University of Pittsburgh
LINCC Frameworks Research Scientist
Mi Dai’s research interest focuses on using Type Ia supernovae to constrain cosmology and time-domain astronomy. Her work involves developing methods and pipelines for studying the systematic uncertainties in SN Ia cosmology, finding SN Ia candidates, and photometric classification. She is a member of the LSST Dark Energy Science Collaboration and the PLAsTiCC Team. She is passionate about applying Machine Learning algorithms to large astronomical data sets and developing infrastructures for automating the scientific workflow.