Selected Work:

  1. 01
    Fail Fast, Run Faster: Shape Safe Deep Learning in Rust on Apple Silicon (PDF) ->

    Const-generic Rust deep learning pipeline with compile-time tensor shape checks and Apple Silicon acceleration.

  2. 02
    Automated Liver Tissue Analysis Pipeline ->

    Point-of-care biopsy analysis with U-Net segmentation and on-device steatosis scoring on Jetson Nano.

  3. 03
    CTDE vs. Independent PPO: Benchmarking Multi-Agent Coordination in Flow-SUMO Vehicle Platoons (PDF) ->

    CS229 study comparing centralized training and independent learning for coordinated autonomous vehicle platoons.

  4. 04

Currently:

  1. 01

    Researching medical computer vision at Stanford's Melcher Lab.

  2. 02

    Incoming Software Engineering Intern at Apple.

  3. 03

    Based in Stanford / Bay Area.

  4. 04

    Recently ran Napa Half Marathon Strava ->

  5. 05

    Upcoming SF Marathon.

  6. 06

    Fluent in Spanish!

Past Experience:

  1. 01

    Aida (SWE Intern, 2025): Built Python/SQL/GCP backend services for CRM automation and production workflows.

  2. 02

    Stanford AIMI (Software Intern, 2022-2023): Trained a ResNet-50 chest X-ray device detection pipeline to 97% accuracy.

  3. 03

    Melcher Lab, Stanford (Software Engineer, 2020-2025): Co-developed a Jetson + iOS + GCP liver analysis system with 100x lower latency.

Some Classes:

  1. 01

    CS143: Compilers (building a compiler from scratch!)

  2. 02

    CS111: Operating Systems

  3. 03
  4. 04

    CS231n: Deep Learning for Computer Vision

  5. 05

    CS229: Machine Learning

  6. 06

    CS234: Reinforcement Learning

  7. 07

    EE108: Digital System Design

Current Project:

In Progress

A COOL Project: My Custom COOL Compiler

Building a compiler from scratch in Stanford CS143, working through parsing, semantic analysis, and code generation.

Read the project note ->

Research

Papers, clinical computer vision, and course research projects.

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