I'm a Computer Science student who likes working at every layer of the stack — from Rust internals to TypeScript frontends. I'm especially drawn to performance-critical systems and practical AI applications.
- Currently building rustnum — a NumPy-compatible numerical library powered by Rust
- Exploring local LLM deployment with LocalQwenModel
- Researching HPC task offloading with OFFLOAD-HPC
- Using ML to drive agricultural intelligence with AgriIntel
- I enjoy competitive programming — solved problems across HackerRank, Google Foobar, and NASCON
Languages
AI / ML
Full Stack & Tools
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NumPy-compatible Python library backed by Rust. Same familiar API — measurably faster execution through Rust's zero-cost abstractions.
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Emotion capture and recognition pipeline using deep learning. Detects and classifies human emotions from visual input in real time.
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Java framework for offloading compute-intensive workloads to high-performance computing infrastructure, reducing local execution overhead.
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Full-stack platform built to streamline entry test preparation for students. Includes separate user and admin dashboards with full CRUD.
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ML-driven agricultural intelligence system. Applies machine learning models to assist data-driven decision-making in farming contexts.
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Local deployment setup for the Qwen LLM. Runs large language models fully on-device — no cloud, no API keys, complete privacy.
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