Monal Narasimhamurthy
Machine Learning Engineer at Chorus
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMonal Narasimhamurthy is a Machine Learning Engineer with a PhD in Computer Science from the University of Colorado Boulder and 12 years of industry and research experience spanning ML, formal methods, and autonomous systems. Her academic work focused on data-driven modeling and state estimation for complex, non-smooth dynamical systems, blending optimization, deep learning, and verification techniques. She transitioned into industry roles including internships at AWS and Microsoft where she added practical verification features (e.g., function contracts in a Rust model checker) and built domain-specific tools for autonomous vehicle testing. Now based in Mountain View and working at Chorus, she pairs rigorous research instincts with hands-on engineering to take models from theory to production. An under-the-radar strength is her experience contributing to the FStar verification ecosystem—resolving merge conflicts and touching parser and build components—showing comfort with proof-oriented codebases and compiler-adjacent work.
11 years of coding experience
6 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and ScienceDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of Colorado Boulder
Github Skills (11)
integrate10
system-integration10
integrations10
data-integration10
fstar10
dependent-types9
verification8
ocaml8
python8
theorem-proving7
data-analysis5
Programming languages (8)
Github contributions (5)
FStarLang/FStar
Jul 2017 - Jan 2018
A Proof-oriented Programming Language
Role in this project:
Backend Developer
Backend DeveloperContributions:110 commits, 64 pushes, 1 branch in 5 months
Contributions summary:Monal primarily addressed merge conflicts in the codebase, indicating they were likely involved in integrating code changes from different branches. The changes included modifications to a Python script used for querying statistics, suggesting involvement in the project's data analysis or performance monitoring aspects. They also merged changes to the FStar_Parser_Env.ml and other .ml files, indicating some level of work involving compilation and build processes.
homotopy-type-theorycoq-librarytype-theorysat-solvercompiler
monal/monal.github.io
May 2016 - Dec 2022
Contributions:310 commits, 286 pushes in 6 years 7 months
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