Hi, I'm Evint
Researcher at UBC by day, co-founder of Kolosal AI by night. I teach machines to decode biology — from circular RNA to tumor suppressor genes — and occasionally, the stock market.
Open-source tools for running large language models locally — private, fast, and fully under your control. Custom training and production-ready inference.
Visit Platform ↗Published ANN pipeline that classifies circRNA-disease associations with Gaussian blur preprocessing — 75% accuracy at 0.14ms per prediction.
Read Paper →Production-grade inference with TensorRT integration — optimized for low-latency model serving at scale.
GitHub ↗Undergraduate Researcher
Building deep learning pipelines for circular RNA classification and genomic sequence analysis.
Co-Founder
Architecting open-source tools for local LLM deployment, inference optimization, and MLOps automation.
First Author
"Deep Learning Algorithm with Gaussian Blur Data Pre-processing in Circular RNA Classification"
I chase problems where data hides something meaningful — a motif buried in RNA sequences, a leading signal in financial time series, or a chance to make ML infrastructure less painful.
Currently an undergraduate researcher at UBC building deep learning systems for genomic data, and co-founding Kolosal AI to make running LLMs locally actually simple. My first-author publication on circular RNA classification is live in URNCST Journal.
When I'm not debugging loss curves, I'm reading about macroeconomics or exploring Vancouver's trails.