Project Portfolio

Thank you for taking the time to visit my online portfolio! Here you’ll find a carefully curated collection of my completed projects, showcasing my skills and expertise in various fields. This page is constantly updated with new and old projects, so be sure to check back often. Each project title links to the corresponding GitHub repository, where you can read more about the project and even explore the code yourself. I’m excited to share my work with you, and I hope you enjoy browsing my portfolio!

Graduate Project

Stroke Prediction and Inference in R and Python

As part of my graduate studies in Applied Data Mining and Analytics in Business, I worked on an exciting project focused on Stroke Prediction. Using the Stroke Prediction Dataset from Kaggle, I carefully analyzed the data to gain insights into the risk factors associated with stroke. To ensure the accuracy of my findings, the dataset was refined to include only adults (Age >= 18), as the risk factors for adolescents and children are not captured in this dataset. This allowed me to delve deeper into the data and gain a more accurate understanding of the underlying risk factors associated with stroke

The primary objective of the project was to conduct a thorough data exploration and build a model that could accurately predict stroke risk, comparable to the physician-established CHADS-VAS Score. The CHADS-VAS Score uses various risk factors, including age, biological gender, presence of congestive heart failure, hypertension, history of strokes, heart disease, and diabetes. To create a more comprehensive and precise risk model, I aimed to integrate additional social determinants of health such as marriage status, work type, and residence type, into the existing model. This approach has the potential to provide a more accurate and nuanced prediction of stroke risk than what is currently available.

RShiny App - Housing Market Dashboard

As part of my graduate course in Data Visualization, I had the opportunity to create an interactive dashboard using reactive R language. This dashboard allows users to easily compare the housing market trends for each state over the last decade. The main motivation behind this project was to provide novice users with a clear and concise overview of the housing market in each state.

The user interface is simple and intuitive, allowing users to select the state they are interested in and use the date slider to zoom in on specific time ranges. The dashboard displays how different types of residential properties have increased in value over the last 10 years, using data collected by Redfin on a per-month basis (i.e., median sale price for Jan-2019). This provides an informative and engaging way for users to explore housing market trends, making it a valuable resource for anyone looking to gain insights into the real estate industry.

Undergraduate Projects

Ammonia Production Model and Optimization

As part of my senior-level course in Kinetics and Reactor Design, I undertook a project that involved designing an autothermic reactor for ammonia production. To achieve this, I created three different reactor models, each highlighting the potential impact of varying design parameters on conversion rates. Building design equations, solving systems of ODEs, and optimizing parameters were some of the key tasks that I had to undertake during the course of this project. All of the model design was done using MATLAB, and involved solving systems of linear equations such as energy balances and net rate equations, as well as calculating gas heat capacities. By demonstrating the depth and breadth of my modeling skills, this project showcases my expertise advanced numerical methods.

Iterative Mass and Energy Balance

For my junior-level course in Mass and Energy Balance II, I tackled a project that involved solving a system of linear equations iteratively for an underdetermined system, or recycle stream. Although the original project scope called for using Excel’s “Goal Seek” to solve for unknown values at three different temperatures, my self-taught skills in MATLAB led me to complete the project using that language instead. I was able to solve for all 150 possible answers, showcasing my proficiency in advanced numerical methods such as matrix algebra, solving underdetermined systems, and calculus. This project is a testament to my strong work ethic and my ability to learn new skills quickly and effectively.