REU Site: Collaborative Research: Undergraduate Research in Computational Data Analytics for Advancing Human Services

全球范围内的数据生产正在爆炸式增长，传统的人类服务相关领域，如教育，公共政策，医疗保健和环境科学，正在寻求提出更聪明的问题，建立更准确的数据模型，并推动更有效的行动。这个本科生（REU）网站的研究经验将吸引本科生在数据密集型计算科学及其跨学科应用的关键和及时的研究。该网站提供了一系列精心策划的本科生学习和研究机会，涵盖了一系列人类服务，例如基于证据的智能健康，数据授权的教育和数据驱动的商业智能。它旨在鼓励合格的学生，特别是代表性不足的少数民族学生和妇女，对数据分析影响社会成果的巨大潜力感到兴奋，并激励他们将数据科学作为未来学习和职业的一部分。REU网站将为来自纽约-新泽西大都市区的学生提供优秀的研究经验，这些经验由支持协作团队环境的学术和社会联系所支持。该网站的学生将住在新泽西理工学院（NJIT）的48英亩的校园，这很可能是一个改变生活的经验，为一组城市通勤学生。学生的家庭学校也将受益于学生分配的任务，即将数据科学与他们的主要研究领域联系起来，并与同学分享他们的研究经验。学生们还将成为数据科学新学习社区的成员，该社区将使用社交网站和定期网络研讨会继续夏季对该领域关键问题的探索，并关注潜在的职业机会。最后，REU网站的毕业生将有可能成为未来的数据科学专业人士，他们可以通过改变人类服务来影响社会并提高生活质量。该网站将新泽西理工学院在计算机科学和高性能计算基础设施方面的广泛专业知识与霍夫斯特拉大学在人类服务和商业方面的优秀课程相结合。每年夏天，10名才华横溢的学生将在专家教师和研究生的指导下，以小团队的形式进行精心策划的研究体验。学生们将从环境癌症风险研究、通过自动评估改善学习、设计智能在线广告以及构建用于驾驶安全的路边传感器等主题中进行选择。除了基于项目的研究，学生将体验各种各样的研讨会，研讨会和行业访问，以获得广泛的令人兴奋的职业发展机会。学生深入的个人参与将使他们能够具体了解数据科学的关键知识和技能，以及其主要研究方法。他们将使用描述性和推理性统计数据从大数据中得出结论，了解模型假设和选择对分析结果的影响，并查看研究过程，包括文献综述，研究方法的设计和实施，数字数据收集以及将研究结果传达给技术和非技术受众。最终，学生将加深对数据科学领域及其概念联系的了解，沿着提高书面和口头沟通，批判性思维和解决问题的能力。该网站的一个主要目标是为有才华的代表性不足的学生开辟新的研究和职业轨道，探索数据科学如何促进人类服务的影响。

The worldwide production of data is exploding and traditional human service related fields such as education, public policy, healthcare, and environmental science are seeking ways to ask smarter questions, build more accurate data models, and drive more effective action. This Research Experience for Undergraduates (REU) site will engage undergraduate students in critical and timely research in data intensive computational science and its interdisciplinary applications. The site offers a collection of carefully planned undergraduate learning and research opportunities spanning a spectrum of human services, such as evidence-based smart health, data-empowered education, and data driven business intelligence. It seeks to encourage qualified students, particularly underrepresented minority students and women, to become excited about the immense potential of data analytics to impact societal outcomes, and to motivate them to include data science as part of their future studies and careers. The REU site will provide students from the New York-New Jersey metropolitan area with excellent research experiences bolstered by academic and social connections that support a collaborative team environment. The site students will live on New Jersey Institute of Technology's (NJIT) fully-wired 48 acre campus, which may well be a life-changing experience for a group of urban commuter students. The students' home schools will also benefit from the students' assigned task of connecting data science to their major fields of study, and sharing their research experiences with their fellow students. The students will also become members of a new learning community in data science, which will use social networking sites and periodic webinars to continue the summer's exploration of critical issues in the field as well as spotlight potential career opportunities. Finally, graduates of the REU site will have the potential to become future data science professionals who can impact society and enhance the quality of life through transforming human services.The site combines New Jersey Institute of Technology's broad depth of expertise in computer science and high powered computing infrastructure with Hofstra University's outstanding programs in human services and business. Each summer ten talented students will work in small teams on carefully planned research experiences under the mentorship of expert faculty and graduate students. The students will choose from topics such as the study of environmental cancer risk, improving learning through automated assessment, designing intelligent on-line advertising, and constructing roadside sensors for driving safety. In addition to project-based research, the students will experience a rich variety of seminars, workshops, and industry visits for a broad spectrum of exciting career development opportunities. The students' in-depth personal engagement will enable them to gain a concrete understanding regarding key knowledge and skills in data science, as well as its main research methodologies. They will use descriptive and inferential statistics to draw conclusions from big data, understand the impact of model assumptions and selection on analysis outcomes, and look at the research process, including the literature review, design and implementation of research approaches, digital data collection and communicating research findings to a technical and non-technical audience. Ultimately, the students are achieving a deepening knowledge of the field of data science and its conceptual connections along with improved written and oral communication, critical thinking and problem solving skills. A major goal of the site is to open new studies and career tracks for talented underrepresented students to explore how data science can advance the impact of human services.