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

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活跃程度研讨会。研讨会的重点是强调机器学习在交通现象研究中应用的最新进展和未来方向。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。这次研讨会是独一无二的，它汇集了交通现象研究的所有领域的国家专家，交流意见，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，他们将就机器学习、交通现象及其交叉路口的重要方向提供他们的专家观点。它还将涉及有关专题的小组讨论，探索推动该领域发展的新方法，并找出课程中存在的差距，以便有效地培训和教育下一代有能力解决这两个学科交叉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。

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.