Registration is Open!
MLMR 2025 dates are announced!
August 4-8, 2025 (hybrid)
For questions or to request an academic or student discount: mlmr@umd.edu
Four days of lectures and hands-on exercises covering a range of data analysis topics from introduction to python and data pre-processing to advanced machine learning analysis techniques. Example topics include:
Hands-on exercises will include practical use of machine learning tools on real materials experimental data (scalar values, spectra, micrographs, etc.)
Scientists will also demonstrate how they performed recently published research, from loading and preprocessing data to analyzing and visualizing results, all in Jupyter notebooks. Day 4 will include hand-on exercises on how to use the AFLOW database online.
Topic: Latest development in Autonomous Materials Science
Baltimore Washington International Airport (closest to College Park)
Please book your hotel room on your own (there are no block room arrangements). The suggested nights for the camp are Aug. 3 (Sunday) – Aug. 8 (Friday, 5 nights departing Friday afternoon)
Nearby hotels in walking distance (we recommend you book early, so you get the good rate): 10 min walk to the Kim Engineering Building (campus map) on campus where the camp will be held.
The Hotel ~$180/night
Cambria Hotel ~$170/night
Best Western Plus ~$125/night
There are several visitor parking lots, the closest one to the Workshop site (Kim Engineering Building) is the Regents Drive Garage. There is more info here: https://transportation.umd.edu/parking/visitors
If you are a student (graduate, undergraduate, or high school), write to us first at MLMR@umd.edu, so we can send you a student discount code BEFORE you register. Write to us also for an academic discount code if you work at an academic institution (university, etc.) BEFORE you register.
The course registration will include all the course material (presentations slides in pdf files, jupyter notebook links, and recorded zoom lectures of the entire camp). As the camp start date approaches, we will be posting starting course material on the canvas website.