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Nyasa139/README.md

Hi 👋, I'm Nyasa

I enjoy building practical full-stack applications and understanding how systems work internally.


✨ About Me

🎓 CS student passionate about problem-solving and building real-world projects
🧠 Interested in Web Development, AI/ML, Cloud, and System Design
⚙️ Enjoy creating end-to-end applications with clean architecture
🚀 Love learning by building hands-on projects and understanding systems internally
🔍 Exploring AI, GenAI, scalable backend systems, and intelligent automation
📄 Presented research work on MST-Conformer, a compact Conformer-based architecture for Human Activity Recognition (HAR), at ISCADS 2026, MIT Bengaluru
🤖 Interested in Edge AI, wearable sensor intelligence, uncertainty estimation, and real-time AI systems
🧩 I value clean code, practical architectures, and building things end-to-end


⚙️ Tech Stack

Languages

Java Python JavaScript SQL


Frontend

React Vite TailwindCSS HTML5 CSS3


Backend

NodeJS Supabase FastAPI


Databases

PostgreSQL Oracle


AI / ML

NumPy Pandas ScikitLearn PyTorch


Tools & Platforms

Git GitHub Vercel VSCode


🚀 Featured Projects

🎵 Melody — Music Streaming App

Spotify-inspired music streaming platform built using React, Supabase, and APIs with centralized audio state management, playlists, and podcast integration.

🔗 Live Demo: https://melody-music-app-chi.vercel.app/


☁️ Cloud Drive

Cloud-based file management application with authentication, uploads, trash recovery, and storage handling using Supabase.

🔗 Live Demo: https://cloud-drive-snowy.vercel.app/login


🧠 MST-Conformer — HAR Research

Proposed a compact Conformer-based architecture for Human Activity Recognition using wearable sensor data with:

  • Multi-scale temporal convolutions
  • Deep Layer Aggregation
  • Dual Conformer attention blocks
  • Monte-Carlo Dropout uncertainty estimation

Presented at ISCADS 2026 at MIT Bengaluru.


🤝 Connect With Me

LinkedIn

GitHub


💭 Quote

Code, curiosity, and consistency.

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