Hi there!
I'm Mia, a software/ML engineer and music technologist
Get in touch xuening.wang2002@outlook.com
Hi! I'm Mia (Xuening / 雪宁), an engineer and musician. I blend coding with creativity to build cool stuff and make music with AI 🎵.
Currently exploring the intersection of tech and creativity at Cornell Tech, I'm passionate about designing AI-powered solutions that have real-world impact. My background blends full-stack development, machine learning, and music technology, and I'm driven to create innovative products that bring together my skills and passions. When I'm not coding, you'll find me playing piano, drinking coffee, or wandering through random record shops in NYC 🎧 🚶♀️.
- Python
- JavaScript
- TypeScript
- SQL
- C++
- Java
- PHP
- C#
- Bash
- HTML
- CSS
- MATLAB
- Max/MSP
- PyTorch
- TensorFlow
- Scikit-learn
- Keras
- Pandas
- Apache Spark
- MySQL
- PostgreSQL
- NoSQL
- GraphQL
- SQLite
- SQLAlchemy
- Redis
- React.js
- Next.js
- Node.js
- Express.js
- JQuery
- Spring Boot
- Flask
- Django
- Three.js
- Plotly.js
- D3.js
- Bokeh
- Docker
- Git
- AWS
- GCP
- Bash
- AliCloud
- Firebase
- Supabase
- Vercel
- Render
- Postman
- ActiveMQ
An AI-powered Ableton Live plugin designed for splitting stems for production, with a full machine learning inference pipeline on AWS. Built with my amazing team at Tona.ai.
A Next.js app that analyzes poems and generates music videos with voice narration, leveraging OpenAI, MusicGen, and Replicate APIs for media generation.
A Next.js music streaming app built for learning Next.js. It calls the Spotify API and allows users to create, manage, and explore playlists. Built with my amazing friend at Cornell Tech.
A machine learning project focused on predicting song skips on Spotify, using algorithms like Gradient Boosted Trees, LSTM, and Transformers.
My undergrad final year project where I built a system to compose full songs by controlling everything from individual bars to entire sections. It combines advanced music theory with deep generative models, using a symbolic Chinese pop music dataset to bring it to life.
A 3D tool for digital fabrication. Designed to optimize digital fabrication workflows. Built with my amazing friends at Cornell Tech.
A hackathon project - an AI-powered personal baseball swing coach that provides personalized analysis for players. Built with my amazing friends at Cornell Tech.
A web-based e-commerce management system, facilitating the handling of products, categories, orders, coupons, addresses, and users.
An enhanced image steganography solution utilizing LSB (Least Significant Bit) technique, AES encryption, and a unique Pixel-location Image Password mechanism.
A university social media platform enabling students to post, engage with content, and customize profiles, with an admin system for database CRUD operations.
Computer Composition Identification Challenge (CCIC) dedicated to finding improved music generation models and objective evaluation models for a number of music styles, initiated by the Conference on Sound and Music Technology (CSMT) 2021. I was the coordinator of the data challenge. Website available here!