Profile
Dr. Nanthini K
Associate Professor
Dr. Nanthini K is a dedicated academician and researcher with a strong specialization in Machine Learning (ML) and Deep Learning (DL), with particular emphasis on their application to real-world challenges, especially in the healthcare domain. Her research focuses on developing intelligent computational approaches for clinical and diagnostic applications, contributing to the integration of emerging technologies with healthcare practices and bridging the gap between computational intelligence and medical decision-making.
She has actively contributed to academic and professional development through technical sessions, workshops, and hands-on training programmes on emerging technologies, including Machine Learning and Internet of Things (IoT) applications in healthcare. She has also conducted practical training in Python programming, with a specific focus on its applications in Machine Learning and data-driven research.
Dr. Nanthini K qualified the University Grants Commission – National Eligibility Test (UGC-NET) in December 2024, conducted by the University Grants Commission (UGC), New Delhi. She has published more than 20 research articles in reputed Scopus- and SCI-indexed journals and international conferences, reflecting her active engagement in research and scholarly activities.
She completed her Ph.D. (Part-time) in the area of Neurological Disorders Classification using Deep Learning from Anna University, Chennai, Tamil Nadu, in April 2025. Her academic and research interests continue to focus on advancing intelligent computational techniques and their practical applications in healthcare and other real-world domains.
Area
Qualification
B.Sc.,MCA.,M.Phil.,PhD, UGC-NET
Experience
18 Years
Publications
Pyingkodi, M., Shanthi, S., Muthukumaran, M., Nanthini, K., & Thenmozhi, K. (2020). Hybrid bee colony and weighted ranking firefly optimization for cancer detection from gene regulatory sequences. International Journal of Scientific & Technology Research, 9(01). (Journal- Scopus)
Pyingkodi M, Shanthi S, Thenmozhi K, Hemalatha D & Nanthini K. A novel deep learning method for identification of cancer genes from gene expression dataset. Machine Learning and Deep Learning in Real-Time Applications, Vol. 9, 2020, pp.129-144. (Book Chapter – Scopus)
Dhivya M, Pyingkodi M, Shanthi S, Saravanan T.M, Thenmozhi K, Nanthini K, Hemalatha D & Muthukumaran M. Performance Study of Classification Algorithms Using the Microarray Breast Cancer Dataset. International Journal of Future Generation Communication and Networking, 13(2), 2020. (Journal – Scopus)
Pyingkodi, M., Thenmozhi, K., Karthikeyan, M., Nanthini, K., Martin, A. A., Deepak, P. V., & Jegan, K. (2022, March). IoT technologies for precision agriculture: a survey. In 2022 6th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 372-376). IEEE. (Conference-Scopus)
Pyingkodi, M., Thenmozhi, K., Nanthini, K., Karthikeyan, M., Palarimath, S., Erajavignesh, V., & Kumar, G. B. A. (2022, January). Sensor based smart agriculture with IoT technologies: a review. In 2022 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1-7). IEEE. (Conference-Scopus)
Nanthini, K., Pyingkodi, M., & Sivabalaselvamani, D. (2022, August). EEG Signal Analysis for Emotional Classification. In 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 192-198). (Conference-Scopus)
Nanthini, K., Pyingkodi, M., Sivabalaselvamani, D., Kumari, S., & Kumar, T. (2022). Performance analysis of machine learning algorithms in Heart diseases prediction. In IoT Based Control Networks and Intelligent Systems: Proceedings of 3rd ICICNIS 2022 (pp. 407-423). Singapore: Springer Nature Singapore. (Conference-Scopus)
Pyingkodi, M., Thenmozhi, K., Nanthini, K., Karthikeyan, M., Kalpana, T., & Deepak, P. V. (2023). Examination of Water Impurities Using IoT and Machine Learning Techniques. In IoT Based Control Networks and Intelligent Systems (pp. 675-687). Springer, Singapore. (Conference-Scopus)
Nanthini, K., Sivabalaselvamani, D., Chitra, K., Gokul, P., KavinKumar, S., & Kishore, S. (2023, February). A Survey on Data Augmentation Techniques. In 2023 7th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 913-920). IEEE. (Conference-Scopus)
Nanthini, K., Sivabalaselvamani, D., Selvakarthi, D., Pavethran, D., Srinaath, N., & Vignesh, K. S. (2023, March). Performance of Recurrent Neural Networks in Liver Disease Classification. In 2023 Second International Conference on Electronics and Renewable Systems (ICEARS) (pp. 1491-1497). IEEE. (Conference-Scopus)
Nanthini, K., Sivabalaselvamani, D., Chitra, K., Mohideen, P. A., & Raja, R. D. (2023, March). Cardiac Arrhythmia Detection and Prediction Using Deep Learning Technique. In Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems: ICCCES 2022 (pp. 983-1003). Singapore: Springer Nature Singapore. (Conference-Scopus)
Nanthini, K., Sivabalaselvamani, D., Sharvanthika, K. S., Ojha, S. K., & Siva, M. (2023, December). Diabetic Retinopathy Detection using Squeezenet. In 2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS) (pp. 695-701). IEEE. (Conference-Scopus)
Sivabalaselvamani, D., Rahunathan, L., Nanthini, K., Harshini, T., & Hariprasath, C. (2023, August). Soil classification using deep learning techniques. In 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) (pp. 582-586). IEEE. (Conference-Scopus)
Sivabalaselvamani, D., Nanthini, K., Selvakarthi, D., Niranchan, V. M., Kumar, L. S., & Swetha, P. (2023, September). Skin melanoma detection using image augmentation. In 2023 4th International Conference on Smart Electronics and Communication (ICOSEC) (pp. 1624-1630). IEEE. (Conference-Scopus)
Chitra, K., Tamilarasi, A., Pyingkodi, M., Nanthini, K., Sneka, V., Swetha, S., & Vishalini, P. (2023, January). Animals detection system in the farm area using IoT. In 2023 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1-6). IEEE. (Conference-Scopus)
Nanthini, K., Tamilarasi, A., Sivabalaselvamani, D., Harini, V. S., Janaki, R., & Madhan, V. K. (2024). EEG signal classification using 1D-CNN and BILSTM. In Artificial Intelligence, Blockchain, Computing and Security Volume 2 (pp. 453-457). CRC Press. (Book Chapter – Scopus)
Sivabalaselvamani, D., Nanthini, K., Vanithamani, S., & Nivetha, L. (2023). Performance of deep learning approaches for detection and classification of ceramic tile defects. Journal of Ceramic Processing Research, 24(1), 78-88. (SCI)
Sivabalaselvamani, D., Nanthini, K., Nagaraj, B. K., Kannan, K. G., Hariharan, K., & Mallingeshwaran, M. (2024). Healthcare Monitoring and Analysis Using ThingSpeak IoT Platform: Capturing and Analyzing Sensor Data for Enhanced Patient Care. In Advanced Applications in Osmotic Computing (pp. 126-150). IGI Global. (Book Chapter – Scopus)
Nanthini K., Tamilarasi A., Sivabalaselvamani D., & Suresh, P. Automated classification of Alzheimer’s disease based on deep belief neural networks. Neural Computing and Applications, 2024, vol. 36, pp.1-15. (SCI)
Nanthini K., Sivabalaselvamani D., MC Madhan Kumar, & R Kaviya. (2024). Comprehensive EEG Signal Feature Extraction for Neurological Disorder Diagnosis: Focus on Alzheimer’s, Parkinson’s, and Seizure Disorders. International Research Journal of Multidisciplinary Technovation, 6(5), 80-93. (Journal-Scopus)
- D. Sivabalaselvamani, Ranjit Singh Sarban Singh, S. Hemalatha, A. Prabhu, and K. Nanthini, “Enhancing Bone Cancer Detection Using AI-Based Multi-Model Ensemble Deep Learning Techniques,” CRC Press, Taylor & Francis Group, September 2025. (Scopus – Book Chapter)
- Nanthini, K., Dey, A. K., Prabha, S., Khurana, S., Dhingra, L., & Kumar, A. (2025, April). “Development of a New Mathematical Optimization Technique for Enhancing MPPT Performance in Photovoltaic Systems.” In 2025 International Conference on Metaverse and Current Trends in Computing (ICMCTC) (pp. 1–13). IEEE. (Scopus – Conference)
- Sivabalaselvamani, D., Nanthini, K., Kavitha, R. K., Jayapriya, P., Singh, W. J., & Hemalatha, S. (2026). “Deep Learning Benchmarking for Low-Resource Tamil News Classification Using Controlled Dataset Balancing and Augmentation.” Array, 101034. (Scopus & WoS – Journal)
- Padmapriya, M., Bremnavas, D. I., Adaikalam, V., P. G., G., Nanthini, K., & Puspha, J. (2026). “Chainbreaker: A Graph-Based Framework for Flow-Level Persistent Advanced Threat Detection, Attack Chain Reconstruction, and Forensic Investigation.” International Journal of Artificial Intelligence and Machine Learning, 6(5s), 497–513. (Scopus – Journal)
- Joshi, M., Nanthini, K., Devi, S., & Swain, B. (2026). “The Future of Behavioral Natural Language Processing in Healthcare.” In Natural Language Processing in Mental Health Care: Methodologies and Clinical Practice (pp. 195–214). (Scopus – Book Chapter)
- SouprayenBalamurugan, Prabhakar Devi, Paianoor Nandhakumar, Naveen Kumar, Kempaiyan Nanthini, Ramaswamy Maruthamuthu. “Smart Monitoring and Analysis of Food Data: A C5.0 Bayesian Network Framework Integrated with Computer Vision and IoT.” In Blockchain and Artificial Intelligence for Secure Computer Vision Technologies and Applications. Book Chapter, 2026. (Scopus – Book Chapter)
FDPs
Attended “FULLSTACK DEVELOPMENT” from 14/07/2025 to 18/07/2025 organized by Jain-GUVI (HCL).
Attended “Cybersecurity” from 04/09/2025 to 08/09/2025 organized by MMTTP-IIT Chennai.
Academic Conferences
Nanthini K, Padmapriya M. R., Balamurugan S., & Bremnavas I. (2024). Investigation of Sustainable Medical Waste Solutions using AI driven Circular Economy. Circular Economy and Artificial Intelligence for Sustainable Future, Jain University.
Padmapriya M. R., Nanthini K., Balamurugan S., & Bremnavas I. (2024). Transforming Electronic Health Records for Sustainable Patient Care Enhancement through AI and Circular Economy Principles. Circular Economy and Artificial Intelligence for Sustainable Future, Jain University.
Nanthini K, Padmapriya M R, Abhijith T S, Bindhusree, Bhavani “AI- based Adaptive firewall for cyber Threats Detectionusing reinforcement Learning” International Conference on Recent Engineering and Technology 2026, Sai Vidya Institute of Technology Collaboration with Samarkand State University, 2026.
Professional Affliations
- Article Reviewer Since January 2025 – RAC Member ( September 2025)
Patents
- Application number 202541044504, Title: FACULTY RESEARCH PUBLICATION CITATION TRACKER APPLICATION, Publication Date on 30th May 2025 (MRP project sanctioned by Jain University Rs.1,55,000.
Additional Information
Delivered a session lecture on Machine Learning and IoT in Healthcare in the AICTE Sponsored STTP on Machine Learning Applications to IoT on 06.03.2021, organized by Velammal College of Engineering and Technology, Madurai.
Delivered a hands-on session on Machine Learning with Python Programming using Google Colab on 17.08.2023, organized by Saaurie Arts and Science College, Vijayamangalam.
Delivered a hands-on session on Machine Learning Classification using Python on 23.01.2024, organized by PKR Arts and Science College, Gobichettipalayam.
Delivered a session lecture on Precision Healthcare at Kongu Engineering College, Perundurai in August 2024.
