The engineer that I am today, and how I got here.

A compiliation of the languages, frameworks, and technologies that I've worked with.

Programming Languages

  • Java

    Java is a versatile programming language that enables the development of robust, high-performance applications. I leveraged its capabilities in a project to create a distributed system for real-time data analysis during launch simulations.

  • Python

    Python is my go-to language for data analysis and machine learning. I recently developed a Python-based tool that visualizes complex datasets, enhancing my ability to make data-driven decisions on large-scale projects.

  • C++

    C++ offers low-level control and high performance, which I appreciate when working on resource-intensive applications. I have a collection of classic keyboards that enhance my coding experience while developing C++ applications.

  • Javascript

    JavaScript is essential for interactive web development. In a recent project, I built a dynamic web application that utilizes JavaScript's gesture capabilities to improve user engagement and enhance the overall experience.

  • SQL

    SQL is invaluable for managing and querying databases efficiently. I used SQL in a data migration project, streamlining the process and ensuring seamless transitions between systems.

Frameworks/Libraries

  • Next.js

    Next.js is a powerful framework for building server-side rendered applications. I employed it to improve SEO and performance in a web project, enjoying the simplicity it brings to routing and data fetching.

  • PyTorch

    PyTorch is my preferred framework for machine learning tasks. I recently implemented a deep learning model for image classification, benefiting from its intuitive API and robust features.

  • Pandas

    Pandas simplifies data manipulation and analysis. I used it in a reporting tool project, enabling efficient handling of large datasets and saving time on admin interface development.

Technologies

  • AWS

    AWS is a reliable cloud platform that supports scalable applications. I utilized AWS in a project to deploy a user data management system, leveraging its infrastructure for optimal performance.

  • Kubernetes

    Kubernetes is crucial for orchestrating containerized applications. I integrated it into my workflow, enhancing organization and allowing me to document insights while managing microservices.

  • Jenkins

    Jenkins is an excellent tool for automating tasks and scheduling workflows. I used it to streamline deployment pipelines, ensuring I maintained focus on deep work while meeting deadlines.

  • Postman

    Postman is a versatile tool for API development and testing. It played a key role in a recent project where I developed and tested APIs, helping me maintain productivity and focus during the process.