REU Site: Trust and Reproducibility of Intelligent Computation

REU 站点：智能计算的信任和可重复性

• 批准号: 2244492
• 负责人: Ganesh Gopalakrishnan
• 金额: $ 40.5万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2244492&HistoricalAwards=false
• 关键词: REU; Site; Trust; Reproducibility; Intelligent

This Research Experience for Undergraduates Site addresses the growing reality that modern society is increasingly dependent on complex software components to work as expected (trustworthy) and produce consistent results (reproducible). Trustworthiness and reproducibility govern adoption and acceptance of the results produced by software across a range of applications including medical diagnostics, facial recognition, traffic analysis, network security, and chemical reaction control. Computing educators are obliged to instill in the next generation of scientists and engineers -- today’s undergraduates -- an understanding of principled methods that enhance software system reliability, trustworthiness, and reproducibility. A typical undergraduate student is not sufficiently exposed to these concerns nor the aforesaid supportive methods, and yet they will be the ones building future intelligent systems. Thus, this REU site will address these issues, as well as emerging dangers such as introducing bias into AI-based applications or leaking personal data demand instruction in ethical considerations of software systems, another aspect of trustworthiness. Student participants will learn the state-of-the-art methods typically used in trustworthy and reproducible science and engineering. Weekly training and activity sessions will bring the entire cohort together for pre-packaged exercises, e.g., using Jupyter notebooks, software version control, automated defect detection, automatic performance analysis and optimization, and data analysis. These activities are deployed on one-of-a-kind, translational research platforms operated by the University of Utah, namely the NSF-funded Cloudlab and the POWDER project. Additional activities through the university’s Office of Undergraduate Research and the Utah Center for Inclusive Computing allow the researchers to offer workshops on research best practices, ethics, and inclusion. With a focus on applications that incorporate machine learning, achieve high efficiency, and the systems that support the applications, each undergraduate participant will work with a faculty mentor and their research group to complete a research project, producing both a written research report and a well-packaged artifact that, together, enable another person to understand the research, repeat the experiments, and reproduce the results. Students are selected to the program with the dual goals of broadening participation in computing and offering research experiences to students with severely limited opportunities at their home institutions. The program is assessed at the beginning and end, with an evaluation of how students applied their new understandings to their research projects, with follow-ups conducted as students apply to graduate school. The project plans to share these assessments and the curricular material with other institutions to propagate education in trustworthy and reproducible software to galvanize the next generation of scientists and engineers.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.

本科生网站的这一研究经验解决了现实的现实，即现代社会越来越依赖复杂的软件组件，可以按预期（可信赖）产生一致的结果（可再现）。可信度和可重复性控制了软件在包括医学诊断，面部识别，交通分析，网络安全和化学反应控制等一系列应用程序中产生的结果的采用和接受。计算教育者有义务在下一代科学家和工程师（当今的本科生）中灌输对主要方法的理解，从而增强了软件系统的可靠性，可信度和可重复性。典型的本科生没有充分接触这些问题，也没有上述支持方法，但它们将是建立未来智能系统的人。这是，此REU网站将解决这些问题，以及在基于AI的应用程序中引入偏见或以软件系统的道德考虑，这是可信赖性的另一个方面的新兴舞者。学生参与者将学习通常用于可信赖和可重复的科学和工程学的最先进方法。每周的培训和活动会议将使整个队列融合在一起进行预包装的练习，例如，使用Jupyter笔记本，软件版本控制，自动缺陷检测，自动性能分析和优化以及数据分析。这些活动部署在犹他大学运营的一种单独的翻译研究平台上，即NSF资助的CloudLab和粉末项目。通过大学本科研究办公室和犹他州包容性计算中心的其他活动，研究人员可以提供有关研究最佳实践，道德和包容的研讨会。侧重于将机器学习，提高高效率以及支持应用程序的系统进行应用程序，每个本科生将与教职员工的心态及其研究小组一起完成研究项目，同时生成书面研究报告和包装好的人工制品，从而使其他人能够理解研究，重复研究，重复实验，并将结果重现。将学生选为该计划，其双重目标是扩大参与计算和为家庭机构机会严重有限的学生提供研究经验。该计划在开始和结束时进行了评估，并评估了学生如何将新理解应用于研究项目，并在学生申请研究生院时进行了随访。该项目计划与其他机构共享这些评估以及当前的材料，以在可信赖和可重复的软件中传播教育，以激发下一代科学家和工程师。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来通过评估来支持的。

项目成果

An NSF REU Site Based on Trust and Reproducibility of Intelligent Computation: Experience Report

基于智能计算的信任和可重复性的 NSF REU 站点：经验报告

• DOI: 10.1145/3624062.3624100
• 发表时间: 2023
• 期刊: and Analysis
• 作者: Hall, Mary;Gopalakrishnan, Ganesh;Eide, Eric;Cohoon, Johanna;Phillips, Jeff;Zhang, Mu;Elhabian, Shireen;Bhaskara, Aditya;Dam, Harvey;Yadrov, Artem
• 通讯作者: Yadrov, Artem