Meghana Kshirsagar

Meghana Kshirsagar

Deputy Director
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About

Dr. Meghana Kshirsagar is an Associate Professor in the Computer Science and Information Systems department at the University of Limerick. As Deputy Director of the Biocomputing and Developmental Systems Research Group, she has managed and supervised postdoctoral researchers, PhD candidates, Master’s students, and interns on multiple funded projects within the group in multidisciplinary areas spanning medical diagnostic systems, fintech, and circuit design.

She has secured €250,000 in funding as Principal Investigator from the Science Foundation Ireland National Challenge Fund project “ALTER: Unleashing the Power of AI and Digital Twins in Emergency Care” and is leading a diverse six-member team. Dr. Kshirsagar collaborates with emergency department consultants and specialists from her project ALTER to streamline patient flow in emergency care and optimize resource utilization using digital twins by integrating key healthcare services and predictive analytics with Machine Learning.

A member of Lero, the Science Foundation Ireland Research Centre for Software, Dr. Kshirsagar also serves on Lero’s Equality, Diversity, and Inclusion Committee. With over 18 years of experience as an Associate Professor at the Government Engineering College, Aurangabad, India, Meghana played a pivotal role in accreditation, curriculum development, and securing funds for empowerment of students and faculties within the department for pursuing training programs for upskilling and facilitating students to present research at international venues and participate in Hackathons.

Research Interests

Digital Twins in Healthcare Medical Diagnostic Systems Machine Learning Predictive Analytics Grammatical Evolution Fintech Circuit Design

Research Statistics

14Projects
52Scopus Indexed Publications
848Citations
100Students Supervised

Recent Publications

2026

From Natural Language to Interpretable Code: Automated Code Generation for Healthcare with Large Language Models-A Comparative Analysis

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2026

Synthetic Data for PET and HDPE Classification: A Comparison of Diffusion and Autoregressive Models

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2025

Machine Learning for Prostate Cancer Risk Stratification: A Web-Based Tool with Explainability and Fairness

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2025

Resource-Efficient Techniques for Hyperparameter Optimization in Machine Learning

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