Dr. K. S. Gayathri is an Associate Professor in the Department of Information Technology, with 25 years of teaching experience including Sri Sivasubramaniya Nadar College of Engineering and Sri Venkateswara College of Engineering. She holds a Ph.D. in Artificial Intelligence from Anna University and has built a research career at the intersection of artificial intelligence and assistive healthcare, applying deep learning to smart-home activity recognition, dementia and cognitive-decline detection, and posture and sleep analysis through wearable and non-wearable sensing. She was a Short-Term Research Scholar under the mentorship of Dr. Raj Reddy at Carnegie Mellon University, Pittsburgh, USA (September–December 2024). Dr. Gayathri actively guides doctoral research, having supervised one completed Ph.D. scholar, and has led major international conferences and faculty development programs in her field.

Work Experience

Teaching Experience: 25 years

• July 2026 – Till Date, Associate Professor, Shiv Nadar University, Chennai
• April 2023 – June 2026,  Associate Professor, Sri Sivasubramaniya Nadar College of Engineering
• June 2021 – March 2023, Assistant Professor, Sri Sivasubramaniya Nadar College of Engineering
• January 2013 – May 2021, Associate Professor, Sri Venkateswara College of Engineering
• June 2005 – December 2012, Assistant Professor, Sri Venkateswara College of Engineering
• June 2001 – June 2005,  Lecturer, Dr. MGR Engineering College

Projects

1. Ongoing

• SthiraSangyaan: An AI-Based Clinical Support System for the Diagnosis and Treatment of Neurodegenerative Parkinson Disease, Integrated with a Robotics-Driven Wearable Assistive Device for Fall Prevention in Patients with Motor and Cognitive Impairment – AICTE Research Promotion Scheme (RPS) – Lab to Market, 2026–2029, Rs. 29 Lakhs
• NutriApp: Multi-Agent System for Complex Decision-Making Using LLM – NVIDIA Academic Grant Program, 2025–2026, worthy Rs. 31 Lakhs
• 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,2024-2027, Rs. 25 Lakhs

2. Completed

• 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, Rs. 10,000
• Ambient Assisted Dementia Care through Smart Home with Activity Recognition, Abnormality Detection and Decision Support System using Artificial Intelligence and Machine Learning – Internally Funded Faculty Projects (IFFP-2021), Sponsored by SSN–HCL Trust, Dec 2021 – Dec 2024, Rs. 2 Lakhs
• 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, Oct 2019 – Oct 2020, Rs. 10,000

Publications

1. Journal Publications

1. D.S. Arunachalam, D. Andrew, K. S. Gayathri, and A. Shahina, “Sleep behavioural stability assessment via deep learning-based pressure map posture recognition and respiratory pattern analysis,” Engineering Research Express, IOP Publishing, 2026 (Scopus & Web of Science indexed; IF 1.6; Q2).
2. K.S. Gayathri, Ritheesh Kumar R, Varshini Ramesh, and Surendar Natarajan, “Enhancing satellite image segmentation for land use and land cover analysis using attention-based deep learning approach,” International Journal of System Assurance Engineering and Management, 2026 (Q2, Scopus).
3. Mohankumar, Parthiban, P. Charumathi, Sam Matthew Hendry, and K. S. Gayathri, “Ergoguard: a low-cost non-wearable machine learning-based posture enhancement system,” Discover Artificial Intelligence, vol. 6, no. 36, pp. 1–15, 2026 (Q1, Scopus).
4. R. Nirranjana, R. Aishwarya, S. Tejshree, K. S. Gayathri, et al., “Rainfall forecasting model for Amaravathi basin using machine learning approach,” Journal of The Institution of Engineers (India): Series A, Springer, 2025 (Q2, Scopus).
5. Rini P. L. and K. S. Gayathri, “Cognitive decline assessment using semantic linguistic content and transformer deep learning architecture,” International Journal of Language & Communication Disorders, 2024 (Impact Factor 2.4, Q1).
6. Rini P. L. and K. S. Gayathri, “Revolutionizing dementia detection: leveraging vision and Swin transformers for early diagnosis,” American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, Wiley, 2024. (Q1)
7. M. Badri Narayanan, Arun Ramesh, K. S. Gayathri, and A. Shahina, “Fake news detection using a deep learning transformer-based encoder-decoder architecture,” Journal of Intelligent & Fuzzy Systems, 2023.(Q2)
8. K.S. Gayathri, K. S. Easwarakumar, and Susan Elias, “Fuzzy ontology based activity recognition for assistive health care using smart home,” International Journal of Intelligent Information Technologies, vol. 16, no. 1, pp. 17–31, 2020 (Web of Science & Scopus indexed; IF 0.293).
9. R. S. Gayathri, K. S. Easwarakumar, and Susan Elias, “Probabilistic ontology based activity recognition in smart homes using Markov Logic Network,” Knowledge-Based Systems, Elsevier, vol. 121, pp. 173–184, 2017 (Impact Factor 4.529).
10. R. S. Anu Inba Mozhi and K. S. Gayathri, “Probabilistic Relational Model based approach for decision support systems,” International Journal of Control Theory and Applications, vol. 9, no. 10, pp. 453–461, 2016.
11. K. S. Gayathri, Susan Elias, and B. Ravindran, “Hierarchical activity recognition for dementia care using Markov Logic Network,” Personal and Ubiquitous Computing, Springer, vol. 19, no. 2, pp. 271–285, 2014 (Impact Factor 2.395).
12. “Semantic based sentence ordering approach for multi-document summarization,” International Journal of Recent Technology and Engineering, vol. 3, no. 2, 2014.
13. “An effective sentence ordering approach for multi-document summarization using text entailment,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 2, no. 1, pp. 1449–1494.
14. “Activity modeling in smart home using high utility pattern mining over data streams,” International Journal of Computer Science and Network, vol. 2, no. 3, 2013.
15. “An unsupervised pattern clustering approach for identifying abnormal user behaviours in smart homes,” International Journal of Computer Science and Network, vol. 2, no. 3, pp. 115–122, 2013.

2. Conference Publications

1. A. Shahina, M. C. V, N. K. Madhukrishaa, and G. K. S., “A comprehensive pipeline for detection and localization of focal epilepsy using EEG signals,” 2026 International Conference on Next Generation Electronics (NELEX), Vellore, India, 2026. (Scopus)
2. D. Sasikala, S. Sivapriya, and K. S. Gayathri, “Speech based early dementia detection using deep transformer networks,” 3rd International Conference on Research Methodologies in Knowledge Management, AI and Telecommunication Engineering (RMKMATE), 2026 (Scopus).
3. R. Meera and K. S. Gayathri, “Deep learning based real-time detection and monitoring of correct CPR posture to improve resuscitation,” International Conference on Electronics and Renewable Systems (ICEARS), Tuticorin, India, IEEE, pp. 213–218, 2026 (Scopus).
4. P. Vijaybaskar, T. Ashok, and K. S. Gayathri, “Multi-agent reasoning in large language models for nutrition and dietetics,” Intelligent Vision and Computing (ICIVC 2025), Lecture Notes in Networks and Systems, vol. 1711, Springer, 2026 (Scopus, Q4).
5. D. S. Arunachalam, D. Andrew, K. S. Gayathri, A. Shahina, V. Durgadevi, and A. Saravanan, “Sleep quality and body strain assessment through 3D pressure mapping using deep learning,” ICT Analysis and Applications (ICT4SD 2025), Lecture Notes in Networks and Systems, vol. 1651, Springer, 2026 (Scopus, Q4).
6. K. S. Gayathri, A. Piriyadharshini, B. Thejesswini, and P. Kumar, “Abnormal sitting posture recognition using skeletal framework and deep learning techniques,” 5th International Conference on Artificial Intelligence and Smart Energy (ICAIS 2025), Springer, 2025.
7. S. Jeyanthi and G. K. S., “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, 2025 (Scopus).
8. A. Shahina, M. S. Shriram, S. Sushmitha, and K. S. Gayathri, “Can structured data reduce epistemic uncertainty?,” First International Workshop on Next-Generation Language Models for Knowledge Representation and Reasoning (NeLaMKRR 2024), arXiv:2410.05339 (A* conference).
9. K. S. Gayathri, R. Mohana, and M. Sagana, “Personalized recommender system using topic modelling approach,” Intelligent Computing Systems and Applications (ICICSA 2023), Lecture Notes in Networks and Systems, vol. 1010, Springer, 2024 (Scopus).
10. “Motion prediction for autonomous vehicle using deep learning architecture and transfer learning,” ITM Web of Conferences, vol. 57, EDP Sciences (ICICSA-2023), 2023.
11. G. Pranav, K. Varsha, and K. S. Gayathri, “Early Alzheimer detection through speech analysis and vision transformer approach,” Communications in Computer and Information Science, Springer, 2023.
12. S. K. Bamrah, S. Srivatsan, and K. S. Gayathri, “Region classification for air quality estimation using deep learning and machine learning approach,” Machine Learning, Image Processing, Network Security and Data Sciences, Lecture Notes in Electrical Engineering, vol. 946, Springer, 2023.
13. S. Srivatsan, S. K. Bamrah, and K. S. Gayathri, “An ensemble approach to recognize activities in smart environment using motion sensors and air quality sensors,” Data Intelligence and Cognitive Informatics (ICDICI 2022), Springer, pp. 141–150, 2022.
14. S. Srivatsan, S. K. Bamrah, and K. S. Gayathri, “Determining the severity of dementia using ensemble learning,” International Conference on Big Data Analytics, Springer, pp. 117–135, 2022.
15. S. K. Bamrah, S. K. R., and G. K. S., “Application of random forests for air quality estimation in India by adopting terrain features,” 4th International Conference on Computer, Communication and Signal Processing (ICCCSP), Chennai, India, pp. 1–6, 2020.
16. K. S. Gayathri, K. S. Easwarakumar, and Susan Elias, “Contextual pattern clustering for ontology based activity recognition in smart home,” Smart Communications in Computer and Information Science, vol. 808, Springer, pp. 209–223, 2018 (Scopus indexed).
17. K. S. Gayathri and K. S. Easwarakumar, “Intelligent decision support system for dementia care through smart home,” Procedia Computer Science, Elsevier, vol. 3, pp. 947–955, 2016 (Scopus indexed; IF 1.26).
18. K. S. Gayathri, Susan Elias, and S. Shivasankar, “An ontology and pattern clustering approach for activity recognition in smart environments,” Advances in Intelligent Systems and Computing, vol. 258, Springer, pp. 833–843, 2014 (Scopus indexed; IF 0.57).
19. K. S. Gayathri, K. S. Easwarakumar, and Susan Elias, “Activity recognition and dementia care in smart home,” book chapter in Digital India: Advances in Theory and Practice of Emerging Markets, Springer Nature, pp. 33–47, 2018.
20. K. S. Gayathri, K. S. Easwarakumar, and Susan Elias, “Assistive dementia care system through smart home,” Smart Innovation, Systems and Technologies, Springer, vol. 79, pp. 455–467, 2018 (Scopus indexed).
21. K. S. Gayathri, Susan Elias, and S. Shivashankar, “Composite activity recognition in smart homes using Markov Logic Network,” IEEE 12th International Conference on Ubiquitous Intelligence and Computing, Indonesia, pp. 46–53, 2015.
22. S. Harish and K. S. Gayathri, “Smart home based prediction of symptoms of Alzheimer’s disease using machine learning and contextual approach,” International Conference on Computational Intelligence in Data Science (ICCIDS), IEEE, pp. 1–6, 2019.
23. “Abnormal user behavior detection in smart homes using pattern clustering,” National Conference on Advances in Computing and Technology (NCACT-13).
24. “Interactive mining of high utility patterns using linked transaction data streams,” International Conference on Computer Science and Information Technology (ICCSIT), pp. 188–193, 2013.
25. “Dynamic content adaptation for mobile multimedia communication,” International Conference on Advanced Computing & Communication Technologies for High Performance Applications, 2008.

3. Books Published

• S. Srivatsan, S. K. Bamrah, and K. S. Gayathri, “Multimodality dementia detection system using machine and deep learning,” in Computational Intelligence Aided Systems for Healthcare Domain, CRC Press, pp. 235–254, 2023.

Awards

• Best Teacher Award, 2022–2023 and 2023–2024
• Received the Wenlock Endowment Scholarship from Anna University in 2018, awarded for the high-impact research publication (2016–2017) titled “Probabilistic Ontology Based Activity Recognition in Smart Homes Using Markov Logic Network,” published in the Journal of Knowledge-Based Systems (Elsevier)
• Research poster accepted at the 2019 Grace Hopper Celebration (GHC 19), Orlando, Florida, titled “Ambient Assisted Dementia Care Using Smart Home Featuring Activity Recognition and Decision Support”

Area of Research

• Multimodal Deep Learning
• Agentic AI and Large Language Models
• Cognitive Computing and Intelligent Systems

Links

• ORCID: https://orcid.org/0000-0002-0971-0186
• Scopus ID: https://www.scopus.com/authid/detail.uri?authorId=58824333500
• Google Scholar: https://scholar.google.com/citations?hl=en&user=R1odoAwAAAAJ
• DBLP: https://dblp.org/pid/37/10546.html