Learn about the project!

The project involves developing Convolutional Neural Networks (CNNs) using novel architectures in detecting cell colonies on petri dishes. This is followed by a comparative study of accuracy, and the inference of morphological features of various species using deep learning. The detection network will then be uploaded to a remote server, where researchers can upload images of their colonies, either using their phone, or using the Pytri prototype.

The research initiative also provides an opportunity for prospective students to explore various applications of artificial intelligence relevant to their research interests. In addition to seminars and workshops to be held throughout the 2020-2021 academic year.

Pytri Roadmap

2021
February 19

3D Model

The 3D model of the prototype is complete and ready for printing.
March 1

AWS Deployment

Deployment of our live service for preliminary testing on AWS.
March 19

Machine Learning Seminars

The seminars will be organized in collaboration with Concordia’s Arts and Science Federation of Associations (ASFA), and will be open to all students and faculty, showcasing the project and exposing students to machine learning.
July 1

Project Launch

The project is launched, with the first Pytri prototype being rolled out to its trial laboratory for live-testing by researchers.

Acknowledgements

Full funding for the project was provided by Concordia University’s Experiential Learning, ASFA, CSU, the Loyola Committee and the Dean’s Office with special thanks to the following research groups and institutions for the provided data:

– 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