SciPy 2024

Joshua Taillon

Dr. Joshua Taillon is a staff scientist within the NIST Office of Data and Informatics, working in the Data Science group as a Materials Research Engineer. Drawing on his extensive background in materials characterization, his professional interests lie at the intersection of materials characterization and data science, utilizing machine learning, artificial intelligence, and state-of-the art signal/data processing techniques to facilitate greater understanding of material systems.

Prior to this appointment, Josh was an NRC Postdoctoral Associate in NIST's Microscopy and Microanalysis Research Group. During this time, his research included the development and application of novel data acquisition and processing schemes in both electron and ion-beam microscopy. He received a B.S. from Cornell University, and as an NSF Graduate Research Fellow, received his Ph.D. in Materials Science and Engineering from the University of Maryland where he specialized in analytical transmission electron microscopy and focused ion beam nanotomography.

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Sessions

07-11
15:00
30min
HyperSpy – Your Multidimensional Data Analysis Toolbox
Joshua Taillon

HyperSpy is a community-developed open-source library providing a
framework to facilitate interactive and reproducible analyses of
multidimensional datasets. Born out of the electron microscopy
scientific community and building on the extensive scientific Python
environment, HyperSpy provides tools to efficiently explore, manipulate,
and visualize complex datasets of arbitrary dimensionality, including
those larger than a system's memory. After 14 years of development,
HyperSpy recently celebrated its 2.0 version release. This presentation
will (re)introduce HyperSpy's features and community, with a focus on
recent efforts paring the library into a domain-agnostic core and a
robust ecosystem of extensions providing specific scientific
functionality.

Data Visualization and Image Processing
Room 316