About Me

I’m a Computer Science PhD student at Carnegie Mellon University, advised by Nihar Shah. My current research focuses on AI Algorithm design for socio-technical systems.

In the past, I was a math undergrad, also at CMU! I really like research breadth and exploration. In the past, I have done some research in Information Theory, Neuroscience and Programming Languages.

Publications

What’s in a Name? Linear Temporal Logic Literally Represents Time Lines
Runming Li*, Keerthana Gurushankar*, Marijn J.H. Heule, Kristin Y. Rozier Jul 2023, IEEE Working Conference on Software Visualization (VISSOFT 2023) (*equal contribution) Preprint Artifact

Capturing and Interpreting Unique Information
Praveen Venkatesh, Keerthana Gurushankar, Gabriel Schamberg Jan 2023, IEEE International Symposium on Information Theory 2023. Preprint

Extracting Unique Information through Markov Relations
Keerthana Gurushankar, Praveen Venkatesh, Pulkit Grover
Jul 2022, Allerton Conference on Communication, Control and Computing. Preprint

Sharp bounds on p-norms for sums of independent uniform random variables, 0<p<1
Giorgos Chasapis, Keerthana Gurushankar, Tomasz Tkocz
May 2021, Journal d’Analyse Mathématique. Preprint

A minimal intervention definition of reverse engineering a neural circuit Keerthana Gurushankar, Pulkit Grover Preprint