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𝗧𝗜𝗚𝗡𝗜𝗦 𝗖𝗥𝗘𝗔𝗧𝗘𝗦 𝗜𝗡𝗡𝗢𝗩𝗔𝗧𝗜𝗢𝗡𝗦 𝗧𝗢 𝗢𝗩𝗘𝗥𝗖𝗢𝗠𝗘 𝗔𝗜 & 𝗔𝗨𝗧𝗢𝗠𝗔𝗧𝗜𝗢𝗡 𝗢𝗕𝗦𝗧𝗔𝗖𝗟𝗘𝗦 𝗜𝗡 𝗧𝗛𝗘 𝗣𝗟𝗔𝗡𝗧
We have a goal of making plants more reliable, efficient, and autonomous.
Our team combines physics, mechanical, chemical, electrical, and petroleum engineers with world class software and AI experts.
Our approach is to combine the best of physics/engineering understanding with the latest in data driven machine learning.
Our solutions are not incremental, they are wildly new and innovative, such as:
A new analytics language for the digital twin - the Digital Twin Query Language.
A digital twin accelerator that takes complex physical simulations and makes them 10000x faster.
A multi-variable closed-loop controller leveraging AI/ML that continuously learns and improves with operation.
研究兴趣
论文共 53 篇作者统计合作学者相似作者
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mag(2009)
引用32浏览0引用
32
0
International Journal of Human-Computer Studiesno. 8 (2009): 639-662
mag(2008)
引用103浏览0引用
103
0
mag(2007)
引用35浏览0引用
35
0
mag(2007)
引用38浏览0引用
38
0
Designing and understanding information retrieval systems using collaborative filtering in an academic library environment (2007)
引用23浏览0EI引用
23
0
Information Processing and Management: an International Journalno. 3 (2007): 791-807
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