Dr. Premalatha S | Neuroscience | Best Researcher Award
Assistant Professor | Karpagam College of Engineering | India
Dr. S. Premalatha is currently serving as an Assistant Professor in the Science and Humanities Department at Karpagam College of Engineering, Coimbatore, Tamil Nadu, India. She completed her M.Phil. in Mathematics in 2016 at Bharathiar University, Coimbatore, and earned her Ph.D. in 2025 from the same institution, demonstrating a sustained commitment to advancing mathematical research. Her key research areas include Neural Networks, Differential Equations, and the theoretical and applied aspects of memristive inertial neural networks (MINNs), with a particular focus on stability, synchronization, dissipativity analyses, and reduced-order modeling of complex dynamical systems. Over the years, Dr. Premalatha has published six high-impact research articles in reputed SCI and Scopus-indexed journals, significantly contributing to the understanding of nonlinear neural network behaviors and secure communication frameworks. Her work has been cited widely, reflecting her growing influence in the field, with a citation index of 143. She is an active member of professional bodies such as ISTE, and her dedication to academic excellence has earned her nominations for awards including the Best Researcher Award, Women Research Award, Young Scientist Award, and Best Paper Award. While she has not yet held formal editorial roles, her publications have contributed to shaping contemporary research directions in neural network theory and applied mathematics, and she continues to mentor and inspire the next generation of engineers and mathematicians through her teaching and scholarly endeavors.
Profile: Google Scholar
Publications
1. Rakkiyappan, R., Premalatha, S., Chandrasekar, A., & Cao, J. (2016). Stability and synchronization analysis of inertial memristive neural networks with time delays.
2. Rajan, R., Gandhi, V., Soundharajan, P., & Joo, Y. H. (2020). Almost periodic dynamics of memristive inertial neural networks with mixed delays.
3. Premalatha, S., Santhosh Kumar, S., & Jayanthi, N. (2022). Results on periodicity of memristive inertial neural networks with mixed delays. International Conference on Data Analytics and Computing.
4. Premalatha, S. S. K., Shanmugapriya, M. M., & Jayanthi, N. (2025). Dissipativity analysis of memristive inertial neural networks with time-varying and distributed delay via reduced order strategy.
5. Premalatha, S. S. K., Indumathi, P., & Aarthi, D. (2025). LMI approach to dissipative of memristive inertial neural networks with time-varying and distributed delay. Advances in Nonlinear Variational Inequalities.