Join researchers and students from around the world for a three-day hybrid hackathon exploring how AI and machine learning can advance microscopy, materials imaging, spectroscopy, and scientific workflows.

Primarily focused on electron microscopy (SEM S/TEM, and related techniques). Projects in SPM (i.e., AFM and STM), hyperspectral imaging, and other microscopy and spectroscopy techniques are also welcome.

WHO CAN PARTICIPATE?

Everyone is welcome — undergraduate and graduate students, postdocs, faculty, researchers, and industry participants. You do not need to be an AI expert. Teams are encouraged to combine microscopy/materials domain knowledge with AI/ML and coding skills.

PROJECT TOPICS

•1. Image and Hyperspectral Image Analysis

•2. New Problems for Real-world Materials Imaging and Spectroscopy

•3. Creating Instructional Tutorials

•4. Active Learning and Real-time Analysis

•5. Simulators for Active Learning

•6. From Microscopy to ML and Back

•7. Grand Challenge Problems

•8. General

HOW IT WORKS

• Hackathon problems will be released one day before the event

• Participants may form local or global interdisciplinary teams

• Teams typically focus on one challenge

• Most projects can be developed using accessible cloud resources such as Google Colab

• Scientific relevance, creativity, domain understanding, robustness, and practical impact matter — not just coding performance

• Examples of projects submitted during the 2025 Hackathon can be found here: Hackathon 2025

Coffee, refreshments, and lunch will be provided.

Local Host/Contact: Mengkun Tian

No registration fee