Vijaya Kalavakonda

@srmist.edu.in

Associate Professor and Department of Computing Technologies
SRM Institute of Science and Technology

Vijaya Kalavakonda


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https://researchid.co/vijayak

RESEARCH INTERESTS

Clinical Data Mining, Artificial Intelligence,
18

Scopus Publications

175

Scholar Citations

6

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Deep Learning-Based Optimal Cell Balancing Mechanism for Electric Vehicle Battery Management System
    Preethileela Selvaraj, Vijaya Kalavakonda
    2nd International Conference on Research Methodologies in Knowledge Management Artificial Intelligence and Telecommunication Engineering Rmkmate 2025, 2025
    The growing adoption of Electric Vehicles (EVs) has led to the need for more efficient, reliable, and long-lasting battery systems. One of the critical issues in EV battery management is the imbalance between individual cells in the battery pack, which can affect the overall performance, safety, and lifespan of the battery. This project proposes a deep learning-based optimal cell balancing mechanism for the Battery Management System (BMS) of EVs. By leveraging deep learning algorithms, this research aims to develop a mechanism that can predict and correct cell imbalances in real-time, ensuring optimal performance and longevity of the battery. The model will use data from various sensors to monitor the state-of-health (SoH) and state-of-charge (SoC) of each cell, enabling dynamic adjustments for efficient energy distribution across the battery pack. The approach aims to outperform traditional model-based or heuristic methods in terms of accuracy, adaptability, and scalability.
  • Evaluation of Machine Learning Techniques in the Classification of Malware Attacks
    Sai Vishal Peela, Vijaya K, Saraag Jayam
    6th International Conference on Innovative Trends in Information Technology Secure Trustworthy and Socially Responsible AI Icitiit 2025, 2025
    This research examines the performance of Random Forest and Decision Tree algorithms in classifying a dataset defined by various process metrics, such as hash, categorisation, and memory management parameters like total_vm, shared_vm, and maj_flt. To ensure the accuracy and reliability of the data, the dataset underwent comprehensive preprocessing. Both algorithms were trained and tested, achieving strong classification accuracy, indicating their suitability for the given dataset. The Random Forest algorithm, an ensemble learning method, showed strong performance by effectively managing the dataset's complexities through the use of multiple decision trees, which enhanced generalization. In contrast, the Decision Tree algorithm, valued for its interpretability, successfully pinpointed key features that influenced the classifications, offering insightful views into the data's underlying patterns. The models' performance was thoroughly evaluated using key metrics, including accuracy, precision, recall, and F1 score, ensuring a comprehensive assessment of their effectiveness. Both algorithms were effective in reducing false positives and false negatives, highlighting their reliability for practical use. While both models achieved high accuracy, the choice between them may depend on the need for either interpretability or superior performance. This study contributes to the understanding of machine learning applications in process classification, stressing the importance of selecting the right model based on dataset characteristics and the need for continuous evaluation in real-world applications.
  • Automated Screening of Hip X-rays for Osteoporosis by Singh’s Index Using Machine Learning Algorithms
    Vijaya Kalavakonda, Sameer Mohamed, Lal Abhay, Sathish Muthu
    Indian Journal of Orthopaedics, 2024
  • Regular grammar Prediction from Finite Positive Samples
    K. Senthil Kumar, K. Vijaya, D. Malathi
    Aip Conference Proceedings, 2024
  • Object Detection and Voice Alert System
    Prashant Pathak, Deepraj Singh, Vijaya Kalavakonda
    Aip Conference Proceedings, 2024
  • Detection of plant leaf diseases using deep convolutional neural network models
    Puja Singla, Vijaya Kalavakonda, Ramalingam Senthil
    Multimedia Tools and Applications, 2024
  • Randomized round crypto security encryption standard for secure cloud storage
    Anitha K., Anto Arockia Rosaline R., Devipriya A., Nancy P., Vijaya K.
    Machine Learning and Cryptographic Solutions for Data Protection and Network Security, 2024
    Due to the heightened expenses associated with maintaining extensive data storage infrastructure on-premises, many organizations face challenges in accommodating large volumes of data within their facilities. Data outsourcing proves beneficial for users as it alleviates the responsibility of storing and managing the data. While efforts have been made to establish a secure and reliable cloud platform for data storage, persistent concerns linger regarding the confidentiality and integrity of data and applications stored in the cloud. Consequently, there exists a critical necessity to establish a robust security framework for cloud-based data storage. In response to this, a proposal is presented for a secure block-level cloud storage system, leveraging the efficient randomized round encryption protocol for encryption and decryption, ensuring the storage and management of sensitive data in a secure manner.
  • Stellar Data Analysis and Deep Space Data Analysis System
    Narra Praneeth, K Chandra Kiran, K. Vijaya
    1st International Conference on Electronics Computing Communication and Control Technology Iceccc 2024, 2024
    This paper focuses on developing an advanced Stellar Data Analysis and Deep Space Data Analysis System, leveraging the power of machine learning and deep learning algorithms. Utilizing cutting-edge techniques such as artificial neural networks, random forest regression, and other sophisticated models as VGG-19,ResNet-50, the system aims to enhance our understanding of celestial phenomena by analysing stellar data. It encompasses the application of these algorithms to decipher complex patterns and anomalies in deep space data, contributing to a more comprehensive comprehension of astronomical observations. The integration of advanced machine learning and deep learning technologies empowers the system to efficiently process vast datasets, providing valuable insights into stellar dynamics, celestial objects, improves celestial object classification by overcoming the vanishing gradient problem, and deep space events. This initiative represents a significant step toward optimizing data analysis methodologies for astronomical research and exploration.
  • Graph-Theoretic Approaches in Semantic Web Service Orchestration and Discovery: A Comprehensive Literature Survey
    Vignesh T. V, Vijaya K, Minu R I
    Proceedings of the 5th International Conference on Data Intelligence and Cognitive Informatics Icdici 2024, 2024
    Semantic Web Services (SWS) have become a powerful means for automating the discovery, composition, and orchestration of web services by providing them with semantic descriptions. This paper provides a comprehensive survey of graph-theoretic approaches in the orchestration and discovery of SWS, systematically categorizing and analyzing various methodologies. We examine how graph-based models contribute to enhancing the efficiency, accuracy, scalability, performance, reliability, and predictability of SWS processes. Furthermore, the paper discusses research gaps, challenges, and potential future directions, offering insights into emerging solutions and state-of-the-art techniques in the field. The survey also integrates recent advancements such as hybrid frameworks combining knowledge graphs and semantic web services, service clustering using graph embedding, and enhanced recommendation models.
  • Retraction Note: Smart communication using tri-spectral sign recognition for hearing-impaired people (The Journal of Supercomputing, (2021), 78, (2651–2664), 10.1007/s11227-021-03968-1)
    B. Kanisha, V. Mahalakshmi, M. Baskar, K. Vijaya, P. Kalyanasundaram
    Journal of Supercomputing, 2023
  • Smart Wearable Sensor Design Techniques For Mobile Health Care Solutions
    K. Vijaya, B. Prathusha Laxmi
    Mobile Computing Solutions for Healthcare Systems, 2023
  • Detection and Categorization of Sorghum Crop using MCRNN Architecture
    M.Senthil Murugan, D. Sungeetha, K. Vijaya, A. Gnana Soundari, R. Dhanalakshmi, S. Gomathi
    Proceedings of the 4th International Conference on Smart Electronics and Communication Icosec 2023, 2023
  • Experimental analysis of machine learning based node failure prediction using game theory strategy
    P. Chitra, P. Subhashini, K. Vijaya, M. Gopikrishnan
    Aip Conference Proceedings, 2022
  • Smart communication using tri-spectral sign recognition for hearing-impaired people
    B. Kanisha, V. Mahalakshmi, M. Baskar, K. Vijaya, P. Kalyanasundaram
    Journal of Supercomputing, 2022
  • Fuzzy local ternary pattern and skin texture properties based countermeasure against face spoofing in biometric systems
    P. Kavitha, K. Vijaya
    Computational Intelligence, 2021
  • Optimal feature-level fusion and layered k-support vector machine for spoofing face detection
    P. Kavitha, K. Vijaya
    Multimedia Tools and Applications, 2018
  • Evidence Based health care system using Big Data for disease diagnosis
    Chitra Pasupathi, Vijaya Kalavakonda
    Proceeding of IEEE 2nd International Conference on Advances in Electrical Electronics Information Communication and Bio Informatics IEEE Aeeicb 2016, 2016
  • Fuzzy neuro genetic approach for predicting the risk of cardiovascular diseases
    Kalavakonda Vijaya, H. Khanna Nehemiah, A. Kannan, N.G. Bhuvaneswari
    International Journal of Data Mining Modelling and Management, 2010

RECENT SCHOLAR PUBLICATIONS

  • Unsupervised Machine Learning for Osteoporosis Diagnosis Using Singh Index Clustering on Hip Radiographs
    V Madhivanan, K Vijaya, A Lal, S Rithika, SK Subramaniam, M Sameer
    arXiv preprint arXiv:2411.15253 , 2024
    2024
    Citations: 2
  • Graph-Theoretic Approaches in Semantic Web Service Orchestration and Discovery: A Comprehensive Literature Survey
    MRI Vignesh T V, Vijaya K
    5th International Conference on Data Intelligence and Cognitive Informatics … , 2024
    2024
  • Automated screening of hip X-rays for osteoporosis by Singh’s index using machine learning algorithms
    V Kalavakonda, S Mohamed, L Abhay, S Muthu
    Indian Journal of Orthopaedics 58 (10), 1449-1457 , 2024
    2024
    Citations: 5
  • Regular grammar prediction from finite positive samples
    KS Kumar, K Vijaya, D Malathi
    AIP Conference Proceedings 3075 (1), 020252 , 2024
    2024
  • Object detection and voice alert system
    P Pathak, D Singh, V Kalavakonda
    AIP Conference Proceedings 3075 (1), 020053 , 2024
    2024
  • Detection of plant leaf diseases using deep convolutional neural network models
    P Singla, V Kalavakonda, R Senthil
    Multimedia Tools and Applications 83 (24), 64533-64549 , 2024
    2024
    Citations: 39
  • Stellar data analysis and deep space data analysis system
    N Praneeth, KC Kiran, K Vijaya
    2024 International Conference on Electronics, Computing, Communication and … , 2024
    2024
    Citations: 1
  • Randomized Round Crypto Security Encryption Standard for Secure Cloud Storage
    K Anitha, A Devipriya, P Nancy, K Vijaya
    Machine Learning and Cryptographic Solutions for Data Protection and Network … , 2024
    2024
  • Detection and Categorization of Sorghum Crop using MCRNN Architecture
    MS Murugan, D Sungeetha, K Vijaya, AG Soundari, R Dhanalakshmi, ...
    2023 4th International Conference on Smart Electronics and Communication … , 2023
    2023
    Citations: 6
  • Retraction Note: Smart communication using tri-spectral sign recognition for hearing-impaired people
    B Kanisha, V Mahalakshmi, M Baskar, K Vijaya, P Kalyanasundaram
    The Journal of Supercomputing 79 (5), 5834-5835 , 2023
    2023
  • Smart Wearable Sensor Design Techniques For Mobile Health Care Solutions
    K Vijaya, BP Laxmi
    Mobile computing solutions for healthcare systems, 204-222 , 2023
    2023
    Citations: 1
  • Experimental analysis of machine learning based node failure prediction using game theory strategy
    P Chitra, P Subhashini, K Vijaya, M Gopikrishnan
    AIP Conference Proceedings 2518 (1), 090001 , 2022
    2022
  • Smart communication using tri-spectral sign recognition for hearing-impaired people
    B Kanisha, V Mahalakshmi, M Baskar, K Vijaya, P Kalyanasundaram
    The Journal of Supercomputing 78, 2651-2664 , 2021
    2021
    Citations: 35
  • Fuzzy local ternary pattern and skin texture properties based countermeasure against face spoofing in biometric systems
    P Kavitha, K Vijaya
    Computational Intelligence 37 (1), 559-577 , 2021
    2021
    Citations: 9
  • Indian flight fare prediction: a proposal
    JS Champawat, U Arora, K Vijaya
    Int. J. Adv. Technol. Eng. Sci 9 (3) , 2021
    2021
    Citations: 2
  • Authorization For Wearable Biomedical Gadgets Monitoring System
    N Suchitra, SG Sanjana, L Raji, K Vijaya, J Swetha
    2019
  • DATA LEAKAGE DETECTION USING CLOUD COMPUTING
    MSC Reddy, TVS Yaswanth, TGL Raji, K Vijaya
    2019
  • Optimal feature-level fusion and layered k-support vector machine for spoofing face detection
    P Kavitha, K Vijaya
    Multimedia Tools and Applications 77 (20), 26509-26543 , 2018
    2018
    Citations: 7
  • A Study on Spoofing Face Detection System
    P Kavitha, K Vijaya
    International Journal of Pure and Applied Mathematics 117 (22), 205-208 , 2017
    2017
    Citations: 6
  • Evidence Based health care system using Big Data for disease diagnosis
    C Pasupathi, V Kalavakonda
    2016 2nd International Conference on Advances in Electrical, Electronics … , 2016
    2016
    Citations: 21

MOST CITED SCHOLAR PUBLICATIONS

  • Detection of plant leaf diseases using deep convolutional neural network models
    P Singla, V Kalavakonda, R Senthil
    Multimedia Tools and Applications 83 (24), 64533-64549 , 2024
    2024
    Citations: 39
  • Fuzzy neuro genetic approach for predicting the risk of cardiovascular diseases
    K Vijaya, H Khanna Nehemiah, A Kannan, NG Bhuvaneswari
    International Journal of Data Mining, Modelling and Management 2 (4), 388-402 , 2010
    2010
    Citations: 36
  • Smart communication using tri-spectral sign recognition for hearing-impaired people
    B Kanisha, V Mahalakshmi, M Baskar, K Vijaya, P Kalyanasundaram
    The Journal of Supercomputing 78, 2651-2664 , 2021
    2021
    Citations: 35
  • Evidence Based health care system using Big Data for disease diagnosis
    C Pasupathi, V Kalavakonda
    2016 2nd International Conference on Advances in Electrical, Electronics … , 2016
    2016
    Citations: 21
  • Fuzzy local ternary pattern and skin texture properties based countermeasure against face spoofing in biometric systems
    P Kavitha, K Vijaya
    Computational Intelligence 37 (1), 559-577 , 2021
    2021
    Citations: 9
  • Optimal feature-level fusion and layered k-support vector machine for spoofing face detection
    P Kavitha, K Vijaya
    Multimedia Tools and Applications 77 (20), 26509-26543 , 2018
    2018
    Citations: 7
  • Detection and Categorization of Sorghum Crop using MCRNN Architecture
    MS Murugan, D Sungeetha, K Vijaya, AG Soundari, R Dhanalakshmi, ...
    2023 4th International Conference on Smart Electronics and Communication … , 2023
    2023
    Citations: 6
  • A Study on Spoofing Face Detection System
    P Kavitha, K Vijaya
    International Journal of Pure and Applied Mathematics 117 (22), 205-208 , 2017
    2017
    Citations: 6
  • Automated screening of hip X-rays for osteoporosis by Singh’s index using machine learning algorithms
    V Kalavakonda, S Mohamed, L Abhay, S Muthu
    Indian Journal of Orthopaedics 58 (10), 1449-1457 , 2024
    2024
    Citations: 5
  • Employing clinical data sets for intelligent temporal rule mining and decision making, a comparative study
    HK Nehemiah, A Kannan, K Vijaya, YN Jane, JB Merin
    ICGST-BIME 7 (1), 37-45 , 2007
    2007
    Citations: 5
  • Unsupervised Machine Learning for Osteoporosis Diagnosis Using Singh Index Clustering on Hip Radiographs
    V Madhivanan, K Vijaya, A Lal, S Rithika, SK Subramaniam, M Sameer
    arXiv preprint arXiv:2411.15253 , 2024
    2024
    Citations: 2
  • Indian flight fare prediction: a proposal
    JS Champawat, U Arora, K Vijaya
    Int. J. Adv. Technol. Eng. Sci 9 (3) , 2021
    2021
    Citations: 2
  • Stellar data analysis and deep space data analysis system
    N Praneeth, KC Kiran, K Vijaya
    2024 International Conference on Electronics, Computing, Communication and … , 2024
    2024
    Citations: 1
  • Smart Wearable Sensor Design Techniques For Mobile Health Care Solutions
    K Vijaya, BP Laxmi
    Mobile computing solutions for healthcare systems, 204-222 , 2023
    2023
    Citations: 1
  • Graph-Theoretic Approaches in Semantic Web Service Orchestration and Discovery: A Comprehensive Literature Survey
    MRI Vignesh T V, Vijaya K
    5th International Conference on Data Intelligence and Cognitive Informatics … , 2024
    2024
  • Regular grammar prediction from finite positive samples
    KS Kumar, K Vijaya, D Malathi
    AIP Conference Proceedings 3075 (1), 020252 , 2024
    2024
  • Object detection and voice alert system
    P Pathak, D Singh, V Kalavakonda
    AIP Conference Proceedings 3075 (1), 020053 , 2024
    2024
  • Randomized Round Crypto Security Encryption Standard for Secure Cloud Storage
    K Anitha, A Devipriya, P Nancy, K Vijaya
    Machine Learning and Cryptographic Solutions for Data Protection and Network … , 2024
    2024
  • Retraction Note: Smart communication using tri-spectral sign recognition for hearing-impaired people
    B Kanisha, V Mahalakshmi, M Baskar, K Vijaya, P Kalyanasundaram
    The Journal of Supercomputing 79 (5), 5834-5835 , 2023
    2023
  • Experimental analysis of machine learning based node failure prediction using game theory strategy
    P Chitra, P Subhashini, K Vijaya, M Gopikrishnan
    AIP Conference Proceedings 2518 (1), 090001 , 2022
    2022