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Projects

Finwatch

Type: Personal
Timeline: Built in 2024
finwatchapp.com

As a longtime Mint user, I was disappointed when Intuit announced its shutdown in 2023. But in hindsight, it sparked an exciting opportunity — to build a budgeting app of my own. I had recently discovered Plaid, which made it easy to let users securely link their bank accounts without ever sharing passwords.

That’s how Finwatch was born. The app offers seamless banking integration via Plaid, custom transaction categorization, net worth tracking, monthly income and expense summaries, and a unique feature — transaction read receipts — so users can always pick up right where they left off.

And this is just the start. I'm currently working on features like AI-powered category predictions, budgeting tools, transaction splitting, enhanced analytics, and more.

Tools Used:
React
Node
AWS DynamoDB
AWS Lambda
AWS API Gateway
AWS SQS/SNS
AWS S3
Plaid
Chick'n Out Customer Orders

Type: Freelance
Timeline: Originally Built in Fall 2020
A local Rochester, NY business offers a pop-up style restaurant which advertises when and where they will be selling their very popular fried chicken to their Instagram followers. Customers have a chance to get their orders in as soon as the "drop" goes live, but they must be very quick because these sales sell out within minutes! I designed and built this application from the ground up so the business would have a branded order workflow to complement their well branded website and instagram. Additionally they avoid the surcharges they were incurring previously with third party solutions.

Tools Used:
React
Node
AWS Amplify
AWS Lambda
AWS API Gateway
AWS SQS
AWS etc
Fat Ergo Data

Type: Personal
Timeline: Originally Built in Spring 2018
Being on the crew team at school filled my phone up with photos of an ergometer screen as each week we were tasked with getting 1-2 supplemental workouts done on our own time and reporting our workouts to our coach. So I developed an application that given an image of an ergometer screen it would output the salient data from the image. In my latest tests, given 62 random images of ergometer screens with varying quality the program can grab the salient data with 93% accuracy. I believe if this was implemented in a mobile app that could regulate the quality of images coming in, this percentage would be sufficient. As of now I only have the backend code written to compute the data from the image. In the future I would like to develop a mobile app that will put this code to use in real-life scenarios. This app could prove to be extremely useful for crew teams across the world at any level. Helping teams keep track of their weekly workouts, holding teammates accountable to completing their workouts, and improving times by encouraging competition through leader boards every workout.

Tools Used:
Python
OpenCV
Various Computer Vision Algorithms
Quickscript

Type: Personal
Timeline: Originally Built in Spring 2017
This was developed when a local pharmacy employee recognized a need for an on-demand prescription delivery service as customers day after day were vocal with their discomfort waiting in the prescription pick up line. The application is currently ready to be used, I am in the process of integrating with local pharmacies who are interested in the platform.

Tools Used:
Javascript ES5/ES6
Meteor
Node.JS
React
jQuery
HTML
CSS
Stripe
Asynchronous Programming
Responsive Design
Bootstrap
Budget

Type: Personal
Timeline: Originally Built in Summer 2016
Previously I used Excel spreadsheets to form a budget and keep track of my spending, I found this to be incredibly tedious and error-prone. So after learning about the Django Framework at RIT, I decided to make a budgeting application for my personal use.

Tools Used:
Python
Django
HTML
CSS
Javascript
jQuery
jQuery UI
AJAX
Selenium
Web Scraping