Department of Mathematics and Statistics
The main focus of my research is on causal inference and causal discovery. I develop statistical methodologies for evaluating the causal effect of actions or treatments on outcome variables of interest, designing policies for optimizing outcomes, and identifying the causal relationships among the variables of a system. I investigate such causal queries in the face of real-world data complexities such as presence of unobserved confounders, measurement error, and missing and censored values. The tools I use in my research include methods from the modern semi- and non-parametric statistics, state-of-the-art machine learning, and information theory.
Before joining Boston University, I was a Postdoctoral Fellow at Johns Hopkins University under the joint supervision of Prof. Ilya Shpitser and Prof. Eric Tchetgen Tchetgen. I received my PhD in the area of Data Science and Communications from the Electrical and Computer Engineering Department at the University of Illinois at Urbana-Champaign (UIUC) in 2020. My PhD program was advised by Prof. Negar Kiyavash. During my PhD, I was fortunate to also work extensively with Prof. Kun Zhang.
I am the co-organizer of the department's Statistics and Probability Seminars with Deb Mukherjee.
- Causal Inference and Discovery
- Statistical Learning Theory and Machine Learning
- Semiparametric Statistics
- Probabilistic Graphical Models