March 4, 2024 UMD Home FabLab AIMLab
MLMR 2023
8th Annual
Machine Learning for Materials Research Bootcamp
August 7-11, 2023



MLMR 2023 dates are announced!

August 7-11, 2023 (hybrid mode)
Please register at
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MLMR 2023 will be hybrid this year from August 7-11. If you have any questions, or would like to join the mailing list to find out the final dates, please contact:

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Bootcamp (Days 1-4)

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:

  • Identifying important features in complex/high dimensional data
  • Visualizing high dimensional data to facilitate user analysis.
  • Identifying the 'descriptors' that best predict variance in functional properties.
  • Quantifying similarities between materials using complex/high dimensional data
  • Identifying the most informative experiment to perform next.

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.

Workshop (Day 5)

Topic: TBD

Past attendees map



A. Gilad Kusne A. Gilad Kusne National Institute of Standards & Technology Materials Measurement Science Division
Alexei Belianinov Alexei Belianinov Sandia National Laboratories Ion Beam Laboratory
Daniel Samarov Daniel Samarov National Institute of Standards and Technology Information Technology Laboratory
Ichiro Takeuchi Ichiro Takeuchi University of Maryland, College Park Department of Materials Science & Engineering

Colleges A. James Clark School of Engineering
The College of Computer, Mathematical, and Natural Sciences

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