My Projects
Golf PDI Website/App
- Developed high-performance React components with a focus on responsive design and user experience
- Implemented backend code in Node.js that efficently manages data between the database and website allowing for a seemless user experince
- Integrated Stripe into the website/app allowing Golf PDI to transition to a subscription based buisness model
- Created a notification service in the application using Firebase Cloud Messaging allowing the company to reach its users through notifications
ReactTypeScriptJavaScriptNode.jsPrismaSQLStripeFirebaseCypress
View WebsiteCFCU Digital Banking Website/App
- Designed and developed new features on CFCU's digital banking app and website
- Engineered a social event platform for CFCU employee's to see and register for CFCU hosted events
- Implemented features like the ATM Locator and check image display; Along with user reward, credit card, and loan management features
- Designed efficently and securely with the user experience in mind
ReactJavaScriptCSSHTMLJavaSpring Boot
View WebsiteResponsive Portfolio Website
- Designed and developed a personal portfolio website using React and Next.js.
- Implemented responsive design principles to ensure optimal viewing across all devices.
- Utilized Tailwind CSS for efficient and consistent styling.
- Incorporated smooth animations and transitions for enhanced user experience.
ReactNext.jsTailwind CSSFramer Motion
View on GitHubKubernetes Chaos Engineering
- Implemented and containerized a live chat application using Python Flask, MongoDB, and Docker.
- Deployed the application to a Kubernetes cluster on Google Cloud Platform.
- Used Chaos Mesh to inject faults and examine system fault tolerance.
PythonFlaskMongoDBDockerKubernetesGCPChaos Mesh
View on GitHubPython Socket Programming
- Engineered a multi-threaded proxy and webserver using Python socket programming.
- Implemented proxy server caching to reduce webserver load.
- Developed safe termination protocols for server threads.
PythonSocket ProgrammingMulti-threadingCaching
View on GitHubStock Market Price Prediction using RNNs
- Implemented and extended a research paper on stock market prediction using PyTorch and NumPy.
- Adapted models for S&P 500 and Apple stock data, incorporating additional features.
- Introduced Bidirectional LSTM (BLSTM) and optimized existing models.
- Conducted comprehensive evaluations using Python Pandas.
PythonPyTorchNumPyPandasMachine LearningRNNLSTM
View on GitHub