Vincent Fiore

Capital One

• Led a rearchitecture of legacy production release pipeline flows, which reduced API load and increased UI performance by more than 50%.
• Architected and implemented an organization-wide error code API, providing real-time updates on more than 5,000 errors across 30+ sources of truth and dozens of teams.
• Integrated Jira Xray into the software delivery pipeline, facilitating quality checks for more than 700,000 releases each year.
• Interviewed dozens of candidates to help double team size and expand sister teams.

Sema4

• Developed Java Spring APIs on AWS Serverless architecture to process quality control data for large-scale genetic testing.
• Engineered Node.js Lambdas and Step Functions for asynchronous, real-time processing of lab data, supporting the company's largest testing suites.
• Reduced API response times and decreased memory usage by up to 90% by implementing ElastiCache for Redis in multiple applications.
• Worked with Product teams to design and build features that are currently in use by thousands of providers.

New York City Department of Investigation

• Maintained and enhanced the agency's Java CMS application, implementing key updates and ensuring system stability.
• Migrated a legacy COBOL database to a modern Java application with a user-friendly interface, enabling efficient reporting and access to decades of data.
• Developed Python scripts to automate investigative search tasks, reducing processing time from hours to minutes.
• Replaced failing Access databases with robust Java applications using Oracle backends, significantly improving uptime, reliability, and user experience.

Major League Baseball

• Used Python to create programs to automate workflows that previously took hours of manual work.
• Created and managed queries for Sumo Logic dashboards.
• Managed and conducted internal and external network scans using Qualys.
• Configured and administered hundreds of employee phones using AirWatch.

Les Pain

Programmed and designed an iOS application using Swift and Firebase for chronic pain patients to track their pain and communicate with doctors.
• Created a Java backend API for hosting user data.
• Released private beta to over 30 users and made changes based on feedback.
• Released full version of application to Apple App Store.
• Finalist team in Zahn Innovation Center Entrepreneurial Competition.

Pace University

Twitter Sentiment and Topic Analysis

Used machine learning and natural language processing to determine the mood and topic of Tweets, creating a classifier that correctly predicted each 87% and 90%, respectively. The team’s research was published as part of Pace University’s Student-Faculty Research Day on May 5th, 2017.
Our Research

Programmatically Produced Cybersecurity Thesaurus

Used natural language processing techniques to dynamically create a thesaurus of cybersecurity words based on the Tweets of experts in the field. Our team parsed over 40,000 posts to find recurrences, remove irrelevant words, and create a pertinent corpus.
Our Research

Majestic 35, Movie Collecting App

Worked with a partner to produce an application for users to catalog and share the movies they’ve seen with friends. Used Swift, Firebase, and Cocoapods to create the application and backend. Published on the Apple App Store.