Predictive modeling of cognitive function with machine learning
Benchmarks machine-learning models for predicting early-midlife cognition from survey and biomarker data.
Machine learning
Muntasir Masum, PhD
Assistant Professor of Epidemiology & Biostatistics
I study alcohol epidemiology, social determinants of health, and machine learning for population health — building open, reproducible workflows that turn large public-health surveys into evidence for policy.
9
Peer-reviewed
3
Grants as PI
8
Students mentored
Research
Population health, decoded
Alcohol, social determinants, and life-course health using large national surveys — NHIS, BRFSS, Add Health, HRS.
Explore research →Studio
Visualizations & tools
Data visualizations from my research, open R workflows and apps, and the occasional experiment.
Enter the studio →Teaching
Methods, taught clearly
Graduate epidemiology and statistical inference at UAlbany — EPI 501, EPI 553 — plus Alcohol, Society & Health.
Courses →Selected publications
View all →Does staying put protect? Neighborhood cohesion, residence & drinking
The protective tie between neighborhood cohesion and lower-risk drinking strengthens the longer adults stay put.
SDOHAlcohol epi
Alcohol and binge drinking frequency and hypertension
Both frequent and binge drinking independently tracked with higher hypertension prevalence across a national U.S. sample.
Alcohol epiCardiometabolic
News
All →Jun 2026Awarded the AI Plus Institute Agentic AI Seed Grant (PI) to harmonize BRFSS data.
Mar 2026SUNY AI Platform Award ($100K) to model early-midlife cardiovascular risk with ML.
2026New paper in Alcohol & Alcoholism on neighborhood cohesion and drinking.
2026Invited talk at the UAlbany AI Plus Symposium.
Currently
- ›Building an open, reproducible agentic-AI pipeline to harmonize the BRFSS — my AI Plus seed-grant project.
- ›Writing Alcohol Intelligence, my newsletter on alcohol, health, and population data.
Prospective students & collaborators
I welcome inquiries from students and collaborators interested in alcohol epidemiology, social determinants of health, and applied machine learning.