Daniel Speckhard on Muck Rack

Daniel Speckhard

Baltimore, Washington, D.C.
As seen in: CNN, MSN, MSN Canada, HuffPost, TIME, The Hill, U.S. News and World Report, ACS Publications, Baltimore Sun, Royal Society of Chemistry and
President and CEO of @CorusIntl, parent of @LuthWorldRelief & @IMAWorldHealth. Former U.S. Ambassador to Greece and Belarus.
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Articles

Band-Gap Regression with Architecture-Optimized Message-Passing Neural Networks

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By Tim Bechtel, Daniel Speckhard, Jonathan Godwin, Claudia Draxl
| ACS Publications
Introduction Click to copy section linkSection link copied! The success of density functional theory (DFT) has allowed researchers to predict material properties outside of the laboratory. There are several materials databases, such as NOMAD (Novel Materials Discovery), (1) the Materials Project, (2) AFLOW (Automatic Flow of Materials Discovery), (3) OQMD (The Open Quantum Materials Database), (4) and others, collecting DFT data.
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How big is big data?

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By Daniel Speckhard, Humboldt-Universität zu Berlin, Luca M. Ghiringhelli, Tim Bechtel
| Royal Society of Chemistry Verified
Big data has ushered in a new wave of predictive power using machine-learning models. In this work, we assess what big means in the context of typical materials-science machine-learning problems. This concerns not only data volume, but also data quality and veracity as much as infrastructure issues.
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How big is Big Data?

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By Daniel Speckhard, Luca M. Ghiringhelli, Santiago Rigamonti, Claudia Draxl
| Royal Society of Chemistry Verified
Big data has ushered in a new wave of predictive power using machine learning models. In this work, we assess what {\it big} means in the context of typical materials-science machine-learning problems. This concerns not only data volume, but also data quality and veracity as much as infrastructure issues.
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