• Developed an automated Selenium-based data ingestion pipeline in Python to extract school datasets from GreatSchools, supporting downstream analytics and AI-driven recommendation features; deployed the workflow on Render for scheduled and scalable execution.

• Redesigned the authentication flow by implementing an email-verification login system using FastAPI and SQLAlchemy. Integrated OAuth2PasswordRequestForm and FastAPI Security utilities to strengthen identity management for ML-enabled application features.

CS5800 Algorithms 2023 Fall

CS6140 Machine Learning 2024 Spring

Career Peer Advisor 2024

• Developed an interactive neural network model editing platform using React, TypeScript, ReactFlow, and Dagre, enabling users to modify computational graph structure and layer parameters via drag-and-drop interactions.

• Integrated existing model inference cost estimation APIs by building Python/Flask end points and visualization components, allowing users to evaluate latency, FLOPs, and optimization impact after model edits.

• Implemented export functionality for TVM and JSON model formats, supporting downstream model compilation and deployment workflows.

• Collaborated with ML and software engineering teams, conducted testing, and maintained documentation to support scalable ML tooling development.

Regulatory compliance