Mike Cichonski

Mike designs and builds the software infrastructure that helps researchers find, access, and analyse large astronomical datasets, with a particular focus on making data and tools from different surveys easier to work with together. He joined CanDIAPL in August 2025 after six years at the University of Toronto's Creative Destruction Lab, where he worked in data analysis and software engineering. Before that, his background was in cognitive science and research software development — a combination of experience that CanDIAPL gave him the chance to bring into astronomy, contributing to the foundations of a large scientific project.

 

What excites Mike most about the work is what becomes possible when researchers can bring together datasets that would otherwise be difficult to connect. Different surveys offer different views of the sky, but combining those observations often takes considerable work before the scientific analysis can even begin. Through Dynamic Datasets, Mike and his colleagues are making that process easier and more consistent, at scales where downloading everything to a personal computer simply isn't practical — building infrastructure that could one day support discoveries and research questions no one has thought to ask yet.

 

A typical week for Mike moves between designing systems, writing and reviewing code, and talking through requirements with researchers and developers across CanDIAPL, the Canadian Astronomy Data Centre, and the broader international astronomy community. That might mean organizing survey data so it can be searched efficiently, developing an automated processing workflow, or making it easier for colleagues to run their software on shared computing infrastructure — including COMET, a tool he has been developing to simplify deploying code to the Canadian Advanced Network for Astronomical Research. His favourite part of the job is the moment a conversation about a research problem turns into a clear idea for something the team can build, and the satisfaction of turning a one-off process into a standardized workflow that benefits a much wider range of users.

 

Outside of astronomy, Mike's background in cognitive science — including research in EEG, neurolinguistics, and visual imagination — reflects a broader pull toward interdisciplinary work, where a method familiar in one field can offer a fresh approach in another. He also runs a small solo software-as-a-service venture, building applications that often grow out of his interests in music and visual art.

 

Outside of work, he enjoys travelling, gardening, cooking, and baking, along with an ongoing string of creative projects spanning software, music, and visual art — from experimenting with unusual rhythms and tuning systems to building procedurally generated worlds for games.

 

Mike's advice for anyone starting out in the field: build something you're curious about, even before you know everything you'll need to finish it, and take the time to understand the scientific question and talk to the people who will use what you're building. He also encourages a thoughtful approach to AI — useful as a tool, but no substitute for understanding how something works, slowing down, and continuing to learn.