About the Hackathon
Our Mission
The Machine Learning for Microscopy Hackathon accelerates the use of AI in microscopy and materials research. By connecting microscopy and machine-learning communities, we foster collaboration, open science, and reproducible workflows for imaging, spectroscopy, and automated experimentation.
Hackathon History
The first edition took place at the University of Tennessee, Knoxville, in 2024, with 250+ registrants and 80+ active participants from around the world. Building on that success, the 2025 edition expands into a multi-site hybrid event, enabling real-time collaboration across universities and research centers.
Core Organizing Team
How It Works
| Element | What to expect |
|---|---|
| Teams | Interdisciplinary groups mixing microscopy and ML backgrounds; remote and on-site collaboration. |
| Data & Tasks | Real microscopy datasets and challenges spanning imaging, spectroscopy, and automation. |
| Mentorship | Guidance from domain experts and tool builders; cross-site office hours and Slack support. |
| Outcomes | Working prototypes, analysis notebooks, and open-source contributions that persist post-event. |
Partners & Support
The hackathon is supported by the AI Tennessee Initiative and the Center for Advanced Materials & Manufacturing (CAMM), with participation from University of Tennessee Knoxville, North Carolina State University, Northwestern University, University of Illinois Chicago, ICN2-ALBA Synchrotron Barcelona, University of Toronto, University of Wisconsin–Madison, University of Colorado Boulder, Colorado School of Mines, Indian Institute of Technology Delhi, Thermo Fisher Scientific (Eindhoven), AISCIA Informatics (Doha, Qatar), Pennsylvania State University, University of Pennsylvania, University of Michigan Ann Arbor, Sungkyunkwan University (SKKU), Nanyang Technological University Singapore, and Texas A&M University.
Sponsors
Our primary sponsors provide critical support for enabling open, collaborative AI-driven microscopy:
Partners
Our partners empower open science and innovation in AI for materials research:
Get Involved
Connect on Slack, meet collaborators, and find a team.
Register for the hackathon and choose your preferred site (or Online).