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AI for Accelerated Materials Design (AI4Mat)
Santiago Miret · Marta Skreta · Zamyla Morgan-Chan · Benjamin Sanchez-Lengeling · Shyue Ping Ong · Alan Aspuru-Guzik

Fri Dec 02 06:00 AM -- 03:00 PM (PST) @ Room 386
Event URL: https://sites.google.com/view/ai4mat »

Self-Driving Materials Laboratories have greatly advanced the automation of material design and discovery. They require the integration of diverse fields and consist of three primary components, which intersect with many AI-related research topics:

- AI-Guided Design. This component intersects heavily with algorithmic research at NeurIPS, including (but not limited to) various topic areas such as: Reinforcement Learning and data-driven modeling of physical phenomena using Neural Networks (e.g. Graph Neural Networks and Machine Learning For Physics).

- Automated Chemical Synthesis. This component intersects significantly with robotics research represented at NeurIPS, and includes several parts of real-world robotic systems such as: managing control systems (e.g. Reinforcement Learning) and different sensor modalities (e.g. Computer Vision), as well as predictive models for various phenomena (e.g. Data-Based Prediction of Chemical Reactions).

- Automated Material Characterization. This component intersects heavily with a diverse set of supervised learning techniques that are well-represented at NeurIPS such as: computer vision for microscopy images and automated machine learning based analysis of data generated from different kinds of instruments (e.g. X-Ray based diffraction data for determining material structure).

Author Information

Santiago Miret (Intel AI Lab)
Marta Skreta (University of Toronto)
Zamyla Morgan-Chan
Benjamin Sanchez-Lengeling (Google Research)
Shyue Ping Ong (University of California-San Diego)

Prof Shyue Ping Ong is a Professor of NanoEngineering at the University of California, San Diego. He obtained his PhD from the Massachusetts Institute of Technology in 2011. He leads the Materials Virtual Lab at UCSD, a dynamic group of materials scientists focusing on the interdisciplinary application of materials science, computer science, and data science to accelerate materials design. He is one of the founding developers of the Materials Project, a DOE-funded initiative to make the computed properties of all known materials publicly available for materials innovation. He is also the founder of Python Materials Genomics (pymatgen), an open-source materials analysis library that is used by hundreds of thousands of users worldwide. At UCSD, Dr Ong has served in the NanoEngineering Department’s Graduate Affairs Committee, Undergraduate Affairs Committee, as well as leads the Alumni Newsletter Committee. Dr Ong is also a recipient of the US Department of Energy Early Career Research Program and the Office of Naval Research Young Investigator Program awards.

Alan Aspuru-Guzik (University of Toronto)

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