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Currently building

Aayush Baniya

Building OpenApplier — AI that applies to jobs for you.

CS + Math @ UT Austin. Austin, TX.

500+ users on OpenApplier$5.5K in hackathon prizes
Aayush Baniya portrait

About

CS + Math at UT Austin, Class of 2028. Based in Austin.

I build software that does work for people — currently OpenApplier.

Texas-raised, Nepal-rooted.

Building now

OpenApplier

AI that applies to jobs for you.

A Rust + Next.js platform that finds roles, custom-tailors a resume for each posting, and submits applications on your behalf — you approve every submission before it goes out. A Chrome extension does the form-fill on the employer's site, so the submission flows through your browser, not a server. Works on Workday, Greenhouse, Lever, and Ashby.

500+ users · Private beta · $5/mo Pro

Building with Abheek Pradhan and Armaan Amatya.

Selected work

MyFutureSelfiOS Engineering Intern · 2025
aImsgProductized · 2025
Watchtower CLIOpen source · 2025
HelpmanduShipped 2024 · Retired

Hackathons

OnionUSDpOnionDAO Hackathon · 1st place · 2025$3K
ReproLabAntler × Codex · 2026$2K DeepInvent credits
VoiceCanvasNepali Leaders of America · 1st place · Virtual · 2026$1.5K
Agent GraphLaunchD · Austin · 2026$500
Change-Aware AuditorAkash Network · AI Agent Build Night · Austin · 2026$500

Experiments

Smaller projects.

Blueprint ViewerConstruction blueprint QA with AI bounding-box overlay on PDFs.PrototypeLive
VisoAI → interactive 3D STEM scenes.Prototypetryviso.ai
BlinkFundX posts → on-chain Solana payments via Blinks.blinkfund.vercel.app

Research

Learning-Directed Operating Systems

UT Austin · Dec 2024 – present

ROS 2 manipulation-stack benchmarking on CloudLab (32-core EPYC). DDS middleware is the primary low-rate DoS surface — 4,000 msg/s flooding causes 100% MoveIt execution failure, and CPU sweeps show pipelines saturate at 2 cores, isolating execution latency as the bottleneck.

GitHub

Activation Patching Under Statistical Stress

BlueDot Impact AISF · Jan – Feb 2026

10,000× bootstrap resampling and multiple-comparison corrections on activation-patching claims for a Time Series Transformer. Most heads flagged “important” by naive patching don’t survive proper controls. Stable on simple tasks (p = 0.88–0.89), breaks on complex ones (p = 0.48).

GitHub

Experience

Security Analyst Intern · UT Austin RSOC

Windows / Linux internals, AD security, enumeration and web exploitation labs.

Jun 2025 – present

iOS Engineering Intern · MyFutureSelf

Shipped pre-launch → 5K+ users, 500+ reviews at 4.7★. Built the paywall.

Jul – Oct 2025

Contact