I like working on projects where models, data, and software systems meet.
Most of my work is focused on building practical tools around AI/ML, backend infrastructure, and scientific computing — from model evaluation pipelines and NLP systems to APIs, databases, and distributed services.
Outside of coursework, I’m especially interested in turning research ideas into usable software: systems that are not just technically interesting, but actually reliable, testable, and useful.
A DSP-based device for detecting intonation and rhythm accuracy through signal processing.
- Detects pitch and rhythm accuracy with high precision
- Designed with accessibility and usability in mind
- Published at CONF-CDS 2022
- Built for real-world use with music learning and neurodiverse users
Building practical software systems with interests in AI, backend engineering, and scientific computing.