International Conference on Design of Experiments 2022

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实验设计国际会议（ICODOE 2022）。实验的设计和分析原则是研究和开发的基本组成部分，涉及医学试验、制药、制造、工程、市场研究、农业和许多其他领域。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，以期改善从食品配送到癌症治疗的日常生活系统。此外，会议将对下一代实验设计研究人员的教育产生重大影响，包括初级研究人员和代表性不足的群体，向他们介绍创新的新方法和新的应用领域，并为这些新的研究人员提供充分的机会与已有的研究人员进行互动。在21世纪的世纪，实验设计的使用已经大大增加。例如，实验设计（DOE），通过有效的数据收集过程追求知识的科学，可以在寻求更有效和更快速的人工智能（AI）学习方面取得进展，这是所谓的“第四次工业革命”的基础。“DOE的基本技术和原则已经在测试新算法中得到了应用。ICODOE会议上关于强化学习和机器学习的会议将向DOE社区介绍这些主题领域，并有助于在这些社区之间架起知识的桥梁。实验设计的其他新发展包括其在网络内的在线实验中的使用，其中治疗组和对照组之间缺乏独立性正在得到解决。在制药行业的实验设计方面取得了重要进展;会议将介绍最近的研究，涉及COVID试验招募，肿瘤学剂量发现和用于临床试验的自适应设计。在工业中，计算机实验设计和模型校准仍然非常重要。与此相关的是筛选，以确定最影响反应的因素，并使用抽样分析大量数据集。此外，优化设计等传统领域正在适应实践者的需求，而不会降低效率。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个独特的跨学科机会，以形成未来合作的网络，并将积极支持数学和数据科学中代表性不足的群体的参与。ICODOE 2022的详细信息可以在www.example.com上找到https://www.memphis.edu/msci/icodoe22.This奖项反映了NSF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而被认为值得支持。

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.