• Managed and conducted internal and external network scans using Qualys
• Created programs to automate workflows that previously took hours of manual work to complete using Python
• Administered and setup of hundreds of employee phones using AirWatch
• Created and managed queries for SumoLogic dashboard
Programmed and designed an iOS application using Swift and Firebase for chronic pain patients to track their pain and communicate with doctors.
• Released private beta to over 30 users and made changes based on feedback
• Finalist team in Zahn Innovation Center Entrepreneurial Competition
• Released full version of application to Apple App Store.
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.
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.
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.
Java & Android. Swift & iOS. Python. C, C++, UnrealScript. SQL, MySQL, NoSQL.