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5th Artificial Intelligence for Materials Scienc ... (No replies)

wines1
3 weeks ago
wines1 3 weeks ago

5th Artificial Intelligence for Materials Science (in-person), July 17-18, 2024, NIST, MD, USA

As a part of the JARVIS workshop series, NIST is sponsoring the 5th Artificial Intelligence for Materials Science (AIMS) workshopThe workshop will be held in-person only at the National Cybersecurity Center of Excellence (NCCoE), located at 9700 Great Seneca Highway, Rockville, MD 20850, from July 17 - 18, 2024. 

The Materials Genome Initiative (MGI) and the U.S. CHIPS Act both promise to expedite materials discovery through high-throughput computation and high-throughput experiments. The application of artificial-intelligence (AI) tools such as machine-learningdeep-learning and various optimization techniques is critical to achieving such a goal.

Some of the key research areas for materials AI include: developing well-curated and diverse datasets, choosing effective representations for materials, inverse materials design, integrating autonomous experiments and theory, merging physics-based models with AI models, and choosing appropriate algorithms/work-flows. 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 materials investigation successful. This workshop is intended to cover all the above-mentioned challenges. To make the workshop as effective as possible we plan to largely but not exclusively focus on inorganic solid-state materials.
 

Topics addressed in this workshop will include (but not be limited to):

1)  Datasets and tools for employing AI for materials

2) Integrating experiments with AI techniques

3) Graph neural networks for materials

4) Comparison of AI techniques for materials

5) Challenges of applying AI to materials

6) Uncertainty quantification and building trust in AI predictions

7)  Generative modeling

8) Using AI to develop classical force-fields

9) Natural language processing/Large language models

 

Registration will be required to attend to cover the cost of lunch and AM break for each day ($120 for regular attendees, $60 for students. Please contact [email protected] for student promo code).

If registered participants are interested in presenting a poster, please send name, affiliation, title and abstract to [email protected], no later than 5/31/2024.

We are looking forward to seeing you in Maryland, USA.

The organizing committee (Daniel Wines, Kamal Choudhary, Kevin Garrity, Austin McDannald, Brian DeCost, Howie Joress and Francesca Tavazza).

Workshop Registration link: https://www.nist.gov/news-events/events/2024-artificial-intelligence-materials-science-aims-workshop




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Ab initio (from electronic structure) calculation of complex processes in materials