• Worked on backend engineering for a startup, including building and shipping features for core microservices and public APIs, as well as owning infrastructure as code in a distributed architecture

• Built a low-latency data streaming connector for the NEAR protocol

• Optimized database writes using a combination of batching and storage tiering, increasing peak write throughput by 20x

• Created a unified metrics, logging, and tracing system using Prometheus, Grafana and OpenTelemetry

• Leading research assistant for an applied machine learning lab focused on healthcare, with direct contributions to four publications

• Contributed to a convolutional neural network built using Keras and Tensorflow that was able to discriminate between surgical tools with 99.1% accuracy

• Created a novel research dataset of nearly fifty thousand images by processing surgical videos using OpenCV

• Optimized a large-scale public health data pipeline that processed millions of records using Apache Airflow, reducing execution time from hours to minutes

• Built a web scraping application that ingested millions of records from an array of public health data sources

• Built and deployed a web API using Python and Django to make data accessible to researchers

• Work led to an academic publication and presentation at a conference

Teaching Assistant for Object Oriented Programming and Introduction to Computer Systems classes.