Dr. K.S. Gayathri
B.E., M.E., Ph.D
Associate Professor
Department of Information Technology
Extn : 224
Dr. K. S. Gayathri has over 24 years of teaching experience in the field of Computer Science
and Engineering. She received her Bachelor’s degree in Computer Science and Engineering
from Madras University in 2001 and her Master’s degree in Department of Computer Science
and Engineering from Anna University in 2009. She earned her Ph.D. in Artificial
Intelligence from Anna University in 2018, with her thesis titled “Activity Recognition in
Smart Home.” Dr. Gayathri served as a Short-Term Research Scholar under the mentorship
of Dr. Raj Reddy at Carnegie Mellon University, Pittsburgh, USA, from September 2024 to
December 2024.
She is a recognized research supervisor under Anna University and currently guides seven Ph.D. scholars, in addition to mentoring several projects across diverse domains of Artificial Intelligence. Her primary research interests include Artificial Intelligence, Machine Learning, Deep Learning, and Agentic AI. She has published more than 35 research papers in reputed international journals and conferences and serves as an active reviewer for leading international journals published by IEEE Transactions, Elsevier, and Springer. She received a Certificate of Appreciation from Anna University (2018) for a publication in the high-impact factor Elsevier journal.
She is a recognized research supervisor under Anna University and currently guides seven Ph.D. scholars, in addition to mentoring several projects across diverse domains of Artificial Intelligence. Her primary research interests include Artificial Intelligence, Machine Learning, Deep Learning, and Agentic AI. She has published more than 35 research papers in reputed international journals and conferences and serves as an active reviewer for leading international journals published by IEEE Transactions, Elsevier, and Springer. She received a Certificate of Appreciation from Anna University (2018) for a publication in the high-impact factor Elsevier journal.
| Sno | Title | Sponsoring Agency | Period | Amount in INR |
| 1 | NutriApp: Multi-Agent System for Complex Decision-Making Using LLM" | NVIDIA Corporation | 2025-2026 | 31 Lakhs |
| 2 | Development of Deep Learning Models for Automatic Detection and classification of multiple sleep disorders from multimodal data using wearable charge transfer ST QVAR Multisensor | ST MEMS Technologies and Solutions | 2023-2026 | 27 lakhs |
| 3 | Satellite Image Segmentation for Land Use and Land Cover Analysis using Attention-based Deep Learning Approach | Naan Mudhalvan Niral Thiruvizha, Tamil Nadu Skill Development Corporation | 2023-2024 | 0.1 Lakh |
| 4 | Ambient assisted dementia care through smart home with activity recognition, abnormality detection and decision support system using artificial intelligence and machine learning technique | SSN -HCL Trust | 2021-2024 | 2 Lakhs |
| 5 | Estimation of air quality in Indian cities using adaptive framework based on transfer learning and semi supervised Learning | Intramural Research Funded Project, Sri Venkateswara College of Engineering | 2019-2020 | 0.1 Lakh |
IEEE, ACM, ISTE
Journal Publications
- Nirranjana, R., Aishwarya, R., Tejshree, S. Gayathri K S et al. (2025). Rainfall Forecasting Model for Amaravathi Basin Using Machine Learning Approach. Journal of The Institution of Engineers (India): Series A, Springer, https://doi.org/10.1007/s40030-025-00914-9 (Q2, Scopus)
- Rini PL and Gayathri KS, (2024). Cognitive decline assessment using semantic linguistic content and transformer deep learning architecture. International Journal of Language & Communication Disorders, Vol.-1, Print ISSN: 1368-2822, Online ISSN: 1460-6984, Impact factor 2.4. (DOI: https://doi.org/10.1111/1460-6984.12973)
- Rini PL and Gayathri KS, (2024). Revolutionizing dementia detection: Leveraging vision and Swin transformers for early diagnosis. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics (AJMGB), Wiley, Published online, ISSN:1552-484. (DOI: https://doi.org/10.1002/ajmg.b.32979)
- Narayanan, M Badri, Ramesh, Arun, K.S, Gayathri & A., Shahina. (2023). Fake news detection using a deep learning transformer based encoder-decoder architecture. Journal of Intelligent & Fuzzy Systems. 1-13. 10.3233/JIFS-223980.
- Gayathri K S, Easwarakumar K S, Susan Elias, (2020). Fuzzy Ontology Based Activity Recognition for Assistive Health Care Using Smart Home. International Journal of Intelligent Information Technologies (IJIIT), Volume 16, Issue 1, pp 17-31. doi: 10.4018/IJIIT.2020010102 (Web of Science and Scopus indexed) Impact factor 0.293, ISSN 1548-3657.
- Gayathri K S, Easwarakumar K S and Susan Elias (2017). Probabilistic ontology based activity recognition in smart homes using Markov Logic Network. Journal on Knowledge-Based Systems, Elsevier, vol. 121, pp. 173–184. Impact factor: 4.529, ISSN: 0950-7051.
- Anu Inba Mozhi R.S. and Gayathri K.S (2016). Probabilistic Relational Model based approach for Decision Support Systems. International Journal of Control Theory and Applications (IJCTA), Volume 9(10), pp. 453-461 (Annexure 2), Impact factor 0.175, ISSN 0974-5572.
- Gayathri K S, Susan Elias and Ravindran B (2014). Hierarchical activity recognition for dementia care using markov logic network. Journal on Personal and Ubiquitous Computing, Springer-Verlag London, vol. 19, no. 2, pp. 271–285. Impact factor: 2.395, ISSN 1617-4909.
Conference Publications
- Gayathri, K.S., Piriyadharshini, A., Thejesswini, B., Kumar, P. (2025). Abnormal Sitting Posture Recognition Using Skeletal Framework and Deep Learning Techniques. In: Manoharan, S., Tugui, A., Perikos, I. (eds) Proceedings of 5th International Conference on Artificial Intelligence and Smart Energy (ICAIS 2025). Information Systems Engineering and Management, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-031-90478-3_22
- S. Jeyanthi and G. K. S. (2025). Vision-Based Fall Detection System: a Machine Learning Approach for Real-Time Alert and Intervention. 11th International Conference on Communication and Signal Processing (ICCSP), IEEE, pp. 211-216. DOI: 10.1109/ICCSP64183.2025.11088509
- Shahina A, Shriram M S, Sushmitha S, Gayathri K S. (2024). Can Structured Data Reduce Epistemic Uncertainty? Proceedings of the First International Workshop on Next-Generation Language Models for Knowledge Representation and Reasoning (NeLaMKRR 2024), arXiv:2410.05339.
- Gayathri, K.S., Mohana, R., Sagana, M. (2024). Personalized Recommender System Using Topic Modelling Approach. Intelligent Computing Systems and Applications. ICICSA 2023. Lecture Notes in Networks and Systems, vol 1010. Springer, Singapore. https://doi.org/10.1007/978-981-97-5412-0_11
- Motion Prediction for Autonomous Vehicle using Deep Learning Architecture and Transfer Learning. (2023). In ITM Web of Conferences (Vol. 57). EDP Sciences (ICICSA-2023), September 22–23, 2023.
- Pranav, G., Varsha, K., K.S. Gayathri (2023). Early Alzheimer Detection Through Speech Analysis and Vision Transformer Approach. Communications in Computer and Information Science, Springer Series. https://doi.org/10.1007/978-3-031-33231-9_19
- Bamrah, S.K., Srivatsan, S., Gayathri, K.S. (2023). Region Classification for Air Quality Estimation Using Deep Learning and Machine Learning Approach. In: Doriya, R., Soni, B., Shukla, A., Gao, XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. Lecture Notes in Electrical Engineering, vol 946. Springer, Singapore. https://doi.org/10.1007/978-981-19-5868-7_25
Notable Events Organized
- The 7th International Conference on Computer, Communication and Signal Processing (ICCCSP 2023) organized on January 5–6, 2023, with proceedings published by Springer.
- Faculty Development Program (FDP) on “Generative AI and Quantum Technologies for Embedded Intelligent Systems: Driving Innovations Across Industries” — conducted from July 28 to August 2, 2025, focusing on emerging trends in AI and quantum computing.
- Industry-Aligned Value-Added Course on JavaScript and Java, a 16-hour program organized during September 2–23, 2025, to enhance student employability and industry readiness.
Research Citations