Sambit Panda

Biomedical Engineering PhD Candidate

I'm a PhD candidate at Johns Hopkins, where I am advised by Joshua T. Vogelstein in the NeuroData lab. Most days, I develop and apply high-dimensional and nonlinear machine learning algorithms to answer interesting biomedical questions. Here's a little bit more about me.

Publications

Here are some of my favorite research articles that I have written. If you want to read more, here is the full publication list.

The Chi-Square Test of Distance Correlation
by Cencheng Shen, Sambit Panda, and Joshua T. Vogelstein
in Journal of Computational and Graphical Statistics on January, 2022
Details
Selective and Mechanically Robust Sensors for Electrochemical Measurements of Real-Time Hydrogen Peroxide Dynamics in Vivo
by Leslie R. Wilson, Sambit Panda, Andreas C. Schmidt, and Leslie A. Sombers
in Analytical Chemistry on January, 2018
Details

Software

I love solving difficult problems, and often times develop software to help. If you want to see more, here is the full software list.

scikit-tree

Scikit-learn compatible decision trees beyond those offered in scikit-learn.

hyppo

hyppo (HYPothesis Testing in PythOn, pronounced “Hippo”) is an open-source software package for multivariate hypothesis testing.

scipy.stats.multiscale_graphcorr

Multiscale Graph Correlation (MGC) is a powerful, universally consistent independence test that performs well on high-dimensional and non-Euclidean data.