I'm currently a graduate student at Carnegie Mellon finishing up a research masters in Robotics. I'm working on problems in the space of Reinforcement Learning and Interpretability.
In the past I've spent:
→ Over half a year working in collaboration with Uber ATG on training self driving cars using reinforcement learning.
→ A summer at Scale AI building computer vision models to assist humans doing data labeling.
→ Half a year at Microsoft Research hacking on systems and algorithm applications for large networks.
→ A summer (and then some), at JPL as a Caltech SURF Scholar designing neural networks to help us better understand the impact of climate change on coral reefs.
Even before that, I was part of a small team that built a data science pipeline to process data for the world's largest sub-GHz frequency radio telescope.

Through my experiences, I've come to realize that I enjoy building systems and tools that solve challenging problems and create meaningful value for society.
I occasionally write.
I love chatting about science, math, computing, economics, politics, art, design philosophy. Feel free to reach out :)


Twitter: @bhaprayan