Chitkara University | India
Dr. Leema Nelson is an accomplished researcher whose scholarly contributions span machine learning, clinical decision support systems, composite materials, signal processing, and intelligent diagnostic frameworks. With a total of 1206 citations, an h-index of 17, and 29 i10-index publications, her research demonstrates both depth and sustained impact across interdisciplinary domains. She has produced numerous high-quality peer-reviewed articles, many in leading Elsevier journals such as Applied Soft Computing and Materials & Design, focusing on neural network optimization, characterization of metal-matrix composites, wear modelling, and advanced computational methods. Her work in clinical data classification, including diabetes and PCOS diagnosis, highlights the integration of artificial intelligence into healthcare decision-making. In recent years, she expanded her research into video smoke detection, cyber-security–based email filtering, audio source separation, and welding parameter optimization using intelligent algorithms. Her studies in deepfake detection, text recognition, and clinical support systems reflect her continuing advancements in data-driven AI models. She has also contributed extensively to IEEE conferences, presenting innovations in masked face detection, ultrasound image analysis, mobile app frameworks, and disease prediction models. Overall, her scientific output reflects strong productivity, interdisciplinary expertise, and meaningful contributions to both computational intelligence and applied engineering research.
Profiles : Scopus | Orcid | Google Scholar
Featured Publications
Jibinsingh, B. R., & Nelson, L. (2025). FL-WOSP: Federated learning with Walrus Optimization for sepsis prediction using MIMIC-III physiological and clinical data. Pattern Recognition. Advance online publication.
Batra, H., & Nelson, L. (2024). ESD: E-mail spam detection using cybersecurity-driven header analysis and machine learning-based content analysis. International Journal of Performability Engineering, 20(4).
Nelson, L. (2024). Data-driven clinical decision support system using neural network topology optimization for PCOS diagnosis. Journal of Soft Computing and Data Mining.
Batra, H., & Nelson, L. (2024). A three-stage deepfake detection framework using deep learning models with multimedia data. International Journal of Intelligent Systems and Applications.
Shanmuga Priya, M., Pavithra, A., & Leema, N. (2024). Character/word modelling: A two-step framework for text recognition in natural scene images. Computer Science.
Batra, H., & Nelson, L. (2023). DCADS: Data-driven computer aided diagnostic system using machine learning techniques for polycystic ovary syndrome. International Journal of Performability Engineering, 19(3).
Kumar, V. A., Rao, C. V. R., & Leema, N. (2023). Audio source separation by estimating the mixing matrix in underdetermined condition using successive projection and volume minimization. International Journal of Information Technology, 15(4), 1831–1844.
Ramesh, A., Sivapragash, M., Ajith Kumar, K. K., & Leema, N. (2023). Investigating the quality of TIG-welded aluminium alloy 5086 using the online acoustic emission and optimization of welding parameters using global best-based modified artificial bee colony algorithm. Transactions of the Indian Institute of Metals, 1–14.
Pranshu Kumar Soni, & Leema, N. (2023). PCP: Profit-driven churn prediction using machine learning techniques in banking sector. International Journal of Performability Engineering, 19(5), 303–311.
Vettum Perumal, S., Suyamburajan, V., Chidambaranathan, V. S., & Nelson, L. (2023). Characterization of microstructure and mechanical behaviour in activated tungsten inert gas welded dissimilar AA joint of AA 5083 and AA 6061 alloys. Journal of the Institution of Engineers (India): Series D, 1–9.