I am a third-year Computer Science PhD student at Stanford University, advised by Clark Barrett.
My interests center on neurosymbolic AI, especially autoformalization, where large language models (LLMs) are used to translate natural language into formal representations (e.g., Lean) for rigorous reasoning and verification.
Previously, I have worked on SMT solvers, loop invariant generation, program synthesis, and verifying software network functions.
I’m seeking Summer 2026 internships. If you think I’d be a good fit for your team, or know of any roles I might be interested in, please reach out!
Email: daneshvar [at] cs [dot] stanford [dot] edu
News
[July 2025]: Our paper “Towards Improved Stability for SMT Solvers via Input Normalization” got accepted to FMCAD 2025.
[June 2025]: Joined the Automated Reasoning Group of Amazon Web Services (AWS) in Santa Clara, California as an Applied Science Intern.
[June 2025]: Passed my PhD qualifications exam and earned a Master’s degree in Computer Science.