Research Objective

Conducting healthcare informatics research deployable in the real world to ensure maximal benefit for a broader population in society especially for reducing social and healthcare disparities across minority groups. Deepening my grasp of theoretical machine learning while exploring practical considerations and nuances of turning research into public policy.

Research Interests

Probabilistic Graphical Models, Noisy Labelling, Crowdsourcing, Weakly Supervised Learning, Healthcare Informatics- Nursing quality metrics, Outcome prediction in clinical settings, Tensor Factorization, Disease Progression Prediction, Machine Learning for real-world data, Data Mining for social good, Bias and fairness in machine learning.

Work experience

Programming and Technical Skills


Selected Graduate Courses

Awards and Honors

Reviewing Experiences

AMIA Annual Symposium and AMIA Informatics Summit 2019-2021

Leadership and Community Engagement