Contributing to expanding the functionality of BookNLP (https://github.com/dbamman/book-nlp), a natural language processing pipeline for books and other long documents, under the supervision of Professor David Bamman.Research involves reading works of fiction in Spanish, annotating linguistic phenomena and building/evaluating computational models for Spanish Natural Language Processing.

Studied the effects of translator style on the translation of global news dispatches, mainly from English into French, under the direction of Professors Justin Davidson and Mairi Mclauglin. These dispatches are the building blocks of international news published and broadcast in French, Italian and Spanish.Worked to automate the manual process of searching for linguistic phenomena by developing an iPython interface to carry out natural language

• Led 180-person organization as a voting member on the board of directors and head of the executive committee.• Coordinated $2 million annual operating budget, created a centralized communication and budgeting platform to reduce excess costs and increase budget transparency• Navigated Covid-19 protocols to maximize overall well being of hall members, facilitated faculty changes to smoothen transitions, and implemented a constitution to codify rules of the hall with Executive Committee.

• Kicked off the development of an internal portal that allows for automation of the manual, labor intensive process to book and schedule First Aid Safety training courses consulting for a 40,000 employee Fortune 500 company. – Developed most of the existing front-end views and layouts using React.js, Redux, and the Material-UI framework. – Implemented global state management forthe application using Redux. – Interfaced with API’s in orderto draw data from SAP and Google Cloud.• Simultaneously took personal initiative to develop an in-house IoT solution utilizing Google Cloud Platform’s IoT Core service.

• Created a proprietary machine learning application (SaaS) on a team of five using Google’s Vision API that analyzes live video data and classifies in real time. Primarily the use case for the application is to detect defective products on a production line before they are cleared to ship.– Developed the full stack of the application using React.js for the front end, while using Google Kubernetes Engine clusters, along with a small physical server, to run the back end.– Set up a containerized software package for clients allowing effortless setup of a client side Ubuntu board with an attached CV camera.

Academic Intern for CS 61B, UC Berkeley’s data structures course. Responsible for helping teach students data structures like ArrayLists, disjoint sets, BSTs, Red Black Trees, HashMaps, heaps, priority queues, Tries, KDTrees, and graphs. Also responsible for helping teach concepts such as unit testing, asymptotic analysis, hashing, graph traversals (A*, DFS, BFS, etc.), and list sorting algorithms.