IFLAI at ETH Zurich: Advanced Machine Learning for Microscopy

From October 5th to 7th, 2022, members of the IFLAI team had the distinct privilege of traveling to Switzerland to kick off the Advanced Machine Learning Techniques applied to Microscopy Data Analysis course at the MaP Doctoral School, ETH Zurich.

The intensive 3-day block course was led by Prof. Giovanni Volpe (head of the Soft Matter Lab at the University of Gothenburg and IFLAI co-founder), alongside IFLAI's CTO Henrik Klein Moberg and Jesús Pineda acting as teaching assistants.

Bridging AI and Microscopy

Over fifteen doctoral students and post-docs attended the first session, which laid the foundational groundwork for applying modern AI to complex, noisy scientific data. Topics covered during this initial block included:

• Deep Learning and Dense Neural Networks
• Recurrent Neural Networks and Transformers
• Convolutional Neural Networks

A highlight of the course was the interactive element: each student introduced a specific, real-world research problem from their own lab that they intend to solve using the techniques learned in the course. The dedication and immediate practical application from the students were incredibly inspiring.

Looking Forward

We were extremely satisfied with the students' work and dedication during the October session, and we are eagerly looking forward to returning to Zurich for the upcoming November and December course blocks to see how their machine learning models develop.

By empowering researchers with data-efficient, physics-informed AI tools, we can accelerate discoveries across the entire field of microscopy.

Read the original coverage on the ETH Zurich MaP Doctoral School News Channel.