Learn about the project!

Our team developed an artificial intelligence solution that easily recognizes petri dish yeast colonies, in addition to other types of assays. The product is giving researchers more time to focus on their research- rather than time-consuming biological entity counting! It also allows researchers to determine their personal threshold of confidence by controlling the AI’s recognition sensitivity. 

The research initiative also provides an opportunity for prospective students to explore various applications of artificial intelligence relevant to their research interests by joining the team!

Pytri Roadmap

November 1

AI update

The model is updated to the latest state of the art standard; incorporating faster inference time with increased accuracy.
December 1

Website live testing

Testing of website features and resource consumption.
January 1

Library Research

Research to incorporate additional libraries, such as IVF and 3D printed organ assays.
February 1

Website Launch

The website is launched for public testing, with features constantly being added and updated based on user feedback.

Special thanks to the following research groups and institutions for the provided data and funding:

– The National Institute of Chemical and Pharmacological Research of Bucharest, Romania
– Dr. Jacalyn Vogel’s lab, McGill University
– The Polar Microbiology Lab, McGill University
– Dr. Stephanie Crane Weber’s lab, McGill University
– Dr. Madoka Gray-Mitsumune’s Teaching Laboratory, Concordia University
– Dr. Sacher’s Teaching Laboratory (466), Concordia University