REU Site: REU Research Experiences and Mentoring in Data-Driven Discovery

非技术：这个REU网站将帮助支持NSF促进科学进步的使命，为本科生提供多学科的研究经验，在计算机科学/工程实验室进行为期10周的令人兴奋的暑期体验，使基础和应用数据驱动的问题的工作成为可能，专注于应用机器学习技术、数据分析和并行计算技术，并为他们未来的科学生涯做好准备。REU的学生将有机会利用最先进的高性能计算资源来解决多个问题领域中存在的大数据问题，包括生物工程、环境工程和生物医学工程。PI‘s将利用位于马萨诸塞州霍利奥克的马萨诸塞州绿色高性能计算中心为这个多学科REU站点提供背景。该项目将为学生提供广泛的网络基础设施培训，让项目参与者掌握探索数学、科学、工程和并行计算之间真正多学科界限的技能。俄勒冈州立大学位于波士顿市中心的东北大学。技术：REU项目涵盖计算机科学和工程领域的广泛技术领域。示例项目包括：应用机器学习对慢性阻塞性肺疾病(COPD)数据进行聚类，挖掘Twitter订阅以确定气候变化趋势，利用硬件加速器检测4-D计算机断层扫描图像中的癌症肿瘤，以及利用对基因表达的回归分析来了解视网膜再生的模式。这个网站的一个新奇之处在于，它专注于招生工作，为那些刚刚完成本科一年级学业的学生定制他们的研究经验，让他们及早参与研究他们的学术道路。REU网站致力于在东北大学和合作机构中创建一个指导生态系统，开发一种可以移植到其他机构的模式。该项目与六所城市社区学院/大学建立了关系，建立了一个学生管道，创造了一个多样化的REU候选人库，向学生展示了研究生教育和研究的潜在途径。该计划利用CEISE REU工具包进行计划前和计划后的调查，以及招聘。REU-D3网站的重点是改变东道主和合作学术机构的指导态度和做法。

Non-Technical:This REU site will help support NSF's mission to promote the progress of science by providing multi-disciplinary research experience for undergraduates with exciting 10-week summer-based experiences in computer science/engineering laboratories, enabling work on both fundamental and applied data-driven problems, focused on applying machine learning techniques, data analytics, and parallel computing technologies, and preparing them for future scientific career. The REU students will have the opportunity to utilize state-of-the-art high performance computing resources to tackle big data problems present in a number of problem domains, including Bioengineering, Environmental Engineering and Biomedical Engineering. PI's will leverage the Massachusetts Green High Performance Computing Center located in Holyoke, MA to provide a backdrop for this multi-disciplinary REU Site. The program will provide students with extensive cyber-infrastructure training, equipping program participants with the skillsets to explore the boundaries between math, science, engineering and parallel computing that are truly multi-disciplinary. The REU Site is located at Northeastern University in the heart of Boston. Technical:The REU projects span a wide range of technical fields in Computer Science and Engineering. Example projects include: applying machine learning to cluster Chronic Obstructive Pulmonary Disease (COPD) data, data mining Twitter feeds to identify trends in climate change, utilizing hardware accelerators to detect cancerous tumors in 4-D Computed Tomography images, and utilizing regression analysis on gene expressions to understand patterns in retina regeneration. One novelty of this site is its focus on recruiting efforts, tailoring their research experiences for students that have only completed their freshmen year of their undergraduate education, engaging them early in research on their academic pathway. The REU site works to create a mentoring eco-system at both Northeastern University and the partnering institutions, developing a model that is transferrable to other institutions. The program builds relationships with six urban community colleges/universities to build a pipeline of students, creating a diverse pool of REU candidates, showing students potential pathways to graduate education and research. The program leverages the CISE REU Toolkit for pre- and post-program surveys, as well as for recruiting. The REU-D3 Site is focused on effecting changes in mentoring attitudes and practices at the host and partnering academic institutions.