Full-stack developer on the network modeling team; specialized in solving problems at Bloomberg's large network scale by utilizing research methods and algorithms and data structures to achieve performant solutions.

• Implemented a contextual firewall policy analysis tool for policy diffing, shadowing,

optimization, and testing based on net flow change. Made original enhancements to the firewall decision tree [FDT] data structure to meet the time and space constraints for enterprise policies, some of which were orders of magnitude larger than benchmark policies in reviewed literature.

• Lead engineer of a network device configuration and topology modeling platform that stored and serviced Bloomberg's device network. Designed a self-servicing architecture that allowed network engineers to model the network devices within their domains using GraphQL schema definition language, which would be auto-ingested as a GraphQL API backed by a graph database.

Tutored students and graded student exams, tests, homework assignments,

and projects for Hunter College's Computer Architecture 1 course.

Team lead of the US Night Skies Urban Development team.

• Worked on refinement and validation of an application for estimating skyglow (light pollution)

using NASA satellite data.

• Developed a new feature for generating hemispherical visualizations of light pollution at a

chosen area.

• Led team through the fulfillment of all project requirements, designing a poster, video, and

writing a scientific paper on our work.

• Presented our work at NASA DEVELOP's annual research conference.

• Aided novel research seeking to use the angle and position of missing data points in 3D LIDAR scans to improve the accuracy of CNN-driven vehicle classification algorithms.

• Helped with data collection and processing of LiDAR-scanned 3D point clouds of NYC streets.

• Labeled and drew bounding boxes for different vehicles in Velodyne 3D point cloud scenes to

provide training data for the neural network.