Resume

• Deploying and benchmarking learned quadrotor navigation policies in Isaac Sim and onto ModalAI Starling 2 drones.

• Architected Alpine, a modular PyTorch library to streamline the development of deep learning model development and training.
• Engineered a neural network pretraining method, boosting PSNR by 25-30 dB over meta-learned baselines, with 2x faster convergence.

• Developed a high-speed robotic vision system using ROS and OpenCV to track rocket trajectories in high-speed video.
• Pioneered a hybrid Neural-PID controller, decreasing tracking error by 94% and selected for deployment in Artemis moon missions.

• Automated the validation pipeline for RF field stabilization, eliminating the need for $350k in legacy hardware resources.
• Replaced manual PID tuning with robust self-tuning control algorithms for precise temperature control in particle accelerators.

• Collaborated with DoE researchers to achieve a 92% runtime improvement in MPAS Ocean through tracer advection modeling.
• Engineered GPU/TPU-compatible heat transfer models by reformulating physics equations into efficient tensor algebra operations.

In Submission · Medical Image Analysis

Accepted · CVPR 2026

Published · NM J. Science 2024

Published · NM J. Science 2022

• GPA: 4.0/4.0
• Scholarships: Max Roy Scholarship (Full Tuition), Los Alamos Lab Gold Scholarship ($20k)
• Coursework: Data Structures & Algorithms, Computer Vision, Machine Learning, OOP, Signals & Systems, Linear Algebra

• Building a differentiable 6-DOF rocket simulator in PyTorch that trains a neural thrust-vector-control policy by backpropagating through the physics.
• Designed a custom Teensy-based flight computer in KiCad to run the learned controller on real hardware.

• Founded a real-time productivity platform with AI-driven study assistance and focus environments (Dart, Google Cloud).
• Boosted system reliability for 1200+ users through optimized indexing, secure user authentication, and CI/CD.

• Developed AUV to capture subsea footage and process it with YOLOv5-based object detection (C++, Python).
• Implemented deep learning and SLAM-based mapping to discover 174,000+ pieces of ocean trash (Regeneron ISEF 3rd Place).

• Simulated over 8000 active satellite trajectories using OpenGL, ImGui, and C++.
• Implemented a modular graphics pipeline with optimized memory usage for smooth 3D visualization.