Conference: Machine Learning in Science and Engineering

该奖项支持于2018年6月6日至8日在宾夕法尼亚州匹兹堡举行的第一届科学与工程机器学习（MLSE）年度研讨会。该会议最初由卡内基梅隆大学和佐治亚理工学院组织，是第一个全面开放的年度会议，汇集了科学和工程领域的领先研究人员，他们的工作受益于机器学习和数据科学的进步。虽然机器学习已经彻底改变了生物学和生物医学研究的许多领域，但它对科学和工程的影响还处于早期阶段。本次研讨会将汇集科学、技术、工程和数学（STEM）领域的研究人员，专注于将机器学习应用于基础或应用性质的问题。演讲将侧重于使现有的机器学习方法适应当前的研究领域，开发针对科学和工程的新机器学习算法，以及确定可能只有使用数据驱动方法才能实现的新研究前沿。研讨会将为与会者提供由机器学习专家讲授的短期课程，内容涉及对推进这些领域至关重要的各种尖端工具。MLSE研讨会将有助于促进机器学习方法和跨科学和工程领域的合作，将STEM领域的研究人员聚集在一起，专注于将机器学习应用于基础和应用问题。演讲将侧重于使现有的机器学习方法适应当前的研究领域，开发针对科学和工程的新机器学习算法，以及确定可能只有使用数据驱动方法才能实现的新研究前沿。预计该研讨会在第一年将有至少400名直接参与者和与会者，包括代表性不足的少数民族、在少数民族服务机构（MSIs）就读的人、会议地点当地的低收入学生，或根据成绩和需要被选中前往参加会议的学生。研究界的几个团体参与其中，包括不同群体的学生、早期职业研究人员和教师。将通过在社区特定和广泛的新闻发布场所发布的新闻项目，不断广泛传播信息。目前提供的部分支助主要是为了使学生和青年研究人员能够参与，此外还有数量有限的辅导班和全体会议发言人。组织者致力于促进代表性不足的群体、初级研究人员和学生的参与，并包括教程，以扩大尽可能多的参与者群体。组织者将对这些旅游奖项进行公开竞争，由一个多元化的委员会选出，申请机会将在相关学科中广泛传播。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

This award supports the first annual Symposium on Machine Learning in Science and Engineering (MLSE), held in Pittsburg, Pennsylvania, June 6-8, 2018. The meeting, initially organized by Carnegie Mellon University and Georgia Tech, is the first comprehensive and open annual conference bringing together leading researchers in science and engineering whose work benefits from advances in machine learning and data science. While machine learning has revolutionized many areas of biological and biomedical research, its impact across the sciences and engineering is at an early stage. This symposium will bring together researchers in a diversity of Science, Technology, Engineering, and Math (STEM) areas focused on applying machine learning to problems of fundamental or applied nature. Presentations will focus on adapting existing machine learning methods to current research areas, developing new machine learning algorithms specific to science and engineering, and identifying new frontiers of research that may only be pursued using a data-driven approach. The symposium will offer attendees focused short courses taught by experts in machine learning on a variety of cutting-edge tools that are critical in advancing these fields. The MLSE symposium will help catalyze machine learning methodologies and collaborations across the sciences and engineering, bringing together researchers in a diversity of STEM areas focused on applying machine learning to fundamental and applied problems. Presentations will focus on adapting existing machine learning methods to current research areas, developing new machine learning algorithms specific to science and engineering, and identifying new frontiers of research that may only be pursued using a data-driven approach.The symposium is anticipated to reach, in its first year, at least 400 direct participants and attendees, including under-represented minorities, those attending Minority Serving Institutions (MSIs), and low income students local to the conference venues, or selected to travel to the event based on merit and need. Several groups within the research community are involved, including a diverse group of students, early career researchers and faculty. Information will be widely disseminated on a continuing basis through news items published via community-specific and broad news release venues. Partial support is being provided primarily to enable participation by students and young researchers, in addition to a limited number of tutorial and plenary speakers. The organizers are committed to promoting participation among underrepresented groups, junior researchers and students, and including tutorials to widen accessibility to as large a group of attendees, as possible. The organizers will have an open competition for these travel awards, selected by a diverse committee, and the opportunity to apply will be widely disseminated across the relevant disciplines.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.