I'm a Computer Science student and software developer with a deep passion for building intelligent, scalable, and user-centric applications.
My goal is to build a career that bridges the gap between powerful AI/ML models, robust DevOps infrastructure, and intuitive Full-Stack applications. I thrive on understanding the full lifecycle of a product, from the cloud architecture it runs on to the user interface it presents.
- 🎓 I'm currently a Bachelor's student in Computer Science.
- 🎯 My primary interests are Machine Learning, Cloud Development (GCP), and automation.
- 🌱 I’m always learning and currently focused on advanced deep learning techniques and cloud-native architectures.
- 💻 My daily driver is Arch Linux—I love building my development environment from the ground up.
- 📫 How to reach me: [email protected] or on LinkedIn.
Here are the primary technologies I work with, categorized by my areas of focus.
| AI / Machine Learning | Full-Stack Development | DevOps & Cloud |
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My pinned repositories provide a good overview, but here are three projects I'm particularly proud of that showcase my different skill sets.
🤖 AI / ML Project: [Name of Your ML Project]
- What it is: A (e.g., image classifier, NLP model, recommendation engine) that [solves what problem].
- How it works: Built with Python, TensorFlow/PyTorch, and Scikit-learn. Deployed [where/how].
- Key takeaway: This project demonstrates my ability to [mention a key ML skill, e.g., "manage data-preprocessing pipelines," "implement deep learning architectures," or "evaluate model performance"].
- Link to Repository →
🖥️ Full-Stack Project: [Name of Your Web App Project]
- What it is: A full-stack (e.g., social media, e-commerce, portfolio) application.
- How it works: Features a React frontend and a Django/Java Spring backend, with a PostgreSQL database.
- Key takeaway: This project highlights my skills in building and connecting front- and back-end services, managing state, and designing RESTful APIs.
- Link to Repository →
☁️ DevOps / Cloud Project: The Bunker Lab
- What it is: A production-grade DevOps homelab designed to mimic enterprise architecture. It decouples compute, storage, and networking to create a resilient, hybrid-cloud platform for hosting portfolio projects and AI workloads.
- How it works: Built on Proxmox VE with ZFS storage. It features a Zero-Trust network via Tailscale, Docker for service orchestration, and an automated Disaster Recovery pipeline using Terraform and Rclone to sync encrypted data to Google Cloud.
- Key takeaway: Demonstrates mastery of Hybrid Cloud Architecture, Infrastructure as Code (IaC), Virtualization, and Secure Networking principles in a production-like environment.
- Link to Repository →
I'm always open to discussing new projects, sharing ideas, or just connecting with other developers. Feel free to reach out!
