FOPAM 2019: Foundations of Process Analytics and Machine learning

FOPAM 2019：过程分析和机器学习的基础

• 批准号: 1927746
• 负责人: Phillip Westmoreland
• 金额: $ 3.24万
• 依托单位: Cache Corporation
• 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: 2019-06-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1927746&HistoricalAwards=false
• 关键词: FOPAM; 2019; Foundations; Process; Analytics

This award is partial support of the 2019 Foundations of Process Analytics and Machine Learning (FOPAM) conference on August 5-9, 2019 in Raleigh, North Carolina. The aim of this conference is to bring together industry and academic researchers to discuss the current status and future directions in data analytics and machine learning relevant to the chemical process industries. The funds will provide support to junior faculty, postdoctoral fellows, and graduate students that may not have the financial support to attend the workshop. The conference also will include optional educational workshops. The conference will focus on the topic of data analytics tools as applied to problems encountered in the chemical process industries. The tools can be applied to processes regardless of whether the underlying phenomena are biological, physical, or chemical. The conference will address topics in data analytics and high-throughput data process for process monitoring and diagnosis; machine learning for process and control design; computational chemistry/materials analytics; reinforcement learning as applied to process operations and control; and, synergies among process, materials, business, and supply chain 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.

该奖项是对2019年8月5日至9日在北卡罗来纳州罗利举行的2019年过程分析和机器学习基础(FOPAM)会议的部分支持。本次会议的目的是将产业界和学术界的研究人员聚集在一起，讨论与化工过程行业相关的数据分析和机器学习的现状和未来方向。这些资金将为可能没有经济支持参加研讨会的初级教师、博士后研究员和研究生提供支持。会议还将包括可选的教育研讨会。会议将集中讨论应用于化工过程工业中遇到的问题的数据分析工具。无论潜在的现象是生物的、物理的还是化学的，这些工具都可以应用于过程。会议将讨论以下主题：用于过程监控和诊断的数据分析和高通量数据处理；用于过程和控制设计的机器学习；计算化学/材料分析；应用于过程操作和控制的强化学习；以及过程、材料、业务和供应链数据分析之间的协同。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。