Hi! I'm

Abhinav Raghunathan

I'm a data scientist and engineer focused on responsible AI.
I've spent over a year studying the responsible AI startup ecosystem and I currently run EAIDB.



BS Computational Engineering + Mathematics @ UT Austin '21
MSE Data Science @ University of Pennsylvania '22

Experience

I've spent a lot of time solving tough but high-value problems with data science and ML in financial / technology sectors. I have a unique understanding of fairness / bias in ML applications and how to detect and mitigate issues.

Projects

Name Description Link
Ethical AI Database (EAIDB) The Ethical AI Database (EAIDB) is the only publicly available, vetted database of AI startups providing ethical services.
Sports vs. Happiness A study investigating the relationship between the nature of a country's sports teams (quantity, gender representation, and performance) and that country's overall happiness. Countries with larger numbers of better performing men's and women's teams tend to be happier.
WildSight An image recognition algorithm platform meant to process conservationists' photos and identify characteristics such as type of animal, number of animals, etc. and place bounding boxes around the subjects.
Designing an All-Terrain Rover A research project conducted with IEEE and Winlab at Rutgers University. The goal was to devise a rover with a unique locomotion method that utilized a combination of linear actuators and wheels to traverse tough terrain.

Recognition

I write broadly about data science and machine learning but tend to focus on topics involving bias / fairness. My work on the "Ethical AI Startup Ecosystem" on behalf of EAIDB has received acclaim across social media and various other blogs and channels.

TEDx Talk

I gave a talk at UT Austin's TEDx conference in 2021 on the dangers of algorithmic bias and some possible ways to mitigate them. See the slide deck here.


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