International Conference on Design of Experiments 2022

2022 年实验设计国际会议

• 批准号: 2202327
• 负责人: Manohar Aggarwal
• 金额: $ 0.99万
• 依托单位: University of Memphis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2202327&HistoricalAwards=false
• 关键词: International; Conference; Design; Experiments; 2022

This award supports participation of junior researchers in the 6th International Conference on the Design of Experiments (ICODOE 2022) held at the University of Memphis during May 8-11, 2022. The principles of design and analysis of experiments form a fundamental part of research and development in areas as diverse as medical trials, pharmaceuticals, manufacturing, engineering, market research, agriculture, and many other fields. The conference will enable vital interaction between outstanding researchers in academia and industry who are advancing experimental design methodology with a view to improving systems for everyday life, from food delivery to cancer treatment. In addition, the conference will have a significant impact on the education of the next generation of researchers in experimental design, both junior researchers and those from underrepresented groups, by introducing them to innovative new methodology and new application areas, and by providing ample opportunity for these new researchers to interact with established researchers. In the 21st century, the uses of experimental design have multiplied considerably. For example, the Design of Experiments (DOE), the science of pursuing knowledge through the process of efficient data collection, can enable progress in the search for more efficient and speedy artificial intelligence (AI) learning, which underpins the so-called "fourth industrial revolution." The techniques and principles that are fundamental to DOE have already found use in testing new algorithms. Sessions on reinforcement learning and machine learning at the ICODOE conference will introduce these topic areas to the DOE community and help to bridge knowledge between these communities. Other new developments in experimental design include its use in on-line experiments within networks, where lack of independence between treated and control groups is being tackled. Important advances on the design of experiments in the pharmaceutical industry have been made; conference sessions will present recent research dealing with COVID trial recruitment, oncology dose finding, and adaptive designs for use in clinical trials. In industry, the design of computer experiments and model calibration remain of high importance. Related to this is screening to determine the factors that most affect a response, and the use of sampling to analyze enormous data sets. In addition, traditional areas such as optimal design are being adapted to practitioner needs without losing efficiency. With sessions devoted to all these topics, the ICODOE conference will provide multiple unique interdisciplinary opportunities for early career researchers to form networks for future collaboration and will also actively bolster participation of underrepresented groups in mathematical and data sciences. Details on ICODOE 2022 can be found at https://www.memphis.edu/msci/icodoe22.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.

该奖项支持初级研究人员参加 2022 年 5 月 8 日至 11 日在孟菲斯大学举行的第六届国际实验设计会议 (ICODOE 2022)。实验设计和分析原则构成医学试验、制药、制造、工程、市场研究、农业和许多其他领域研究和开发的基本组成部分。此次会议将使学术界和工业界的杰出研究人员之间进行重要的互动，他们正在推进实验设计方法，以改善从食品输送到癌症治疗等日常生活系统。此外，会议还将向下一代实验设计研究人员（包括初级研究人员和来自代表性不足群体的研究人员）的教育产生重大影响，向他们介绍创新的新方法和新的应用领域，并为这些新研究人员提供与成熟研究人员互动的充足机会。在 21 世纪，实验设计的用途大大增加。例如，实验设计（DOE）是一门通过有效数据收集过程追求知识的科学，可以在寻求更高效、更快速的人工智能（AI）学习方面取得进展，从而支撑所谓的“第四次工业革命”。 DOE 的基础技术和原理已经用于测试新算法。 ICODOE 会议上的强化学习和机器学习会议将向 DOE 社区介绍这些主题领域，并帮助在这些社区之间架起知识桥梁。实验设计的其他新进展包括其在网络内在线实验中的使用，其中正在解决治疗组和对照组之间缺乏独立性的问题。制药行业实验设计取得了重要进展；会议将介绍有关新冠肺炎试验招募、肿瘤学剂量发现以及临床试验中使用的适应性设计的最新研究。在工业中，计算机实验的设计和模型校准仍然非常重要。与此相关的是筛选以确定对响应影响最大的因素，以及使用抽样来分析大量数据集。此外，优化设计等传统领域正在适应从业者的需求，而不会损失效率。通过专门讨论所有这些主题的会议，ICODOE 会议将为早期职业研究人员提供多种独特的跨学科机会，以形成未来合作的网络，并将积极支持数学和数据科学领域代表性不足的群体的参与。有关 ICODOE 2022 的详细信息，请访问 https://www.memphis.edu/msci/icodoe22。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。