Workshop 2019: AI and Tensor Factorization for Physical, Chemical, and Biological Systems

2019年研讨会：“物理、化学和生物系统的人工智能和张量分解”将于2019年9月17日至9月20日在新墨西哥州圣达菲举行。其中一个主题是讨论如何缩小当前最先进的方法与新兴的超大异构数据集之间的差距。该研讨会将促进我们对可解释和强大的人工智能（AI）以及针对科学发现的大数据分析方法的了解。多学科参与者之间的讨论将有助于定义由于最近人工智能和机器学习（ML）技术及其大数据应用的爆炸性增长而产生的挑战和问题。来自世界各地的多学科参与者之间的讨论将有助于传播和定义人工智能领域的挑战，并确定需要探索的问题和方向，以应对最近世界上数据的爆炸式增长。将年轻科学家纳入研讨会将为讨论带来新的视角，并通过互动和网络促进他们的职业发展。研讨会的具体主要成果将包括提高对与可解释的人工智能和大数据分析相关的研究、教育和技术转让的认识；促进研究和STEM教育转变的理念；政府、学术界和工业界之间的合作机会；以及可解释的人工智能和大数据分析技术应用中数学活动的协同作用。研讨会将集中在两个主题上：回顾人工智能的数学和算法进展，重点是张量分解方法；并在各种物理、化学和生物系统的广泛应用中定义和展示这些进步的力量。它将为传播信息和分享关于无监督机器学习和人工智能的现代方法的想法提供一个论坛，重点是张量分解方法及其在自然科学中的应用。研讨会将有助于确定重要主题，确定研究方向和机会，这些方向和机会可能会启动可解释的人工智能和大数据分析的新发展。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.