TechConnect World 2020
Co-Located with Nanotech 2020 SBIR/STTR Spring AI TechConnect
Nanotech 2020
 
 

Machine Learning for Materials Characterization and Imaging: Special Focus Session

Nanoscale Materials Characterization

Symposium Co-Chairs

Greg HaugstadGreg Haugstad
Technical Staff Member & Director, Characterization Facility (CharFac)
University of Minnesota

Dalia YablonDalia Yablon
Technical Program Chair
TechConnect World Innovation Conference

Key Speakers

Huolin XinHuolin Xin
Assistant Professor, Department of Physics and Astronomy
University of California, Irvine

Maxim A ZiatdinovMaxim A Ziatdinov
Research Scientist
Oak Ridge National Laboratory

Mary ScottMary Scott
Assistant Professor
UC Berkeley

 

The purpose of this symposium is to explore the application of machine learning to characterization with an emphasis on microscopy methods such as electron microscopy, probe microscopy, optical microscopy, and other imaging techniques. A natural point at the nexus of ML and such methods is image analysis and processing. Modern imaging systems have the further capability to generate data cubes, where the third dimension is a kind of spectral information. Thus in seeking characteristic "signatures" during data analysis one is exploring a much richer terrain, not simply looking for features or patterns in pictures. In addition to faster, "deeper", and more powerful image processing, additional issues that will be addressed include a broader role for ML improving our current capabilities and even enabling new modes and techniques.

Submit Abstract - due December 13 »

2019 Sponsors & Partners
 

2019 SBIR/STTR Agency Partners:

SBIR/STTR Agency Partners