• Workshop: Artificial Intelligence for Materials Science (AIMS)

    August 7 - 8, 2018

  • The Materials Genome Initiative (MGI) promises to expedite materials discovery through high-through computation and high-throughput experiments. While the MGI effort has been successful to screen interesting materials among thousands of materials, the possible materials can span up to 10100 limiting the current MGI philosophy.

    One of the possible approaches to deal with this problem is using artificial-intelligence (AI) tools such as machine-learning, deep-learning and various optimization techniques to efficiently evaluate materials performance. Although AI has been very successful in fields such as voice-recognition, self-driving cars, language translation etc., its applicability to materials design is still in its developing phase. Two key challenges in employing AI techniques to materials are: choosing effective descriptors for materials and choosing algorithm/work-flow during AI design. The idea of including physics-based models in the AI framework is also fascinating. Lastly, uncertainty quantification in AI based predictions for material properties and issues related to building infrastructure for disseminating AI knowledge are of immense importance for making AI based investigation of materials successful. This workshop is intended to cover all the above-mentioned challenges. To make the workshop as effective as possible we plan to mainly focus on inorganic solid-state materials, but are not limited by it.

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    • bookmark_borderApplication of classification/regression techniques
      Short description.
    • bookmark_borderApplication of physics-based constraints
      Short description.
    • bookmark_borderSelection and importance of features/descriptors
      Short description.
    • bookmark_borderComparison metrics of AI techniques
      Short description.
    • bookmark_borderChallenges applying AI to materials
      Short description.
    • bookmark_borderDataset and tools for employing AI
      Short description.
    • bookmark_borderIntegrating experiments with AI techniques
      Short description.
    • bookmark_borderUsing AI to develop classical force-fields
      Short description.


  • user bg
    visibility Kamal Choudhary

    perm_identity Role

    email kamal.choudhary@nist.gov

    Kamal Choudhary close

    Dr. Choudhary is ...

    perm_identity Material Scientist

    business NIST

    location_on Gaithersburg, Maryland

    user bg
    visibility Francesca Tavazza

    perm_identity Role

    email francesca.tavazza@nist.gov

    Francesca Tavazza close

    Dr. Tavazza is ...

    perm_identity Material Scientist

    business NIST

    location_on Gaithersburg, Maryland

    user bg
    visibility Carelyn Campbell

    perm_identity Role

    email carelyn.campbell@nist.gov

    Carelyn Campbell close

    Dr. Campbell is ...

    perm_identity Material Scientist

    business NIST

    location_on Gaithersburg, Maryland

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