About

Professional introduction and public links for Igor Kuvychko.

This site is where I publish the parts of my work that are public-safe and worth a durable, readable home: technical essays, mathematical notes, papers and their supporting information, interactive educational artifacts, public projects, and selected 3D-printed designs. The work itself is industrial: analytics, machine learning, AI, optimization, and simulation, aimed at making factories run better — especially semiconductor fabs.

Some ideas only become clear when you can step through them, so many of the pages here are interactive. They are built to work offline and to remain archivable — an idea should stay accessible long after the link that pointed you to it.

Background

I am a principal data scientist at INFICON. The work spans analytics and data pipelines, classic machine learning, emerging AI / agentic applications, and operations-research optimization and scheduling, all of it for semiconductor manufacturing. I came to it the long way: I spent roughly a decade inside the industry I now model. At Intel’s lead development site in Hillsboro, Oregon, where new process technologies are developed and ramped to high-volume manufacturing, I worked as a process engineer on ALD/CVD deposition tools, then as an analytical and environmental engineer, starting a testing program that later spread to other manufacturing sites. That decade on the factory floor — its queues, tool availability, recipes, setups, holds, and operational policies — is the domain knowledge that keeps the schedulers, simulators, and models I build today close to how a factory actually behaves.

Before semiconductors I was a research chemist: a PhD and years of laboratory work in fullerene and fluoroorganic chemistry, with 49 peer-reviewed journal articles, plus book chapters and patents to show for it. I left the laboratory in 2013; the habits of careful measurement and mechanistic explanation came along.

Elsewhere

What you’ll find here

  • Essays — forthcoming: technical essays and notes.
  • Papers — formal publications, preprints, and supporting resources.
  • Explainers — educational HTML artifacts and visual explainers.
  • Projects — selected public projects.
  • Objects — 3D-printed mathematical objects and practical designs.

This site is a curated hub, not a complete archive or a social feed. If you’re looking for something you can’t find here, the GitHub profile is the best next stop.

This is a personal site; the views and materials here are my own and do not represent my employer.