Workshop 2019: AI and Tensor Factorization for Physical, Chemical, and Biological Systems
Workshop 2019: AI and Tensor Factorization for Physical, Chemical, and Biological Systems
批准号:
1936680
负责人:
Ludmil Alexandrov
金额:
$2.44万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2020-08-31
中文摘要
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英文摘要
The Workshop 2019: "AI and Tensor Factorization for physical, chemical, and biological systems" will take place between September 17 and September 20, 2019 in Santa Fe, New Mexico. One of the main themes is discussion of the efforts that are needed to close the gap between current state-of-the-art methods and the emerging extremely large heterogenous data sets. The workshop will advance our knowledge of explainable and robust Artificial Intelligence (AI) and Big-Data Analytics methods targeting scientific discoveries. The discussions among the multi-disciplinary participants will help to define the challenges and questions arising because of the recent explosive growth in AI and Machine Learning (ML) technologies and their Big-Data applications. The discussions amongst the multi-disciplinary participants from around the world will help to disseminate and define the challenges in the AI field and determine the questions and directions that need to be explored to tackle the recent explosive growth of data in the world. Inclusion of young scientists in the workshop will bring fresh perspective to the discussions and foster their career development through interactions and networking. Specific major outcomes of the workshop will include the increased awareness of research, education, and technology transfer related to the explainable AI and Big-Data Analytics; ideas enabling the transformation of research and STEM education; partnership opportunities among government, academia, and industry; and synergism for mathematical activities in the applications of explainable AI and Big-Data Analytics technologies.The workshop will focus on two themes: reviewing the mathematical and algorithmic advancements in AI with accent on Tensor Factorization methods; and defining and demonstrating the power of these advancements in a broad range of applications in various physical, chemical, and biological systems. It will provide a forum for propagating information and sharing ideas about the modern methods of unsupervised Machine Learning and Artificial Intelligence with accent on Tensor Factorization methods and their applications in the natural sciences. The workshop will contribute toward defining important topics and identifying research directions and opportunities that potentially can initiate new developments in the explainable AI and Big-Data Analytics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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