Resume

Automation / AI Software Engineering Intern · Houston, TX

• Built AlgoBuilder, an LLM agent system that generates and validates NAND/NOR flash programming algorithms. It reached over 80% fully automated completion across more than 40 validated algorithms, saving an estimated 10–15 engineering hours per algorithm.
• Modernized Chip, an internal AI assistant used by about 75% of employees. Connected it to Salesforce and Google Drive through the Model Context Protocol (MCP), added tests, and cut the cost of model calls.
• Built PDR Builder, a pipeline that turns datasheets and product specs into engineering artifacts, with deterministic validation and human review. It passed 27 of 27 historical design validations.
• Extended the BPWin REST API from 1.2 to 1.9 with job monitoring, device discovery, and validation endpoints so programming jobs can run unattended.

Robot Learning Research: Zero Shot and Active Learning · West Lafayette, IN

• Developing methods that use LLMs and diffusion policies to generate robot demonstrations without human input. The demonstrations bridge transitions between hubs, and from hubs to goals, in latent space so a robot can learn new tasks zero shot.

Computer Vision Research · West Lafayette, IN

• Implemented computer vision methods that transcribe piano performance video into MIDI, tested on the Rach3 and PianoYT datasets and used to evaluate generative systems for music performance.

Robot Learning and Teleoperation

• Fine-tuned SmolVLA, a vision-language-action (VLA) model, on 50 teleoperated episodes, raising task success from 0% to about 75%. Built XR teleoperation with Meta Quest/Unity and a digital twin. Honorable Mention, Best Use of AMD Tech, StarkHacks 2026.

Browser Extension for Detecting AI Content

• Built the integrations for five social platforms (LinkedIn, Facebook, Instagram, X, Reddit) in a browser extension that flags likely AI-generated posts. Cut detection time to about 0.6 seconds.

Financial Machine Learning Research System

• Built an ML system that predicts abnormal stock returns after SEC filings using only data available at filing time, validated with purged walk-forward cross-validation and backtested net of transaction costs.

Market Simulation and Automated Trading

• Built an event-driven market simulator that replays Level 2 order book data with latency- and depth-aware fills, plus a strategy engine that runs the same code in backtests and Interactive Brokers paper trading.