New York, New York, United States
I am an MIT Alumni (EECS B.S '22, EECS M.Eng '23) who has a passion for leveraging machine learning and software engineering to tackle complex problems across diverse domains.
YouTube Search & Ranking
Designing and developing AI/ML tools to create interfaces to betters understand and learn from news media
- Implemented a C++-based MapReduce pipeline to bulk generate incentive promotional codes, allowing more accessible access to the premium services referral system. - Generated ~9 million codes for the YouTube Premium Friends Referral Program for a go-to-market email campaign. - Designed and implemented expanded support for incentive campaigns on family accounts using C++, providing a greater reach of incentive programs on family plans.
- Improved the quality of annotations on Google user data by implementing a Java-based MapReduce style pipeline to propagate conflicts between data annotations and human assertions. -Collaborated with multiple teams in the Google GCP organization to design and approve a series of design docs outlining the development of a new multistage MapReduce pipeline aimed to synchronize data annotations.
- Created a full stack web portfolio that used Java Servlets, JavaScript, and HTML in conjunction with the Google Charts API and Google Sentiment Analysis API - Developed an open-source application (with two other interns) which involved creating a design doc, having design reviews by mangers, and performing a soft launch for the project internally - Used Google Charts API, Google Datastore, Java, and JavaScript to create infographics based on user ratings as part of an open-source application that allowed students to rate and review classes at their institution