Projects
A collection of my work spanning iOS development, web applications, open-source tools, and research projects.
All Projects
DubDubSings
Make Siri sing your favorite song!
Initially introduced as SiriSings for my WWDC23 Swift Student Challenge Submission, DubDubSings serves as an interactive platform for aspiring songwriters. It utilizes Apple's AVSpeechSynthesizer to convert text into spoken words and bring musical ideas to life with expressive audio controls.
- WWDC23 Swift Student Challenge Submission
- Featured on WWDC Scholars
- Published on App Store
A macOS lightweight status bar media visualizer that integrates directly into the macOS status bar. MusicBar provides instant visual feedback on the current media without disrupting your workflow, featuring real-time audio visualization and seamless integration with Apple Music and Spotify.
- Built with SwiftUI for native macOS integration
- Real-time audio visualization
- Supports Apple Music and Spotify
mixr
Lightweight Virtual Mixer
My WWDC22 Swift Student Challenge Submission - a lightweight virtual mixer designed for everyone from beginners to mix engineers. It allows for referencing music on specific Apple devices and provides individual control over each track or instrument in a song.
- WWDC22 Swift Student Challenge Submission
- Featured in App Store Story
- Individual track/instrument control
Optimizing Large Language Model training through scaling techniques. This project explores weak and strong scaling in LLM training using DeepSpeed, Flash Attention 2, and LoRA. We assessed multi-node efficiency, memory usage, and runtime optimization using NCCL configurations, developing custom tools for performance monitoring, fine-tuning automation, and visualization.
- Showcased at AI Thailand Forum 2024
- Multi-GPU training optimization
- Custom performance monitoring tools
A simple multinode performance logger for Python, designed to be used similarly to Python's built-in logging module but with a focus on performance logging. It provides a simple API for logging performance data including start and end times, and allows for easy integration with other logging systems.
- Published on PyPI for easy installation
- Simple API similar to Python's logging module
- Designed for HPC environments with Slurm