Soham Ghosh

Currently a second year Ph.D. student in Statistics at the University of Wisconsin, Madison.

About Me

I work as a Graduate Research Assistant under Prof. Guanhua Chen, working primarily on developing a novel feature selection procedure with controlled FDR using knock-off sampling.

My interests include Bayesian Statistics and Stochastic Calculus. Prior to this, I have worked on problems involving outlier detection in multinomial logistic models. If not Statistics, I am usually interested in Cryptology problems, particularly hash-key recovery and forgery attacks.

Recently, I am into Causal Inference which in my opinion can help us think beyond data, that is, to think more clearly about the data generating process. I like the idea of exploring the circumstances when Correlation actually implies Causation.

I enjoy writing blogs highlighting various unsung aspects of Probability Theory, some of them are featured below!

Understanding Statistical Regularity through Random Walks

The Law of Statistical Regularity formulated in the mathematical theory of probability lays down that a moderately large number of items chosen at random from a very large group are almost sure to have the characteristics of the large...

Nonconglomerability & The Law of Total Probability

This explores the unsung sector of probability : "Nonconglomerability" and its effects on conditional probability. This also emphasizes the idea of how important is the idea countable additivity or extending finite addivity to infinite sets.