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

研讨会 2019：物理、化学和生物系统的人工智能和张量分解

• 批准号: 1936680
• 负责人: Ludmil Alexandrov
• 金额: $ 2.44万
• 依托单位: University of California-San Diego
• 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
• 起止时间: 2019-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1936680&HistoricalAwards=false
• 关键词: Workshop; 2019; AI; Tensor; Factorization

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.

研讨会2019年：“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。其中一个主要主题是讨论为缩小当前最先进的方法与正在出现的极大的异质数据集之间的差距所需的努力。研讨会将增进我们对可解释和强大的人工智能(AI)和针对科学发现的大数据分析方法的知识。多学科参与者之间的讨论将有助于确定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，以应对最近世界上爆炸性的数据增长。让青年科学家参加讲习班将为讨论带来新的视角，并通过互动和建立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教育转型的想法；政府、学术界和行业之间的合作机会；以及可解释人工智能和大数据分析技术应用中的数学活动的协同效应。研讨会将集中于两个主题：回顾人工智能的数学和算法进步，重点是张量因式分解方法；以及定义和展示这些进步在各种物理、化学和生物系统的广泛应用中的力量。它将提供一个论坛，传播关于无监督机器学习和人工智能的现代方法的信息和分享想法，重点是张量因式分解方法及其在自然科学中的应用。研讨会将有助于定义重要的主题，并确定研究方向和机会，这些研究方向和机会可能会启动可解释人工智能和大数据分析的新发展。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。