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publications

Edge Evolution Analysis using Social Network

05, 2016

This paper presents an efficient and doubly robust estimator of the total population size from incomplete lists. It uses tools like nonparametric statistics and efficiency theory. It also estimates the total number of war casualties in the Peru Internal Armed Conflict 1980-2000.

Manjari Das, Ritwika Law, Diganta Mukherjee (2016). Edge Evolution Analysis using Social Network.

Linking galaxies to their progenitors based on galaxy morphology

04, 2018

We analyze the statistics of galaxy data from the Illustris Project at different time points, and we use these results to build models that predict the past mass rank of a galaxy given its current mass rank, morphology, and physical properties such as star-formation rate.

Manjari Das, Ann B. Lee, Peter Freeman, Gregory F. Snyder

Doubly robust capture-recapture methods for estimating population size.

Published in arXiv.org, 07, 2021

This paper presents an efficient and doubly robust estimator of the total population size from incomplete lists. It uses tools like nonparametric statistics and efficiency theory. It also estimates the total number of war casualties in the Peru Internal Armed Conflict 1980-2000.

Das M, Kennedy EH, Jewell NP (2021). Doubly Robust Capture-recapture Methods for Estimating Population Size." arXiv preprint arXiv:2104.14091. https://arxiv.org/pdf/2104.14091

Total population size estimation under partial identification using sensitivity analysis.

This paper presents an efficient and doubly robust estimator of the total population size from incomplete lists. It uses tools like nonparametric statistics and efficiency theory. It also estimates the total number of war casualties in the Peru Internal Armed Conflict 1980-2000.

Das M and Kennedy EH. Total population size estimation under partial identification using sensitivity analysis.

talks

teaching

Quantitative Social Science Scholars program

Workshop, Carnegie Mellon University, Dietrich College of Humanities and Social Sciences, 2021

This was part of my Dietrich Teaching Fellowship. I got the opportunity to teach and hold workshops for two weeks on basic statistical topics. The first topic was variable transformation for which I designed the lecture notes and created some shiny applications (available in the shiny_apps repository on my Github account) for interactive learning. The second topic was Bootstrap and some practical applications.

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Introduction to Statistical Inference (36-226 U)

Undergraduate summer six-week course, Carnegie Mellon University, Department of Statistics and Data Science, 2021

This is a six week long course offered in summers. The topics include basic ideas of statistics, random variables, estimation, hypothesis tests and confidence intervals. I was involved in partially designing the lecture notes and assignments. I held lectures Monday to Friday every week and also conducted flexible doubt clearing sessions. Apart from this, I also worked with a team of six teaching assistants and handled the logistics. I am grateful to Professor Peter Freeman and my fellow student Matteo Bonvini for sharing their resources and for the very helpful guidance.

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