August 2025- December 2025:
Under the advice of Ms. Abbaszadegan, my job involved me researching the tools and tech stack required for the roles. I also served as a Scrum Master, research lead, and also helped coding the frontend for the product. After researching, I found that Java and PostGresSQL would work best for Inventrade's backend as it had better Relational Database Integrity, and AWS C2 and Lambda services for scalability and convenience. I also worked on flowcharts describing both how Buyers and Sellers would go through the app/website and began to code our frontend in the Fall.
Jan 2026-May 2026:
The second semester of Inventrade involved us working on the coding of the frontend and backend of the application. worked on the Seller Confirmation page of the frontend using React, authored a two page documentation of teammate's contributions and research, implemented the UI of the Preferences page with React and implemented the backend for it, allowing Users to choose preferences from cities, categories, and industries. From the guidance of Professor Echeagaray, I contributed to making our powerpoints and posters for the Capstone Showcase. After we presented to our sponsors and professors, Inventrade will be launched to 50 customers.
Reflection:
This project was the bridge between my undergraduate CS degree and my upcoming Master’s in Data Science at ASU.
Working on a product like this felt impactful as an engineer. It was my first time contributing to something with huge value and real-world consequences. I've had to face some major hurdles in this project which tested me personally and professionally. Whether it was dealing with serious time management issues when it was my turn to be the Scrum Master (the group leader) for the team; Or it was my technical skills, when a bug I accidentally created made it impossible to click the page in the Preferences section and I needed to use the browsole console to identify the incorrect line of code. Additionally, mastering the backend architecture in Spring Boot provided me with a foundational understanding of how data pipelines function, which is essential for my future as a data scientist when deploying scalable machine learning models into production environments. I definitely think that this served as my culminating experience both as my Capstone project and final GCSP experience.
Sustainability Connection:
The Capstone was overall a good experience with helping me code professionally and employ my technical skills to a meaningful cause. It was a culmination of my work as a CS major. Inventrade connects to Sustainability. This was a great way to do apply my technical skills and connect it to my theme of Sustainability as Inventrade helps with reducing wastage of old industrial equipment and promotes sustainability as a whole. By digitizing the secondary market for industrial equipment, Inventrade extends the lifecycle of carbon-intensive machinery, reducing the Scope 3 emissions associated with manufacturing new replacements. The search function on Inventrade also has a distance selection meter which can optimize distances to use less gas to get the best product.
You can see the pictures of the pages below.