Jomol Puthuparampil Mathew

Jomol Puthuparampil Mathew serves as an Adjunct Assistant Professor in the Population and Quantitative Health Sciences Department at UMass Chan Medical School's T.H. Chan School of Medicine. His academic appointments also include affiliation with the Health Informatics And Implementation Science Division. Previously associated with UW-Madison School of Medicine and Public Health, his work bridges clinical research and computational health sciences.

• BS Science - Kerala Agricultural University, Thrissur, KL, India
• MS Science - Kerala Agricultural University, Thrissur, KL, India
• PhD Plant and Soil Sciences - University of Massachusetts Amherst, Amherst, MA, United States

Dr. Mathew's research centers on health informatics and population health, with emphasis on electronic health record analytics, health disparities measurement, and machine learning applications in clinical settings. His work frequently examines social determinants of health outcomes, particularly in cancer surgery and pandemic response. Recent publications demonstrate growing focus on generative AI analysis of medical records and privacy-preserving data commons for substance misuse research.

Publication trends reveal significant contributions to COVID-19 research (15+ papers 2020-2025), with work appearing in Lancet Digital Health, JAMA Internal Medicine, and Annals of Surgical Oncology. His collaborative network spans 19+ co-authors across institutions, with frequent work on national consortia like the National COVID Cohort Collaborative.

• Developed privacy-preserving patient record linkage systems for substance misuse research
• Created real-time point-of-care patient recruitment platforms (JITA)
• Identified neighborhood disadvantage impacts on pancreatic cancer outcomes
• Validated GPT-4 for multilingual medical note analysis

Dr. Mathew actively contributes to health equity research through statewide EHR networks, examining Medicaid enrollment impacts on surgical care and developing novel metrics for health disparity measurement. His work integrates computational biology with clinical implementation science, maintaining strong connections to translational cancer research through earlier genomic EHR integration studies.