Adithya "Adi" Yerramsetty
Howdy! My name's Adi. Below you'll find some things I've made public, which
you hopefully find interesting/useful.
I'm currently
- a junior at ASU going for a double major in CS + Math
- president at the ASU Machine Learning Club, where I teach ML, Deep Learning and more to interested members
- an undergrad researcher at ASU DREAM Lab working on NeRF/View Synthesis
- working on building a NeRF of all of Seattle from some driving data I collected
- implementing and playing with various algos/problems in ML/CV including Diffusion Models, NeRFs, Visual-SLAM, etc.
In the past I
- interned as a Deep Learning Intern at Silicon Valley Bank(May 2022 - January 2023), where I worked on Graph Neural Nets for investment predictions
- have won prizes at a variety of hackathons, including but not limited to DataFest @ ASU, ASU AI In Education and SVB @ ASU 2021
Here is
I'm currently writing up
- a whirlwind tour of ML, going over some of the topics we would normally cover at the ML club
- an explainer for the proof for gradient descent; a lot of it is detailed nicely by this article, but I want to go through it myself
- a derivation for the SVD Solution to Homogenous LLS. I have it on my old site, but haven't moved it here yet. It's pretty useful in V-SLAM
- a post on the basics of vector search(LSH, HNSW, etc). They're a super cool application of Neural Nets, and fascinated me during my freshman year
- an overview and walkthrough of applying standard generative models(GAN, EBMs, Diffusion Models) on MNIST. I'm working toward's re-producing Waymo's MotionDiffuser, so this is a good preliminary.