University of Massachusetts, Amherst|Amherst, MA

B.S. in Computer Science, B.S. in Mathematics, B.S. in Economics | GPA: 3.811/4.0 (August 2020 - December 2024)

• Undergraduate Coursework: Data Structures and Algorithms, Artificial Intelligence, Data Science, Design Patterns, Operating Systems, Database Systems, Statistics I & II, Statistical Computing, Regression Analysis, Advanced Linear Algebra, Multivariable Calculus, Discrete Mathematics, Abstract Algebra, Macroeconomic Theory, Microeconomic Theory
• Graduate Coursework: Machine Learning, Convex Optimization, Systems for Data Science

University of Massachusetts, Amherst|Amherst, MA

Undergraduate Research Assistant (September 2023 - Present)

• Studying how convex optimization and modern statistical theory can be used to create new machine learning methods for Recommender Systems that aim to avoid significant differential performance between different groups/classes of people.
• Implementing fair machine learning methods on Recommender Systems using Python and libraries such as cvxpy and applying them to relevant datasets to achieve more fair model performance across all different groups of people.
• Attending weekly meetings with a supervising graduate student and professor to discuss progress on the project and paper.
• Viewing weekly presentations given by graduate students in the same research group about related topics also dealing with safety/fairness.

University of Massachusetts, Amherst|Amherst, MA

Undergraduate Research Assistant (June 2023 - Present)

• Investigating whether server communication in a distributed database bottlenecks short read query latencies in local or wide area networks.
• Leading a small group of undergraduate students to build a distributed query execution engine using Java, CockroachDB, gRPC, and Docker for the purpose of running experiments on short read queries to record their execution times under different controlled settings.
• Implementing many different short read queries to understand their execution time performance under different server configuration settings.
• Attending weekly meetings with a supervising professor to discuss the progress on the query implementations and experiment results.

University of Massachusetts, Amherst|Amherst, MA

Undergraduate Course Assistant (January 2023 - Present)

• Answering questions online and in person during labs to clarify concepts for confused students and gave hints on how to solve problems.
• Reviewing homework and exam submissions by writing thoughtful feedback to students on where they did well and where they can be better.
• Discussing with other Teaching Assistants in the Computer Science Department on what current strategies and processes can improve.
• Communicating with the professor during weekly meetings on how well students are doing in the course in terms of their grades and mood.

University of Massachusetts, Amherst|Remote

Undergraduate Research Volunteer (June 2021 - July 2021)

• Implemented the VGGNet architecture using Pytorch and achieved more than 92 percent test accuracy on the CIFAR10 dataset.
• Reviewed papers on Continual Learning and its application to address catastrophic forgetting, an issue faced by deep learning solutions.
• Explored and reproduced the performance of different continual learning solutions to observe their effects on reducing catastrophic forgetting.

STEMHQ - Tech Garage|Boca Raton, FL

Camp Counselor (June 2019 - August 2019)

• Taught children ages 6-14 the fundamentals of programming in Python and Java.
• Walked through and demonstrated solving programming challenges through the CodeCombat platform.
• Assisted children in programming and controlling custom built quadcopters using Python to navigate across obstacles and do aerial stunts.

STEMHQ - Tech Garage|Boca Raton, FL

Camp Counselor (June 2018 - August 2018)

• Mentored children ages 6-14 in the fundamentals of mechanical design using Actobotics parts to build land and underwater ROVs.
• Assisted children in programming and controlling their ROVs using Python and OpenCV to complete several tasks and missions.

End-To-End Diabetes Diagnosis Machine Learning Pipeline and Web App

• Developed a pipeline using Python that collects and cleans over 100,000 data records of people’s medical information which is later used to train different ML algorithms such as Neural Networks and Random Forests to record performance metrics and select the best models.
• Deployed and tested the pipeline using Github Workflows, Docker, and Amazon Web Service’s Elastic Compute Cloud to ensure that data ingestion, model training, and model inference works correctly as data comes in and users request a diagnosis.
• Created a simple web app using Python Flask that allows users to input their relevant medical information and receive a diabetes diagnosis.

Full Stack Parody Reddit Application

• Implemented an intuitive user interface using Next.js that allows users to create media posts and threads for different topics, and perform other interactions such as commenting, upvoting/downvoting, joining/leaving, and logging in/out.
• Designed a database and schema using MySQL and Prisma to organize and store important user content such as login information, relevant conversations threads, and posts they have created or interreacted with.
• Optimized user content retrieval by using Upstash Redis to cache content recently viewed so the application isn’t always making backend requests to the database to render user content.