Work & Research

Software Development Engineer Intern

Amazon Web Services (AWS) · May 2026 -- Aug 2026

ProActive Security Team

AI/ML Research Intern

FloodWatch (floodwatch.io) · Mar 2025 — Present

Contributing to an NSF-funded flood early warning system for smart cities.

  • Built backend + frontend services (TypeScript, Next.js, tRPC, AWS Lambda) for platform features and data delivery.
  • Developed and deployed deep learning + statistical forecasting models to predict real-time flood severity from weather, satellite, and IoT sensor data.
  • Co-authored an IEEE CAMA 2025 paper on an unsupervised multimodal statistical framework for flood severity.
TypeScript Next.js tRPC AWS Lambda

Software Engineering Intern

Dewberry Engineers · Jun 2024 — Feb 2025

Built a secure analytics platform to automate financial document processing and collaboration.

  • Developed a secure analytics web platform with React, Flask, PostgreSQL, Docker, and Kubernetes.
  • Automated financial document processing for multi-user collaboration, reducing reporting time by 50%.
  • Built a document intelligence pipeline integrating OCR (Tesseract) + GPT-4 API for extraction, entity recognition, and anomaly detection.
React Flask PostgreSQL Docker Kubernetes

Software Engineering Intern

Anote.ai (Breakthrough Tech AI) · May 2025 — Present

Built a benchmarking suite and leaderboard to evaluate API-submitted AI models across tasks.

  • Developed and integrated a benchmarking suite (Flask, MySQL, React) to evaluate models across web, Q&A, and image classification tasks.
  • Built an interactive leaderboard to compare performance consistently across models and datasets.
  • Implemented evaluation metrics and integrity safeguards to ensure fair comparisons and prevent metric gaming.
Flask MySQL React Evaluation

Research Assistant

UVA Link Lab · Jun 2024 — Present

Researching self-driving policy interpretability using reinforcement learning and simulation tooling.

  • Built an RL data collection pipeline to study self-driving policy interpretability; engineered a custom driving rig.
  • Fine-tuned MetaDrive simulators for replay/control of 10,000+ Waymo scenarios.
  • Applied behavioral transformers and adversarial imitation learning residual policies to gather expert-like driving data.
Reinforcement Learning MetaDrive Imitation Learning Python

Research Assistant

UVA School of Medicine · Jan 2024 — Feb 2025

Published deep learning work for large-scale analysis of experimental images + text records.

  • Published a psychiatric journal paper on a deep learning pipeline combining CNNs + SBERT.
  • Enabled automated analysis of 100,000+ experimental images and text records.
PyTorch CNNs SBERT Research

Skills

Languages

Python, Java, C/C++, JavaScript/TypeScript, SQL

ML / Data

PyTorch, TensorFlow, NumPy, pandas, sklearn

Tools

Git, Linux, Docker, FastAPI, Firebase