deep learning”[Curr. Plant Biol. 44 (2025) 100562]
    R Kumar, C Mahanty, BS Panigrahi, SGK Patro, TM Tuan, LH Son
    Current Plant Biology, 100574 , 2025
    2025
  • Designing an empirical grid-connected PV system based on FLC-MPPT approach for local community use
    SS Sree, M Muthalakshmi, PA Surendhar S, ASS Kumar, BS Panigrahi, ...
    International Journal of Information Technology 17 (9), 5605-5612 , 2025
    2025
    Citations: 1
  • Precise Pharmaceuticals: Computational Intelligence in Drug Manufacturing
    A Dogra, B Posinasetty, BS Panigrahi, SK Sahoo, S Jailani, GS Gayathri
    Computational Intelligence Solutions for Real-Life Problems, 1-17 , 2025
    2025
  • Explainable Artificial Intelligence with Cloud and Blockchain-as-a-Service Model for Consumer Electronics in Connected Healthcare
    S Potluri, BS Panigrahi, SN Mohanty, A Albalawi
    IEEE Transactions on Consumer Electronics , 2025
    2025
    Citations: 1
  • A new method for prediction of Vigna mungo millet disease based on deep learning
    R Kumar, C Mahanty, BS Panigrahi, SGK Patro, TM Tuan, LH Son
    Current Plant Biology, 100562 , 2025
    2025
  • Smart Patient Monitoring for Heart Disease Prediction using IOT and Deep Learning
    NSR Nalla, CL Praneeth, TS Varma, S Tripathy, C Mahanty, B Brahma, ...
    2025 International Conference on Cognitive, Green and Ubiquitous Computing … , 2025
    2025
  • Computational Diagnosis Application of Cervical Cancer Using Deep Learning Application
    RK Kanna, BS Panigrahi, S Duvvi, PR Devi, SK Sahoo, J Swain
    Artificial Intelligence in Oncology: Cancer Diagnosis and Treatment, Medical … , 2025
    2025
  • Heart disorder detection using evolutionary algorithms : A real-time pulse sensor system for early intervention
    VK R. Kishore Kanna, Bhawani Sankar Panigrahi*, Sanjay Kumar Sen, Susanta ...
    Journal of Information and Optimization Sciences 46 (6), 1945–1951 , 2025
    2025
  • Interpretable Temporal-Spatial Graph Attention Network with Hyperbolic Sine Optimizer Algorithm for Alzheimer’s Disease Diagnosis Through Multiscale Feature Modeling
    B Brahma, GL Aruna Kumari, BS Panigrahi, SK Sen, SK Sahoo
    Biomedical Materials & Devices, 1-24 , 2025
    2025
    Citations: 1
  • Integrating User Relationships and Features for Intelligence of Social Things Aware Information Diffusion Prediction
    BS Panigrahi, ME Seno, B Murugesan, O Isam, VJ Sowmya, KDV Prasad, ...
    IEEE Transactions on Computational Social Systems , 2025
    2025
    Citations: 1
  • Emotion Detection Using Physiological Signals: A Comparative Study of LSTM, Random Forest, and Hybrid Models with Environmental Context Integration
    C Kethan, BS Panigrahi, K Sriram, V Boopathi, NR Reddy, B Brahma, ...
    2025 International Conference on Next Generation of Green Information and … , 2025
    2025
  • Enhancing Financial Forecasting with a Hybrid LSTM-Graph Neural Network Model
    CR Kumar, BS Panigrahi, A Sattar, P Karthikeya, APB Reddy, B Brahma, ...
    2025 International Conference on Next Generation of Green Information and … , 2025
    2025
  • EXPLORING QUANTUM ALGORITHMS AND THEIR IMPACT ON CRYPTOGRAPHY AND INFORMATION SECURITY IN THE AGE OF QUANTUM SUPREMACY
    BISWAJIT BRAHMA, YUGANDHAR MANCHALA, SOUJANYA DUVVI, SUSANTA KUMAR SAHOO ...
    Journal of Environmental Protection and Ecology 26 (2), 784-795 , 2025
    2025
  • Identification of Breast Cancer Using an Ensemble of Deep Learning Techniques
    CM Bhawani Sankar Panigrahi, S Gopal Krishna Patro, Pravallika Dannana
    2024 Eighth International Conference on Parallel, Distributed and Grid … , 2025
    2025
  • Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment
    CL Kumar, S Betam, D Pustokhin, E Laxmi Lydia, K Bala, R Aluvalu, ...
    Scientific reports 15 (1), 14166 , 2025
    2025
    Citations: 14
  • Hybrid AI models for predicting heat distribution in complex tissue structures with bioheat transfer simulation
    BS Panigrahi, SS Nath, P Agarwal, S Karimunnisa, M Neeladri
    Journal of Thermal Biology 129, 104122 , 2025
    2025
    Citations: 5
  • Smart City: Challenges and Issues
    N Agarwal, SN Mohanty, BS Panigrahi, CR Patnaik
    Explainable IoT Applications: A Demystification, 209-221 , 2025
    2025
    Citations: 3
  • Innovative edge computing-driven recognition of cardiac monitoring application
    RK Kanna, R Sandiri, B Brahma, BS Panigrahi, SK Sahoo, R Ala
    International Journal of Grid and Utility Computing 16 (5-6), 552-560 , 2025
    2025
    Citations: 29
  • Reducing the environmental impact of cloud data centres achieved through renewable energy sources under power grid energy trading with enhanced VM consolidation techniques
    R Karthikeyan, U Srinivasarao, S Hariharan, PK Sarangi, BS Panigrahi
    International Journal of Services, Economics and Management 16 (3), 277-296 , 2025
    2025

MOST CITED SCHOLAR PUBLICATIONS

  • Detection of Covid-19 using AI application
    KK Ravikumar, M Ishaque, BS Panigrahi, CR Pattnaik
    EAI endorsed transactions on pervasive health and technology 9 , 2024
    2024
    Citations: 105
  • Design and implementation of iot integrated monitoring and control system of renewable energy in smart grid for sustainable computing network
    NPG Bhavani, R Kumar, BS Panigrahi, K Balasubramanian, ...
    Sustainable computing: Informatics and systems 35, 100769 , 2022
    2022
    Citations: 42
  • Machine Learning Based Stroke Predictor Application.
    RK Kanna, CVR Reddy, BS Panigrahi, N Behera, S Mohanty
    EAI Endorsed Transactions on Internet of Things 10 , 2024
    2024
    Citations: 31
  • Innovative edge computing-driven recognition of cardiac monitoring application
    RK Kanna, R Sandiri, B Brahma, BS Panigrahi, SK Sahoo, R Ala
    International Journal of Grid and Utility Computing 16 (5-6), 552-560 , 2025
    2025
    Citations: 29
  • Reinforcement Learning for Dynamic Power Management in Embedded Systems
    BS Panigrahi, B Pattanaik, O Pattanaik, SBGT Babu, B Shaik
    2024 5th International Conference on Recent Trends in Computer Science and … , 2024
    2024
    Citations: 28
  • Smart Assist System Module for Paralysed Patient Using IoT Application.
    RK Kanna, NR Pradhan, BS Panigrahi, SS Basa, S Mohanty
    EAI Endorsed Transactions on Internet of Things 10 , 2024
    2024
    Citations: 28
  • IoT Applications in cold chain management for pharmaceuticals: ensuring product integrity and safety
    BS Panigrahi, A Vanitha, MR Palav, SBGT Babu, AM Nair, N Bogiri
    2024 5th International Conference on Recent Trends in Computer Science and … , 2024
    2024
    Citations: 27
  • Detection of Brain Tumour based on Optimal Convolution Neural Network
    RK Kanna
    EAI Endorsed Transactions on Pervasive Health and Technology , 2024
    2024
    Citations: 26
  • Real-Time Remote-Controlled Human Manipulation Medical Robot Using IoT Module.
    RK Kanna, BS Panigrahi, S Sucharita, B Pravallika, SK Sahoo, P Gupta
    EAI Endorsed Transactions on Internet of Things 10 , 2024
    2024
    Citations: 24
  • Advanced signal processing techniques for feature extraction in data mining
    M Nayak, BS Panigrahi
    International Journal of Computer Applications 19 (9), 30-37 , 2011
    2011
    Citations: 22
  • Machine Learning Based Intelligent Management System for Energy Storage Using Computing Application
    BS Panigrahi, RK Kanna, PP Das, SK Sahoo, T Dutta
    EAI Endorsed Transactions on Energy Web 11 , 2024
    2024
    Citations: 17
  • Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment
    CL Kumar, S Betam, D Pustokhin, E Laxmi Lydia, K Bala, R Aluvalu, ...
    Scientific reports 15 (1), 14166 , 2025
    2025
    Citations: 14
  • Deep learning techniques for fault detection in industrial machinery
    BS Panigrahi, T Thiyagarajan, M Tamilselvi, SBGT Babu, G Pavithra, ...
    2024 5th International Conference on Recent Trends in Computer Science and … , 2024
    2024
    Citations: 13
  • Enhanced movie recommendation and sentiment analysis model achieved by similarity method through cosine and Jaccard similarity algorithms
    U Srinivasarao, R Karthikeyan, PK Sarangi, BS Panigrahi
    2022 International Conference on Computing, Communication, and Intelligent … , 2022
    2022
    Citations: 12
  • Cnn based face emotion recognition system for healthcare application
    RK Kanna, BS Panigrahi, SK Sahoo, AR Reddy, Y Manchala, NK Swain
    EAI Endorsed Transactions on Pervasive Health and Technology 10, 10 , 2024
    2024
    Citations: 10
  • Detection of Covid-19 using AI application. EAI endorsed transactions on pervasive health and technology
    KK Ravikumar, M Ishaque, BS Panigrahi, CR Pattnaik
    EAI endorsed transactions on pervasive health and technology 9 , 2023
    2023
    Citations: 8
  • Prediction of Covid-19 Using Artificial Intelligence [AI] Applications
    RK Kanna, M Ishaque, BS Panigrahi, CR Pattnaik
    International Conference on Cryptology & Network Security with Machine … , 2022
    2022
    Citations: 7
  • A Palmprint Classification Scheme using Heart Line Feature Extraction
    MD Atul Negi, B. Panigrahi, M.V.N. K. Prasad
    Proceedings 9th International Conference on Information Technology Icit 2006 … , 2006
    2006
    Citations: 7
  • Novel nature-inspired optimization approach-based SVM for identifying the android malicious data
    BS Panigrahi, N Nagarajan, KDV Prasad, Sathya, SS Salunkhe, ...
    Multimedia Tools and Applications 83 (28), 71579-71597 , 2024
    2024
    Citations: 6
  • Automatic Crop Securing System Using IoT
    AS Aashrith, C Manaswini, G Preetham, BS Panigrahi, PK Sarangi
    2022 5th International Conference on Computational Intelligence and Networks … , 2022
    2022
    Citations: 6