Conference: Quality and Productivity Research Conference - Statistics, Deep Learning, and the People Side of Process

第39届质量与生产力研究会议(QPRC)将于2023年6月6日至8日在德克萨斯州休斯顿由休斯顿大学(UH)主办。这是美国统计协会质量和生产力部门的主要年度活动，它将通过演讲、海报会议、技术参观和为期一天的短期课程来审议数据科学和统计相关主题。由于在几乎每个已知的环境中，每天都会收集、处理和分析数十亿个数据集，越来越多的基于数据的决策对个人和社会产生现实影响，因此数据科学和统计界必须跟上收集的数据的快速增长和多样化的步伐，并向每个利用数据的应用领域提供最新的方法和指导。QPRC旨在支持数据科学和统计方面的知识共享，使研究人员和从业者能够了解基于数据的系统和决策的影响，并避免或至少检测和减轻意外的不利后果。它将为与会者提供一个独特的机会，让他们见面、交流想法和经验，并形成合作关系。通过参加QPRC，学生们将获得宝贵的学习经验和与其他与会者建立联系的机会。这次会议的主题是“统计、深度学习和过程的人的一面”，它将包括18个受邀的论文会议、四到六个投稿会议、海报会议、技术参观和一个为期一天的短期课程(6月5日)。QPRC为统计学家、数据科学家、量化分析师、研究人员和从业者提供了一个独特的机会，讨论机器学习、面部识别等计算机密集型领域目前取得的进展，并交流使用现代大数据的新想法和经验，从而有可能增进对数据科学和统计相关主题的知识和理解。因此，这次会议有可能1)传播新的方法和数据驱动的方法，对以前的研究结果进行评估，并验证理论方法，2)促进对使用大数据的好处的进一步调查，包括结构化和非结构化的，以及3)提高人们对合乎道德地使用大数据的认识，并解决自动收集和分析大数据集可能导致的偏见。此外，QPRC还具有在几个方面造福社会的潜力。首先，它为与会者提供了学习和重新构建他们对数据科学和统计相关概念的理解的机会。第二，QPRC将促进数据科学和统计方法在各种应用领域的负责任的部署和解释。第三，为了将会议的知识传播给更广泛的社区，QPRC的演讲者将被邀请提交他们的工作，并在《商业和工业应用随机模型杂志》的特刊上发表。第四，扩大代表不足的群体(即妇女、种族/少数族裔等)的参与。在科学、技术、工程和数学(STEM)学科中，要求提供资金以支持研究生，特别是那些来自美国机构的代表性不足的群体参加QPRC。会议的网站是www.uh.edu/qprc2023。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。

The 39th Quality and Productivity Research Conference (QPRC) will be hosted by the University of Houston (UH) in Houston, Texas from June 6-8, 2023. It is the main annual event for the Quality and Productivity Section of the American Statistical Association, and it will consider data science and statistics related topics though presentations, poster sessions, a technical tour, and a one-day short course. Because billions of data sets are collected, processed, and analyzed on a daily basis in virtually every environment known, with an increasing number of data-based decisions being made that have real-world consequences for individuals and society, the data science and statistics community must keep pace with the rapid growth and variety of collected data and provide up-to-date methodologies and guidance to every applied field that utilizes data. QPRC aims to support knowledge sharing regarding data science and statistics to enable researchers and practitioners to understand the impact of data-based systems and decisions, and avoid, or at least detect and mitigate, unintended adverse consequences. It will provide a unique opportunity for attendees to meet, exchange ideas and experiences, and form collaborations. Through participation in QPRC students will gain access to invaluable learning experiences and networking opportunities with other conference attendees. The conference theme is “Statistics, Deep Learning & the People Side of Process,” and it will include 18 invited paper sessions, four to six contributed sessions, poster sessions, a technical tour, and a one-day short course (on June 5). QPRC has the potential to advance knowledge and understanding of topics related to data science and statistics by providing a unique opportunity for statisticians, data scientists, quantitative analysts, researchers, and practitioners to discuss the current progress made in computer-intensive fields such as machine learning, facial recognition, and so forth, and exchange novel ideas and experiences in working with modern big data. Hence, this conference has the potential to 1) disseminate new methods and data-driven approaches, the evaluation of previous findings, and the validation of theoretical approaches, 2) stimulate further investigations regarding the benefits of working with big, multidimensional data, both structured and unstructured, and 3) increase the awareness of the need to use big data ethically and to address the bias that may result from the automated collection and analysis of large datasets. In addition, QPRC has the potential to benefit society in several ways. First, it provides the opportunity for attendees to learn and reframe their understanding of concepts related to data science and statistics. Second, QPRC will promote the responsible deployment and interpretation of data science and statistical methods in a variety of applied areas. Third, to disseminate the knowledge from the conference to the broader community, QPRC presenters will be invited to submit their work for publication in a special issue of the Journal of Applied Stochastic Models in Business and Industry. Fourth, to broaden the participation of underrepresented groups (i.e., women, racial/ethnic minorities, etc.) in science, technology, engineering, and mathematics (STEM) disciplines, funding is requested to support graduate students especially those in underrepresented groups from U.S. institutions to participate in QPRC. The conference website is www.uh.edu/qprc2023.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.