Yumkhaibam Budhachandra

Final year M.S. Computer Science student, University of Texas at Arlington.
Graduate Research Assistant, Center for Health Informatics (CIHI), UTA.
Advised by Dr. Jacob M. Luber and Dr. Jennifer Woo.

LinkedIn · Google Scholar · GitHub · Academic CV · CV

Research Interests

My research broadly focuses on the intersection of machine learning and biomedical informatics. Current areas of interest include:

Pre-term birth modelling and prediction using machine learning
Multi-modal data modeling
Medical Imaging
AI for Mental Health
Interpretable AI in Healthcare

Publications

Multi-Modal Modeling of Preterm Birth Risk in an Underrepresented Black/African-Ancestry Cohort

Budhachandra Yumkhaibam — M.S. Thesis, University of Texas at Arlington

In preparation

[PDF] [Slides]

Stable Pipeline for Multi Modal analysis on preterm birth for small datasets

Budhachandra Yumkhaibam et al.

In preparation

Open Source Contributions

Oppia Contributed to Oppia, a large-scale open-source interactive learning platform.

NeuroML / pyNeuroML 3 merged PRs: added matplotlib animation support for generated plots, introduced default figure-saving behavior, and added a new CLI flag (-swc).

Mozilla / bugbug 2 merged PRs: refactored count_bugs to use the libmozdata library, and simplified CI configuration using mergeDeep.