Associate Professor, Francis Xavier Engineering College, India
📘 Dr. A. Jainul Fathima, B.Tech., M.E., Ph.D., is an innovative professor with a strong passion for fostering academic development and success for every student. With 12 years of combined experience in teaching, research, and industry, she excels in implementing technology-based curriculum delivery and assessment tools.
Profile
Scopus
Education🎓
Dr. Fathima holds a Ph.D. in Computational Drug Discovery from Kalasalingam Academy of Research and Education, where her interdisciplinary research focused on developing anti-viral drugs for dengue targets using AI techniques. She earned her M.E. in Computer Science and Engineering from Anna University with an 83% aggregate and a B.Tech. in Information Technology from Anna University with a 75% aggregate.
Experience 🛠️
👩🏫 With 12 years of total experience, Dr. Fathima has 6 years of teaching experience, currently serving as an Assistant Professor at Francis Xavier Engineering College. She has previously worked at K.L.N. College of Information Technology, Sethu Institute of Technology, and Kalasalingam University. Her research experience includes 3 years as a UGC Research Fellow and 2 years of teaching and instructing in Qatar. She also has 1 year of industrial experience as a Research Assistant in Computer-Aided Drug Design.
Research Interests 🔍
🔬 Dr. Fathima’s research interests are in the areas of computational drug discovery, machine learning, artificial intelligence, and bioinformatics. Her work focuses on applying advanced computational techniques to predict protein interactions and develop therapeutic solutions for diseases like dengue and Alzheimer’s.
Awards 🏆
🏆 Dr. Fathima has received several accolades, including the “Research Associate Award” from the Anti-viral Research Society in 2022, “Best Paper Award” at INCODS ’17 and NCAC ’09, and the “Outstanding Student Award” from Mepco Schlenk Engineering College.
Publications 📚
A comprehensive review on heart disease prognostication using different artificial intelligence algorithms, Computer Methods in Biomechanics and Biomedical Engineering, February 2024. Cited by 1.5
Alzheimer’s Patients Detection using Support Vector Machine (SVM) with Quantitative Analysis, Neuroscience Informatics, 2021. Cited by 0.5
IoT-Based Intelligent System for Garbage Level Monitoring in Smart Cities, International Conference on IoT, Communication and Automation Technology, 2023. Scopus Indexed
Intelligent Deep Learning Framework for Breast Cancer Prediction using Feature Ensemble Learning, IEEE Global Conference for Advancement in Technology, 2023. Scopus Indexed
Compressing Biosignal for diagnosing chronic diseases, Journal of Physics: Conference Series, 2021. Scopus Indexed