About Me
I'm a developer who specializes in solutions for finance-related problems. In early 2021, I became obsessed with the stock market and how trends work. With each price making it's mark on history, the immense amount of data became a playground. I searched for trends and anomalies.
Naturally, I stumbled upon crypto and fell in love with blockchain and its use cases. Decentralization fascinated me. The idea of replacing modern-day processes with trustless systems felt like the future. I picked up a book and built a small voting application on the blockchain. I experimented with Sepholia, an Ethereum testnet, and conducted test transactions through a web interface.
Then the artificial intelligence buzz came around. I dove into neural networks, specifically convolutional neural nets. I got deep into data and solidified my understanding of data engineering. Sample sizing, data preprocessing, structured analysis. It all clicked. I used that knowledge to build a malware detection model with CNNs to differentiate between benign and malicious malware.
But the stock market kept calling me back. I saw the gaps in trading tools and financial automation. I set out to develop solutions for the market. My focus now is on creating systems that empower traders, leveraging data and automation to give them an edge.
JavaScript
TypeScript
React
Next.js
TailwindCSS
Node.js
Java
PostgreSQL
Stripe
Python
Pandas
PyTorch
Docker
Git
AWS
QUANTUM WAVE
A multi-timeframe stochastic trading indicator designed to help traders identify optimal turning points in the market. With 120 signed-up users and 72 active traders, it has generated $33K CAD in revenue from Q2 2024 to Q1 2025. The platform is developed using Next.js and built entirely with TypeScript, ensuring a scalable and maintainable architecture. Authentication and customer data are managed through PostgreSQL via Supabase, while purchases and subscriptions are seamlessly processed using Stripe. Discord integration is handled through Python-based Discord bots hosted on AWS, which verify user subscriptions and grant access accordingly. The indicator itself is built with PineScript and utilizes market data through TradingView.
Elliott Wave Pattern Recognition Dataset
An initiative to gain data for recognizing Elliott Wave patterns in financial markets. The program extracts and processes data from Yahoo Finance at a given timeframe inputted by the user and uses pyplot to create an image of the pattern. The image, label, and price data is saved to create a dataset for future CNN and LSTM models to recognize elliott wave patterns.
Malware Detection Model
Malware Detection Model using Convolutional Neural Nets. Malware is visualized from its binary code to a grayscale image. Using an existing dataset of benign and malicious malware, I sucessfully trained a CNN model using PyTorch to distinguish between benign and malicious code with a 98.2% accuracy.
NASA Image of the Day App
NASA Image of the Day Explorer is an Android app that allows users to search, explore, and save NASA’s Image of the Day with a sleek, user-friendly interface. Built using Java and Android Studio, this app integrates NASA’s public API to fetch and display space imagery while allowing users to create their own personal library of favorite images using SQLite.
Contact Me
Feel free to reach out with any questions or ideas.