Aadi Malaviya
Opening the box
The work I keep coming back to is making opaque things inspectable. In UCLA's NLP lab that was literal: finding which layers and attention heads carry a behaviour, then steering them to prove the link was causal and not coincidental. At Ryniant it meant a synthesis route a chemist could trace to a citation instead of taking on faith. At Chelle it meant a rubric, so a prompt decision became something you could run an experiment on rather than argue about. At Genter it meant a required distribution a client could actually be shown, deadline attached, instead of a number living in someone's spreadsheet.
A system you cannot inspect is one you can only trust or abandon. Most of what I have built exists to give people a third option.
Software engineer working on ML systems. UCLA, B.S. Computer Science and Mathematics. Most recently a founding engineer at Ryniant; before that, interpretability research in UCLA’s NLP lab.
University of California, Los Angeles
B.S. Computer Science and Mathematics
September 2023 – June 2026Data Structures and Algorithms · Computer Systems · Database Systems · Machine Learning · Deep Learning · Artificial Intelligence · Linear Algebra · Optimization · Probability and Statistics · Applied Numerical Methods
- Built with
- Astro · plain CSS
three.js · GSAP · Lenis - Type
- Archivo
Source Serif 4
JetBrains Mono - Desert
- Live WebGL
Procedural dune field
GPU sand