A black and white cartoon bat, winking. Stands in for a photograph.

Tri Do

Final year CS and Statistics at Purdue. I build AI serving systems: observable, measurable, and under real hardware constraints.

I work on the layer between a model and the people who depend on it: retrieval, serving, evaluation, and the telemetry that makes all three arguable. Every system here was built against a ceiling I could not raise. A 6GB GPU picked the quantization, the reranker, and the vector store. $290 of secondhand homelab hardware picked the cluster topology. A zero dollar API budget picked the rate limiter before it picked the provider.

A fixed ceiling is also what makes the work measurable, because it turns most design questions into arithmetic. I try to answer those honestly. On the project below, a six arm retrieval ablation produced a clean set of per stage improvements, and every one of them sat under the smallest effect that run could actually detect, so I withdrew them. The numbers on this site are the ones that survived that.

I came to Purdue for statistics and added computer science in my second year, which turned out to be the whole story. I liked the math and I liked the systems, and AI is the place where those stop being two separate interests. I moved toward it later that same year and have not looked seriously at anything else since. Infrastructure came later and from somewhere else entirely, and that story is on the homelab page where it belongs.

The domain name, pure-white-ash.com, comes from volume 14 of Ashita no Joe:

That burning sense of worth and completeness is something I've only tasted on a bloodied ring. And this burning sensation isn't a momentary sputtering that other people my age might feel. It's so bright it burns your entire body up in an instant. And when it's over, only white ashes remain. Not even any tiny cinders. Only white ashes.

Ashita no Joe, Takamori Asao and Chiba Tetsuya, 1968 to 1973. Some translations render the last line as pure white ash rather than white ashes. The domain takes that reading.

Stack

Languages
Python, Java, C, SQL, Bash
ML and LLM systems
PyTorch, Hugging Face, Qdrant, QLoRA fine tuning, GGUF quantization, hybrid retrieval, LLM as judge evaluation
Backend
FastAPI, Spring Boot, REST, GraphQL, PostgreSQL, Redis, ActiveMQ, Docker, Kubernetes, AWS, Linux
Observability and CI
OpenTelemetry, Prometheus, Grafana, Jaeger, GitLab CI/CD

Muay Thai

Two years of Muay Thai and kickboxing. I came for the conditioning, stayed for the intellectual game, and keep going because I have CTE.

Literature

I read mostly Russian and French classics. It is where the project above got its name and most of what I think about outside work.

A four shelf bookcase filled with hardback and paperback classics.

Manchester United

Thirteen years a United fan. I arrived for Ferguson's last title and got the decade of despair that followed. Still counting.

Manchester United warming up at Soldier Field, seen from the upper tier.
Soldier Field, Premier League Summer Series.

Projects

  • Mitya

    A grounded question answering system over Dostoevsky, on one 6GB GPU. Hybrid retrieval, a two provider gateway, and a CI evaluation gate that withdrew several of my own findings.

  • Homelab

    Twelve self hosted services on a $290 box, reachable only through a WireGuard tunnel and mutual TLS against a private CA.

  • Other

    kurono, better-ls, better-library. Smaller things, built because the existing tool annoyed me.