Predictive cancer epigenomics
Deep learning models for estimating epigenetic treatment-induced transposable element expression changes from pre-treatment genomic and epigenomic data.
Research Projects
Current and selected research directions across cancer epigenomics, single-cell systems biology, public health analytics, and environmental data science.
Computational public-health modeling
COVID-19 forecasting, geospatial visualization, cross-country survey analysis, and social-media mining for pandemic response.
Remote sensing and environmental machine learning
Machine learning for flood detection, Sentinel-1 to NDWI modeling, and GLDAS groundwater storage downscaling.
Single-cell communication and cellular dynamics
Cell dynamics models that integrate intercellular communication, pathway-level features, and single-cell RNA-seq analysis pipelines.