Er. Edith Esther E is an accomplished academic and emerging researcher specializing in Machine Learning, Artificial Intelligence, Data Science, Healthcare Analytics, and Medical Data Mining. She is currently pursuing her Ph.D. in Computer Science/Information Engineering at Anna University, having completed her doctoral coursework with an impressive 8.00 CGPA. She has accumulated 16 years and 1 month of teaching experience, contributing to engineering education through teaching, student mentoring, project guidance, academic governance, and institutional development.

She has served as an Assistant Professor at GRT Institute of Engineering and Technology, Tiruttani, since August 2021. Previously, she held Assistant Professor positions at Jaya Engineering College and Sri Venkateswara College of Engineering & Technology, following her earlier role as a Lecturer at Sri Ram Engineering College.

Research Interests & Expertise

Her research portfolio demonstrates a strong interdisciplinary focus at the intersection of Artificial Intelligence and healthcare. Her major areas of research include:

• Machine Learning and Artificial Intelligence
• Healthcare Analytics and Predictive Healthcare
• Gestational Diabetes Mellitus and Cardiovascular Risk Prediction
• Medical Data Mining and Personalized Healthcare
• Deep Learning and TinyML
• Non-invasive Blood Glucose Monitoring
• Data Science, Exploratory Data Analysis and Visualization

Her doctoral research direction focuses on data-driven prediction of comorbid risks associated with Gestational Diabetes Mellitus using data mining and machine learning approaches.

Research Contributions & Publications

Er. Edith Esther E has contributed research addressing contemporary challenges in healthcare and intelligent computing. Her notable recent work, “Early Prediction of Cardiovascular Risks Induced by Gestational Diabetes Mellitus: A Machine Learning Perspective Towards Personalized Interventions,” was published through IEEE Xplore in 2026 and is indexed in Scopus.

Her research output also includes work on TinyML in healthcare, hybrid machine-learning approaches for brain pathology classification, deep reinforcement learning for diagnostic and medical data, cloud-security analytics, machine-learning-based loan eligibility prediction, and virtual interfaces for ATM accessibility.

She has presented her research at national and international conferences, including conferences focusing on AI-driven smart systems, communication and signal processing, intelligent computing, and emerging technologies in computer applications.

Healthcare AI & Emerging Technology Research

A distinctive aspect of her research profile is the application of computational intelligence to healthcare challenges. Her work encompasses predictive healthcare, cardiovascular-risk assessment associated with gestational diabetes, medical data analytics, deep learning, and non-invasive glucose monitoring using photoplethysmography signals.

Her research interest in TinyML further reflects her engagement with emerging low-resource artificial intelligence technologies capable of supporting healthcare applications at the edge.

Research & Development Projects

Her professional portfolio includes interdisciplinary R&D activities involving technology and societal applications. Documented projects include:

• Groundwater-quality mapping, health impact assessment, and geospatial analysis supported by the Department of Science & Technology, Government of India.
• Development of a web-based system for monitoring solar centres.
• Development of a coastal-district disaster-management website through a World Bank-supported initiative via the Tamil Nadu Disaster Management Agency.

She has also served as Co-PI for a research proposal submitted to the Anusandhan National Research Foundation (ANRF) addressing inclusive education, assistive technology, rural healthcare, and skill-based livelihood training in underserved communities.

Book Publication

Er. Edith Esther E is a co-author of the book “Foundations of Data Science,” published by Charulatha Publications in August 2023. The book carries ISBN 978-93-5577-606-8 and reflects her academic engagement with data science and computational technologies.

Teaching & Academic Contributions

Alongside research, she has made significant contributions to teaching and academic administration. She has guided undergraduate projects, supported student technical activities, participated in Board of Studies and Academic Council activities, and contributed to institutional ISO, NAAC, and NBA-related processes.

She has also served as a question-paper setter for Python Programming and has undertaken institutional responsibilities involving the Institutional Innovation Council (IIC), Students Grievance Redressal Committee, NAAC Criterion 3, and NBA Criterion 6.

Her teaching profile is further supported by documented recognition for effective lesson planning, technical instruction, and classroom management.

Professional Development

She has consistently strengthened her expertise through national and international Faculty Development Programmes, workshops, and certifications covering Deep Learning, NLP, Computer Vision, Cyber Security, Data Visualization, AI applications in banking and healthcare, Generative AI, Prompt Engineering, Machine Learning, 5G communication, and Agentic AI.

Her professional learning includes NPTEL Introduction to Machine Learning, AI Mastery for Educators through Vishlesan i-HUB, IIT Patna, and Red Hat Academy Educator training. This sustained engagement with emerging technologies demonstrates her commitment to continuous academic and professional development.

Interdisciplinary & Social-Impact Orientation

A notable strength of her profile is the integration of computer science with healthcare and community-oriented applications. Her research and project portfolio connects AI, machine learning, healthcare analytics, geospatial technology, disaster management, assistive technology, and rural healthcare.

This interdisciplinary orientation enables her to address technological problems not only from a computational perspective but also in relation to healthcare delivery, social inclusion, and community welfare.

Eligibility for Women Researcher Award 

Er. Edith Esther E demonstrates several qualities relevant to consideration for the Women Researcher Award in Scientific Laurels. Her profile combines more than 16 years of teaching experience, ongoing doctoral research, interdisciplinary research in AI and healthcare, Scopus-indexed research output, conference presentations, a published book, R&D project involvement, and continuous professional development.

Her research on machine-learning-based prediction of cardiovascular risks associated with gestational diabetes, together with her work in TinyML, deep learning, medical data analytics, and non-invasive glucose monitoring, reflects a research trajectory focused on applying emerging computational technologies to important healthcare challenges. Her academic mentoring, institutional contributions, and social-impact-oriented research projects further strengthen her overall academic and research profile.

Based on the documented academic, research, publication, project, teaching, and professional-development achievements provided, Er. Edith Esther E is eligible for consideration for the Women Researcher Award in Scientific Laurels.