RAMNATH M

@ritrjpm.ac.in

ASSISTANT PROFESSOR (S. G.), DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE
RAMCO INSTITUTE OF TECHNOLOGY

RAMNATH M


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https://researchid.co/ramnath

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Science
18

Scopus Publications

23

Scholar Citations

3

Scholar h-index

Scopus Publications

  • COURSE FORGE AI IN COMPUTERS: AN AGENTIC, MODULAR, AND EXPLAINABLE EDUCATIONAL ASSISTANT USING LLMS AND RAG
    Journal of Theoretical and Applied Information Technology, 2026
  • Analyzing Public Sentiment on Demonetization Using SVM: A Machine Learning Approach
    Kaliappan M, Guruprakash B, Rajalakshmi, J. Blessing Karunya T, Mariappan E, Ramnath M, Angel Hepzibah R
    Journal of Computer Science, 2025
    The Indian economy experienced significant disruption following the implementation of demonetization, a policy initiative aimed at eliminating black money, controlling inflation, and promoting financial inclusion. However, this currency ban generated widespread debate and polarized public opinion. This study analyzes public sentiment toward demonetization using social media data, specifically Twitter posts characterized by mixed sentiments, sarcasm, and nuanced linguistic expressions. We employ a PAD-SVM (Preprocessing-Analysis-Decision Support Vector Machine) approach comprising three stages: preprocessing, descriptive analysis, and prescriptive analysis. The preprocessing stage involves data cleaning, handling missing values, and feature extraction from tweet data. The descriptive analysis stage identifies key influencers and performs exploratory data analysis related to demonetization discourse. Subsequently, sentiment analysis is conducted to quantify user sentiments and assign polarity scores to individual tweets. Predictive modeling is then applied to forecast evolving public perception toward demonetization over time. This approach combines machine learning, statistical modeling, and natural language processing (NLP) techniques to process unstructured textual data and classify sentiments as positive, negative, or neutral. The integration of sentiment analysis with predictive analytics provides valuable real-time insights into public opinion dynamics and enables future trend forecasting regarding major economic policy interventions.
  • Real-Time Detection of Cracks and Structural Weaknesses in Materials and Surfaces Using Improved Deep Layered CNN
    K. Amudhan, K. Vignesh Saravanan, R. Venkatesh, M. Ramnath
    Journal of the Institution of Engineers India Series C, 2025
  • SECURE BROADCAST COMMUNICATION IN SENSOR NETWORKS: FORTIFYING THE KD AUTHENTICATION PROTOCOL
    Journal of Theoretical and Applied Information Technology, 2025
  • NEXT-GEN SECURITY: LEVERAGING DNA CRYPTOGRAPHY FOR ROBUST ENCRYPTION
    Journal of Theoretical and Applied Information Technology, 2025
  • Revolutionizing Agricultural Supply Chain Management with Blockchain-Based IoT: Improving Traceability, Efficiency and Sustainability
    Twinkle Geojini Gurupatham, Yesubai Rubavathi Charles, Ramnath Muthusamy
    Aip Conference Proceedings, 2025
  • High-precision malware detection in android apps using quantum explainable hierarchical interaction network
    Ramnath Muthusamy, Yesubai Rubavathi Charles
    Knowledge Based Systems, 2025
  • PREDICTIVE ANALYSIS ON DEMONETIZATION DATA USING SUPPORT VECTOR MACHINE TECHNIQUE
    Journal of Theoretical and Applied Information Technology, 2025
  • AI-POWERED RESUME SCREENING SYSTEM FOR SMART HIRING: LEVERAGING NLP AND LARGE LANGUAGE MODELS FOR EFFICIENT AND FAIR RECRUITMENT
    Journal of Theoretical and Applied Information Technology, 2025
  • Enhancing AppAuthentix recommender systems using advanced machine learning techniques to identify genuine and counterfeit android applications
    Ramnath M., Yesubai Rubavathi C.
    Peerj Computer Science, 2024
    Smartphone app expansion needs strict security measures to avoid fraud and danger. This study overcomes this issue by identifying apps differently. This new solution uses convolutional neural network (CNN), natural language processing (NLP), and the strong AppAuthentix Recommender algorithm to secure app stores and boost customer confidence in the digital marketplace. Since the app ecosystem has grown, counterfeit and harmful applications have risen, threatening consumers and app merchants. These risks need advanced technology that can distinguish malware from legitimate apps. A complex prediction model using CNNs for image analysis, NLP for text feature extraction, and the novel AppAuthentix Recommender algorithm to properly identify legitimate and counterfeit mobile applications is the goal of this research. The whole strategy secures app stores and authenticates apps. The urgent need to safeguard app markets and users against unauthorized and hazardous programs sparked this study. Our cutting-edge solutions make mobile app consumers’ digital lives safer and app marketplaces more trustworthy. CNN, NLP, and AppAuthentix Recommender yielded amazing results in this investigation. Mobile app authenticity may be estimated with 98.25% accuracy. This technology greatly improves app store security and enables mobile app verification. In conclusion, our work offers a novel way to app identification at a time of rapid mobile app development. CNN, NLP, and AppAuthentix Recommender have dramatically enhanced app store security. These new solutions may boost mobile app security and consumer confidence.
  • Oral Lesion Cell Segmentation and Classification using Convolution Neural Network Technique
    J. Amutha, S. Priyadarsini, S. Prasanth, M. R. Senkumar, M. Ramnath, T. Jasperline
    2024 IEEE 3rd World Conference on Applied Intelligence and Computing Aic 2024, 2024
  • Advancing Brain-Computer Interaction: EEG-based Eye Movement Recognition with AI
    Ravi Kumar Saidala, M. Ramnath, Komala C R, N. Gowri Vidhya, Syed Noeman Taqui, Rajendiran M
    7th International Conference on Inventive Computation Technologies Icict 2024, 2024
  • Machine Learning in Healthcare: Prognosis Heart Disease Prediction
    Ramnath M, Revathi B, Selva Birunda S, Usharani C, Ramana R, Tyson Masillamani J
    2024 4th International Conference on Advancement in Electronics and Communication Engineering Aece 2024, 2024
  • Recommendations of Smartphone Applications According to Customer Reviews and Capabilities
    M. Ramnath, C. Yesubai Rubavathi
    Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2023, 2023
  • Feature Adaptive Developmental Mechanisms for Mobile Apps Recommendations System using the Nearest Centroid Classification Algorithm
    G. Twinkle Geojini, M. Ramnath, C. Yesubai Rubavathi
    7th International Conference on Trends in Electronics and Informatics Icoei 2023 Proceedings, 2023
  • Prediction of Breast Cancer Risk Using Microarrays and Deep Learning
    R. Madhubala Shanmu, P. Brundha, G. Aravind Swaminathan, R. Tino Merlin, V. Hemamalini, M. Ramnath
    Proceedings of the 1st IEEE International Conference on Networking and Communications 2023 Icnwc 2023, 2023
  • Towards Enhanced Deep CNN for Early and Precise Skin Cancer Diagnosis
    S. Malaiarasan, R. Ravi, D.R. Maheswari, C.Yesubai Rubavathi, M. Ramnath, V. Hemamalini
    Proceedings of the 1st IEEE International Conference on Networking and Communications 2023 Icnwc 2023, 2023
  • App assessment with three phase evidence system using sentiment analysis
    M. Ramnath, C. Yesubai Rubavathi
    Proceedings of the 3rd International Conference on Intelligent Communication Technologies and Virtual Mobile Networks Icicv 2021, 2021

RECENT SCHOLAR PUBLICATIONS

  • COURSE FORGE AI IN COMPUTERS: AN AGENTIC, MODULAR, AND EXPLAINABLE EDUCATIONAL ASSISTANT USING LLMS AND RAG
    MG LENIN MARKSIA U, JEYASHANTHI J, JEGADEESH A, KALIAPPAN M, MARIAPPAN E ...
    Journal of Theoretical and Applied Information Technology 104 (02), 53-68 , 2026
    2026
  • COURSE FORGE AI IN COMPUTERS: AN AGENTIC, MODULAR, AND EXPLAINABLE EDUCATIONAL ASSISTANT USING LLMS AND RAG
    MG LENIN MARKSIA U, JEYASHANTHI J, JEGADEESH A3, KALIAPPAN M, MARIAPPAN E ...
    Journal of Theoretical and Applied Information Technology 104 (02), 53-68 , 2026
    2026
  • Analyzing Public Sentiment on Demonetization Using SVM: A Machine Learning Approach
    AHR Kaliappan M. 1 , Guruprakash B. 2 , Rajalakshmi3 , J. Blessing Karunya T ...
    Journal of Computer Science 21 (11), 2482-2487 , 2025
    2025
  • AI-POWERED RESUME SCREENING SYSTEM FOR SMART HIRING: LEVERAGING NLP AND LARGE LANGUAGE MODELS FOR EFFICIENT AND FAIR RECRUITMENT
    RM ANGEL HEPZIBAH R, JEYASANTHI J, DURGA DEVI G, MARIAPPAN E, KALIAPPAN M ...
    Journal of Theoretical and Applied Information Technology 103 (23), 10146 … , 2025
    2025
  • PREDICTIVE ANALYSIS ON DEMONETIZATION DATA USING SUPPORT VECTOR MACHINE TECHNIQUE
    VS KALIAPPAN M1 , MARIAPPAN E2 , RAMNATH M3 , KARPAGAVALLI C4 , ANGEL ...
    Journal of Theoretical and Applied Information Technology 103 (1), 317-327 , 2025
    2025
  • PREDICTIVE ANALYSIS ON DEMONETIZATION DATA USING SUPPORT VECTOR MACHINE TECHNIQUE
    VS KALIAPPAN M, MARIAPPAN E, RAMNATH M, KARPAGAVALLI C, ANGEL HEPZIBAH R
    https://www.jatit.org/volumes/Vol103No1/27Vol103No1.pdf , 2025
    2025
  • ISL Sign Language Recognition Using LSTM-Driven Deep Learning Model
    ST Guruprakash B, Nagarajan Gurusamy, RamnathM, Sumathi S, Mariappan E
    https://journal.esrgroups.org/jes/article/view/7496/5149 , 2024
    2024
  • Maximizing Solar Energy Efficiency Through Grasshopper Algorithm-Based Site Selection
    AHR Anna Lakshmi A, Ramaswamy S, Mariappan E, Kaliappan M, Ramnath M
    https://journal.esrgroups.org/jes/article/view/7132/4909 , 2024
    2024
  • Machine Learning in Healthcare: Prognosis Heart Disease Prediction
    M Ramnath, B Revathi, S Selva Birunda, C Usharani, R Ramana, ...
    2024 4th International Conference on Advancement in Electronics … , 2024
    2024
  • Enhancing AppAuthentix recommender systems using advanced machine learning techniques to identify genuine and counterfeit android applications
    M Ramnath
    PeerJ Computer Science 10, e2515 , 2024
    2024
  • LDPC CODE BASED AUTOENCODER OF AWSN USING DEEP NEURAL NETWORKS MODEL FOR WIRELESS COMMUNICATION CHANNEL
    DME VAISSNAVE V, AMUTHACHENTHIRU K, DURGA DEVI G, Dr. ANNA LAKSHMI A, Dr ...
    https://tianjindaxuexuebao.com/details.php?id=DOI:10.5281/zenodo.14043365 , 2024
    2024
  • Dragonfly Algorithm-Based Approach for Solar Power Plant Optimization in IEEE 69-Bus Network
    KC Angel Hepzibah R., Anna Lakshmi A., Mariappan E., Kaliappan M., Sugel ...
    https://www.thelearner-ijsmtl-cgrn.org/cgrn/issue-details.php?pid=474 , 2024
    2024
  • Heart Disease Prediction: A Machine Learning Model for Evaluation and Hyperparameter Tuning
    RMDAALKCSTLVBTTGGD Mariappan E+
    https://africanjournalofbiomedicalresearch.com/index.php/AJBR/article/view/2891 , 2024
    2024
  • Enhanced Solar Plant Positioning Using Moth-Flame Optimization Technique
    DEMMDADTJDPEDAJDMKMMRMRA Hepzibah+
    https://africanjournalofbiomedicalresearch.com/index.php/AJBR/article/view/2845 , 2024
    2024
  • AN EXAMINING CLUSTER BEHAVIOUR ANALYTICALLY USING KMEANS, EM, AND K* MEANS ALGORITHM
    RM Dr. MARRIAPPAN E, Dr. ANNA LAKSHMI A, AMALA PRINCETON X, VETRIVEL P, Dr ...
    https://tianjindaxuexuebao.com/details.php?id=DOI:10.5281/zenodo.14038149 , 2024
    2024
  • Oral Lesion Cell Segmentation and Classification using Convolution Neural Network Technique
    J Amutha, S Priyadarsini, S Prasanth, MR Senkumar, M Ramnath, ...
    2024 IEEE 3rd World Conference on Applied Intelligence and Computing (AIC … , 2024
    2024
    Citations: 1
  • Advancing Brain-Computer Interaction: EEG-based Eye Movement Recognition with AI
    RK Saidala, M Ramnath, NG Vidhya, SN Taqui
    2024 International Conference on Inventive Computation Technologies (ICICT … , 2024
    2024
    Citations: 1
  • 7th International Conference onInventive Computation Technologies (ICICT 2024) 24–26 April, 2024
    NSS Reddy, VVA Rohith, PS Abhiram, MD Siva, R Saran, S Rebecca, ...
    Artificial Intelligence 18, 5 , 2024
    2024
  • Benign and Malignant Cancer Prediction Using Deep Learning and Generating Pathologist Diagnostic Report
    K Madasamy, V Shanmuganathan, Nithish, Vishakan, Vijayabhaskar, ...
    International Conference on IoT and Health, 73-87 , 2023
    2023
  • Recommendations of smartphone applications according to customer reviews and capabilities
    M Ramnath, CY Rubavathi
    2023 Second International Conference on Augmented Intelligence and … , 2023
    2023
    Citations: 5

MOST CITED SCHOLAR PUBLICATIONS

  • Towards enhanced deep cnn for early and precise skin cancer diagnosis
    S Malaiarasan, R Ravi, DR Maheswari, CY Rubavathi, M Ramnath, ...
    2023 International Conference on Networking and Communications (ICNWC), 1-7 , 2023
    2023
    Citations: 7
  • Recommendations of smartphone applications according to customer reviews and capabilities
    M Ramnath, CY Rubavathi
    2023 Second International Conference on Augmented Intelligence and … , 2023
    2023
    Citations: 5
  • App Assessment with Three Phase Evidence System using Sentiment Analysis
    M Ramnath, CY Rubavathi
    2021 Third International Conference on Intelligent Communication … , 2021
    2021
    Citations: 4
  • Dynamic analysis of agent network in self organization using service level agreement technique
    DK Jesintha, JP Anandh, M Ramnath
    Int. J. of Eng. Sci. Invent 4 (3), 44-49 , 2015
    2015
    Citations: 3
  • Oral Lesion Cell Segmentation and Classification using Convolution Neural Network Technique
    J Amutha, S Priyadarsini, S Prasanth, MR Senkumar, M Ramnath, ...
    2024 IEEE 3rd World Conference on Applied Intelligence and Computing (AIC … , 2024
    2024
    Citations: 1
  • Advancing Brain-Computer Interaction: EEG-based Eye Movement Recognition with AI
    RK Saidala, M Ramnath, NG Vidhya, SN Taqui
    2024 International Conference on Inventive Computation Technologies (ICICT … , 2024
    2024
    Citations: 1
  • Feature Adaptive Developmental Mechanisms for Mobile Apps Recommendations System using the Nearest Centroid Classification Algorithm
    GT Geojini, M Ramnath, CY Rubavathi
    2023 7th International Conference on Trends in Electronics and Informatics … , 2023
    2023
    Citations: 1
  • Prediction of Breast Cancer Risk Using Microarrays and Deep Learning
    RM Shanmu, P Brundha, GA Swaminathan, RT Merlin, V Hemamalini, ...
    2023 International Conference on Networking and Communications (ICNWC), 1-6 , 2023
    2023
    Citations: 1
  • COURSE FORGE AI IN COMPUTERS: AN AGENTIC, MODULAR, AND EXPLAINABLE EDUCATIONAL ASSISTANT USING LLMS AND RAG
    MG LENIN MARKSIA U, JEYASHANTHI J, JEGADEESH A, KALIAPPAN M, MARIAPPAN E ...
    Journal of Theoretical and Applied Information Technology 104 (02), 53-68 , 2026
    2026
  • COURSE FORGE AI IN COMPUTERS: AN AGENTIC, MODULAR, AND EXPLAINABLE EDUCATIONAL ASSISTANT USING LLMS AND RAG
    MG LENIN MARKSIA U, JEYASHANTHI J, JEGADEESH A3, KALIAPPAN M, MARIAPPAN E ...
    Journal of Theoretical and Applied Information Technology 104 (02), 53-68 , 2026
    2026
  • Analyzing Public Sentiment on Demonetization Using SVM: A Machine Learning Approach
    AHR Kaliappan M. 1 , Guruprakash B. 2 , Rajalakshmi3 , J. Blessing Karunya T ...
    Journal of Computer Science 21 (11), 2482-2487 , 2025
    2025
  • AI-POWERED RESUME SCREENING SYSTEM FOR SMART HIRING: LEVERAGING NLP AND LARGE LANGUAGE MODELS FOR EFFICIENT AND FAIR RECRUITMENT
    RM ANGEL HEPZIBAH R, JEYASANTHI J, DURGA DEVI G, MARIAPPAN E, KALIAPPAN M ...
    Journal of Theoretical and Applied Information Technology 103 (23), 10146 … , 2025
    2025
  • PREDICTIVE ANALYSIS ON DEMONETIZATION DATA USING SUPPORT VECTOR MACHINE TECHNIQUE
    VS KALIAPPAN M1 , MARIAPPAN E2 , RAMNATH M3 , KARPAGAVALLI C4 , ANGEL ...
    Journal of Theoretical and Applied Information Technology 103 (1), 317-327 , 2025
    2025
  • PREDICTIVE ANALYSIS ON DEMONETIZATION DATA USING SUPPORT VECTOR MACHINE TECHNIQUE
    VS KALIAPPAN M, MARIAPPAN E, RAMNATH M, KARPAGAVALLI C, ANGEL HEPZIBAH R
    https://www.jatit.org/volumes/Vol103No1/27Vol103No1.pdf , 2025
    2025
  • ISL Sign Language Recognition Using LSTM-Driven Deep Learning Model
    ST Guruprakash B, Nagarajan Gurusamy, RamnathM, Sumathi S, Mariappan E
    https://journal.esrgroups.org/jes/article/view/7496/5149 , 2024
    2024
  • Maximizing Solar Energy Efficiency Through Grasshopper Algorithm-Based Site Selection
    AHR Anna Lakshmi A, Ramaswamy S, Mariappan E, Kaliappan M, Ramnath M
    https://journal.esrgroups.org/jes/article/view/7132/4909 , 2024
    2024
  • Machine Learning in Healthcare: Prognosis Heart Disease Prediction
    M Ramnath, B Revathi, S Selva Birunda, C Usharani, R Ramana, ...
    2024 4th International Conference on Advancement in Electronics … , 2024
    2024
  • Enhancing AppAuthentix recommender systems using advanced machine learning techniques to identify genuine and counterfeit android applications
    M Ramnath
    PeerJ Computer Science 10, e2515 , 2024
    2024
  • LDPC CODE BASED AUTOENCODER OF AWSN USING DEEP NEURAL NETWORKS MODEL FOR WIRELESS COMMUNICATION CHANNEL
    DME VAISSNAVE V, AMUTHACHENTHIRU K, DURGA DEVI G, Dr. ANNA LAKSHMI A, Dr ...
    https://tianjindaxuexuebao.com/details.php?id=DOI:10.5281/zenodo.14043365 , 2024
    2024
  • Dragonfly Algorithm-Based Approach for Solar Power Plant Optimization in IEEE 69-Bus Network
    KC Angel Hepzibah R., Anna Lakshmi A., Mariappan E., Kaliappan M., Sugel ...
    https://www.thelearner-ijsmtl-cgrn.org/cgrn/issue-details.php?pid=474 , 2024
    2024