Dr. Divya is a clinician-turned-researcher with over a decade of experience in Obstetrics and Gynecology, now specializing in translational and computational research to advance precision medicine. She holds an MBBS and DNB in Obstetrics and Gynecology from India, with extensive experience as a Fertility Consultant, having performed over 800 IVF-related procedures. Driven by a commitment to improving reproductive health outcomes, she is currently pursuing an MSc in Precision Health and Medicine at the National University of Singapore, where she is gaining expertise in multi-omics data integration, microbiome analysis, machine learning, and molecular dynamics simulations.
Her research interests lie at the intersection of clinical medicine and computational biology, with a focus on personalized reproductive health. Her ongoing capstone projects include molecular dynamics simulations to investigate the structural impact of coding variants in Type 2 Diabetes Mellitus (KCNJ11 V337I mutation) and an AI-driven exploration of the endometrial microbiome to identify dysbiosis thresholds predictive of IVF implantation outcomes. These projects highlight her ability to translate clinical questions into data-driven research and apply advanced analytical tools to real-world biomedical challenges.
Technically proficient in Python, R, TensorFlow, PyTorch, QIIME2, AMBER, and molecular visualization tools such as PYMOL and VMD, Dr. Divya leverages high-performance computing environments to conduct her analyses. She is dedicated to principles of FAIR data management and clinical data compliance, ensuring rigorous, reproducible research practices.
Her career trajectory reflects a commitment to bridging clinical experience with computational innovation, aiming to improve diagnostic and therapeutic strategies in reproductive medicine. Through this unique blend of clinical insight and computational expertise, Dr. Divya seeks to contribute to multidisciplinary collaborations in precision health, making evidence-based, individualized care a reality for patients.