Collaborative Research: REU Site: Advancing Data-Driven Deep Coupling of Computational Simulations and Experiments

合作研究：REU 站点：推进数据驱动的计算模拟和实验的深度耦合

• 批准号: 2243981
• 负责人: Xiaokun Yang
• 金额: $ 4.67万
• 依托单位: University of Houston - Clear Lake
• 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: 2023-05-15 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243981&HistoricalAwards=false
• 关键词: Collaborative; Research; REU; Site; Advancing

This project establishes a Research Experiences for Undergraduate (REU) site at Washington State University Vancouver and University of Houston Clear Lake. The REU site hosts a diverse cohort of ten undergraduate students across the nation per year for three years to participate in various research projects on developing and optimizing data-driven and data-intensive scientific workflows used for arrhythmia detection, intelligent monitoring of health behavior, cancer cell detection. The REU site provides an excellent platform for undergraduate students to gain new insights into and potential interests in high-performance computing (HPC) and data-intensive workflows. The project informs a generation of teaching modules on various aspects related to scientific data analysis, large-scale simulation in mechanical engineering, and optimization of HPC systems. The REU site provides underrepresented students, from community colleges, primarily undergraduate institutions, and Hispanic-serving institutions, opportunities to gain experience in interdisciplinary research from a group of researchers representing different races, genders, and cultures.Data-intensive workflows (i.e., scientific workflows) are widely used in most data-driven research disciplines today, often exploiting rich and diverse data resources and parallel and distributed computing platforms. In the proposed summer research program, undergraduate students participate a variety of projects focusing on various aspects of developing data-intensive and data-dependent scientific workflows, from their use as a technique to analyze and process large-scale, real-world data from HPC applications to investigating the underlying computer software and hardware support for accelerating the execution of those workflows. The REU site focuses on real-world scientific problems, including flow simulations for managing large wind farms, droplet ejection modeling for advanced manufacture, microfluidic cancer cell detection in liquid biopsy. The site activities include students training on using data-driven approaches (e.g., machine learning, advanced system software, and emerging hardware) to address the big data issues in the study of these scientific research problems.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.

该项目为华盛顿州立大学温哥华大学和休斯顿大学清克湖的本科生（REU）网站建立了研究经验。 REU网站每年在全国各地拥有多种学生队列，三年来参与各种研究项目，以开发和优化数据驱动的数据驱动和数据密集型科学工作流，用于心律不齐检测，智能监测健康行为，对健康行为进行智能监测，癌症细胞检测。 REU网站为本科生提供了一个绝佳的平台，以获得对高性能计算（HPC）和数据密集型工作流程的新见解和潜在利益。该项目为与科学数据分析，机械工程中的大规模模拟以及HPC系统的优化有关的各个方面提供了一系列教学模块。 REU网站为社区大学，主要是本科机构以及西班牙裔服务机构提供了不足的学生，从一组代表不同的种族，性别和文化的研究人员那里获得跨学科研究的机会，从而获得跨学科研究的经验。并行和分布式计算平台。在拟议的夏季研究计划中，本科生参与了各种项目，这些项目着重于开发数据密集型和数据依赖数据的科学工作流程的各个方面，从它们用作一种技术来分析和处理HPC应用程序中的大规模现实世界数据到研究这些工具执行的基础计算机软件和硬件支持的基础软件和硬件支持。 REU站点着重于现实世界中的科学问题，包括用于管理大型风电场的流仿真，用于高级生产的液滴射血建模，液体活检中的微流体癌细胞检测。现场活动包括学生对使用数据驱动方法（例如机器学习，高级系统软件和新兴硬件）进行培训，以解决研究这些科学研究问题的大数据问题。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响来通过评估来支持的。