World Meeting of the International Society for Bayesian Analysis 2022

该奖项为参加2022年6月25日至7月1日在加拿大蒙特利尔举行的国际贝叶斯分析学会（ISBA）世界会议的美国与会者提供旅费支持。会议主题是贝叶斯统计的理论、建模和应用。该奖项的重点是资助来自美国机构的初级研究人员（研究生和博士后研究人员）前往会议。重点将放在支助妇女和代表性不足群体的成员。参加会议将使初级统计学家了解影响现代贝叶斯统计研究的关键问题和方法，并为他们提供向更成熟的研究人员学习的机会，并建立指导和合作关系。关于会议的更多信息可在会议网页上查阅：https://isbawebmaster.github.io/ISBA2022/Statisticians在根据嘈杂、复杂的数据结构作出决策方面发挥着不可或缺的作用。统计方法在许多领域都有应用，包括生物医学研究、环境科学、金融、市场营销、心理学、公共卫生和基因组学。在统计学中，贝叶斯方法提供了许多吸引人的特点：贝叶斯方法提供了一个连贯的框架，用于整合来自不同来源的信息，并使用概率传达发现和结论；贝叶斯层次模型可以捕获数据和过程中不同来源的可变性；相关知识可以很容易地吸收；所有相关的不确定性被相干传播并合并到最终的推断中。因此，贝叶斯分析在各种各样的应用领域中都很常见。ISBA 2022将汇集不同的国际研究人员和从业人员，他们开发和使用贝叶斯统计方法，分享最新发现，交流思想，讨论新的，具有挑战性的问题。作为一个真正的国际会议，它将使与会者有机会接触其他国家的想法和同事，而他们通常可能不会与这些人打交道。会议组织者希望提供一个促进思想交流和交流的场所，欢迎年轻的研究人员，并促进合作和互动。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 provides travel support for US-based participants in the 2022 World Meeting of the International Society for Bayesian Analysis (ISBA), to be held from June 25 to July 1, 2022, in Montreal, Canada. The conference themes are theory, modeling, and applications of Bayesian statistics. The focus of this award is on funding for junior researchers (graduate students and postdoctoral researchers) from U.S.-based institutions to travel to the conference. Emphasis will be placed on supporting women and members of underrepresented groups. Participating in the conference will inform junior statisticians about key problems and methods that shape research in modern Bayesian statistics and provide them with opportunities to learn from more established researchers and to build mentoring and collaborative relationships. More information on the conference is available on the meeting web page: https://isbawebmaster.github.io/ISBA2022/Statisticians play an indispensable role in making decisions based on noisy, complex data structures. Statistical methods find application in myriad areas, including biomedical research, environmental science, finance, marketing, psychology, public health, and genomics. Within statistics, the Bayesian approach offers many appealing features: Bayesian methods provide a coherent framework for integrating information from different sources and communicating findings and conclusions using probabilities; Bayesian hierarchical models can capture different sources of variability in data and processes; relevant knowledge can be incorporated easily; and all relevant uncertainties are coherently propagated and incorporated into the final inference. Consequently, Bayesian analyses are commonplace across a wide variety of application areas. ISBA 2022 will bring together a diverse international community of researchers and practitioners who develop and use Bayesian statistical methods to share recent findings, exchange ideas, and discuss new, challenging questions. As a truly international meeting, it will provide participants with access to ideas and colleagues from other countries with whom they may not ordinarily interact. Meeting organizers hope to provide a venue that facilitates the exchange of ideas and cross-fertilization, is welcoming to young researchers, and promotes collaborations and interactions.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.