Collaborative Research: Workshop on Exuberance of Machine Learning in Transport Phenomena

合作研究：机器学习在交通现象中的丰富性研讨会

• 批准号: 1940134
• 负责人: Ali Beskok
• 金额: $ 5.1万
• 依托单位: Southern Methodist University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1940134&HistoricalAwards=false
• 关键词: Collaborative; Research; Workshop; Exuberance; Machine

This award is to support the Workshop on Exuberance of Machine Learning in Transport Phenomena to be held on February 10-11, 2020 in Dallas, Texas. The workshop focuses on highlighting the current state-of-the-art and future directions on the application of Machine Learning on transport phenomena research. With the growth of Machine Learning in all areas of science and engineering, we have observed a rapid growth in the number of workshops, conferences, and summer schools all over the world. This workshop is unique in which it brings together national experts from all areas of transport phenomena research to exchange ideas, and to establish a better understanding on limitations and potentials of Machine Learning. The workshop program includes invited speakers who will offer their expert views of important directions in Machine Learning, transport phenomena, and their intersection. It will also involve panel discussions on related topics, exploring novel ways to advance the field, and to identify gaps across the curriculum for effective training and education of the future generation of scientists and engineers capable of tackling important problems at the intersection of these two subjects. A Final Report will be prepared at the end of the workshop which will include a summary of the workshop and the major recommendations made by the experts in the field.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.

该奖项是为了支持将于2020年2月10日至11日在德克萨斯州达拉斯举行的机器学习在交通现象中的蓬勃发展研讨会。该研讨会的重点是突出机器学习在运输现象研究中的应用的当前最先进水平和未来方向。随着机器学习在所有科学和工程领域的发展，我们观察到世界各地的研讨会，会议和暑期学校的数量迅速增长。该研讨会是独一无二的，它汇集了来自运输现象研究各个领域的国家专家，交流思想，并更好地了解机器学习的局限性和潜力。研讨会计划包括特邀演讲者，他们将提供机器学习，传输现象及其交叉点的重要方向的专家观点。它还将涉及相关主题的小组讨论，探索推进该领域的新方法，并确定课程中的差距，以有效培训和教育未来一代能够解决这两个学科交叉点的重要问题的科学家和工程师。研讨会结束时将准备一份最终报告，其中将包括研讨会的总结和该领域专家提出的主要建议。该奖项反映了NSF的法定使命，并被认为值得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来支持。