Resume

Dr. Mona Pathak, Ph.D

Assistant Professor

Email- mpathak@sgpgi.ac.in ; mona.pathak19@gmail.com

Professional Profile

Dr. Mona Pathak is a Biostatistician and Health Data Scientist with 10+ years of experience and 85+ publications in biostatistical research, clinical research, health outcomes research, and interdisciplinary collaboration. She has academic and research experience in India and the United States, working with clinicians, epidemiologists, pharmacists, public-health researchers, and basic scientists.

She received her Ph.D. in Biostatistics from AIIMS, New Delhi, with doctoral research in competing-risk survival models and evidence synthesis in breast cancer. Her research combines statistical methodology, clinical research, evidence synthesis, and artificial intelligence/machine learning to address complex health and population-health problems.

Research Interests

Statistical Methodology: survival and competing-risk analysis; multi-state, longitudinal models and trajectory modelling; structural equation modelling; multilevel and hierarchical modelling; meta-analysis, network meta-analysis, Bayesian network meta-analysis; individual participant data meta-analysis; predictive modelling and machine learning; fairness of machine learning models

AI & Health Data Science: AI/ML in healthcare; Clinical prediction modelling; Natural language processing of clinical data; Electronic health record and real-world data; Responsible and interpretable AI

Applied & Collaborative Research: Health disparities and social determinants of health; Neurology and stroke; Alzheimer's disease and related dementias; Cardiometabolic health and multimorbidity; Mental health; Cancer; Rheumatology; Maternal and child health

Current Research Directions: Current research focuses on AI-enabled clinical data research, health disparities, evidence synthesis, clinical prediction, and advanced statistical modelling.

Data & Technical Expertise

Experience with electronic health records, real-world data, claims databases, cancer registries, and large-scale population surveys, including TriNetX, MyChart, Medicare/SEER-Medicare, HRS, NHATS, and the Census Household Pulse Survey.

Statistical & programming software: R, Stata, SAS, Python, and SPSS.

Teaching

With experience in designing the curriculum, Dr. Pathak’s teaching interests include Biostatistics and statistical modelling; Survival and longitudinal data analysis; Clinical trial and epidemiological study design; Research methodology; Systematic reviews and meta-analysis; Predictive modelling; Artificial intelligence and machine learning in healthcare