September 26, 2017 UMD Home FabLab AIMLab
MLMR 2017
Machine Learning
for
Materials Research
Bootcamp & Workshop
2017

Organizers

A. Gilad Kusne A. Gilad Kusne National Institute of Standards & Technology Materials Measurement Science Division Gilad Kusne develops machine learning algorithms to accelerate the discovery and optimization of advanced materials as part of the Materials Genome Initiative at NIST. The algorithms integrate data analysis, materials property measurement instruments (e.g. X-ray diffractometers), and databases of experimental and computational materials property data to provide high throughput analysis of materials data. The algorithms run both offline and online during sample characterization to provide live guidance to the experimentalist and improve data collection.
Alexei Belianinov Alexei Belianinov Oak Ridge National Laboratory Center for Nanophase Materials Sciences Alexei Belianinov is a Research Staff Member at CNMS Oak Ridge National Laboratory, working on developing chemical imaging and direct-write material assembly at the nanoscale via a wide range of imaging and analytical techniques. In addition, he incorporates multivariate statistical computation methods into High Performance Computing environments, in order to process vast quantities of experimental and theoretical data and enable real-time, knowledge driven, approach to science.
Daniel Samarov Daniel Samarov National Institute of Standards and Technology Information Technology Laboratory Daniel Samarov is a mathematical statistician at NIST interested in multivariate statistics, machine learning, nonparametric statistics, sparse methods, big data applied to any and all interesting problems. His recent work has focused on hyperspectral image processing on massive multi-dimensional images applied to biomedical problems, analysis of next generation sequencing data, development of recommender systems and research on sparse coding methodology.
Tim Mueller Tim Mueller John Hopkins University Department of Materials Science & Engineering One of Tim Mueller's research interests is materials informatics. In particular, his group created a database of efficient k-point grids to reduce the cost of calculations that require integration over the Brillouin zone. Prior to joining the faculty of Johns Hopkins in 2012, Tim cofounded Pellion Technologies, a company that is leveraging computational tools to develop advanced batteries.
Ichiro Takeuchi Ichiro Takeuchi University of Maryland, College Park Department of Materials Science & Engineering Takeuchi's expertise is in the area of combinatorial synthesis and characterization of functional thin film materials. He has previously successfully used the high-throughput methodology to discover numerous materials with enhanced properties. His recent research emphasis has been on development of informatics techniques to effectively handle, visualize, and analyze the large amount of data which are generated from combinatorial experiments. More information on Takeuchi research group can be found at http://www.mse.umd.edu/faculty/takeuchi.

Conference Support

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

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