Conference: NSF Meta-Workshop on AI to Accelerate Scientific and Engineering Discovery (AI2ASED)

近年来，人工智能(AI)、机器学习(ML)和数据科学的基础研究吸引了人们难以置信的兴趣。一些研究的重点是使用这些数据驱动的方法来加强其他学科的科学和工程发现。虽然世界各地都举办了研讨会和会议，讨论尖端突破和新出现的趋势，但大多数活动都是为孤立的科学领域安排的。通过整合这些事件中的重要发现(即，元研讨会)来开发令人信服的新颖见解，一场改变范式的科学革命可能成为可能。该项目支持一个关于人工智能的元研讨会，以加速科学和工程发现。讲习班将向科学界提供关于人工智能、机器学习和科学和工程领域其他数据分析方法的补充研究状况的信息。感兴趣的主题包括确定具有高潜力的特定主题领域，以数据驱动的方法来发现。这个元研讨会将聚集人工智能、最大限度地、数据科学和科学与工程(例如，生物、生物工程、化学、化学工程、物理、材料科学等)的领导人。大多数与会者将是最近围绕数据密集型发现核心的研讨会和会议的核心组织者。他们将包括他们活动中最重要的发现，并与其他参与者合作，产生新的见解。元研讨会的最终目标是与不同学科的领导人合作，制定一个连贯和影响深远的研究计划议程。具有跨领域广泛适用性的数据密集型AI/ML技术可以在领域科学和工程领域带来革命性的发现，并应对最大的全球社会挑战(如促进人类健康、使用可再生能源、控制和管理气候变化、在不破坏环境的情况下养活不断增长的人口，以及建立一个公正和可持续的社会)。为了我们国家的经济增长和整体福祉，这个研讨会还将致力于如何创造未来的产业和劳动力。这一奖项反映了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。

In recent years, foundational research in artificial intelligence (AI), machine learning (ML) and data science, have drawn incredible interest. Some of the research has focused on using these data-driven approaches to enhance scientific and engineering discoveries in other disciplines. While workshops and meetings have been held around the world by the to discuss cutting-edge breakthroughs and emerging trends, the majority of events are structured for siloed scientific fields. A paradigm-shifting scientific revolution might be made possible by integrating important discoveries across these events (i.e., a meta-workshop) to develop cogent novel insights. This project supports a meta-workshop on AI to accelerate science and engineering discovery. The workshop will provide the scientific community with information on the state of complementary research in AI, machine learning and other data analytic approaches across the science and engineering domains. The topics of interest include identifying specific subject areas with high potential for data-driven approaches to discovery.This meta-workshop will bring together leaders of AI, ML, data science and science and engineering (e.g., biology, biological engineering, chemistry, chemical engineering, physics, material science, etc). The majority of attendees will be core organizers from recent workshops and meetings around the heart of data-intensive discoveries. They will include the most important findings from their events and collaborate with other participants to generate new insights. The ultimate goal of the meta-workshop is to work with the leaders of diverse disciplines to develop a coherent and far-reaching research program agenda. Data-intensive AI/ML techniques with broad applicability across domains can lead to transformative discovery in domain sciences and engineering and address the biggest global societal challenges (such as promoting human health, using renewable energy, containing and managing climate change, feeding the expanding population without damaging the environment, and establishing a just and sustainable society). For the economic growth and general well-being of our nation, this workshop will also target ways to create the industries and workforce of the future.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.