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

全球范围内的数据生产呈爆炸式增长，传统的与人类服务相关的领域，如教育、公共政策、医疗保健和环境科学，正在寻求方法来提出更聪明的问题，建立更准确的数据模型，并推动更有效的行动。这个REU网站将吸引本科生在数据密集型计算科学及其跨学科应用方面进行关键和及时的研究。该网站提供了一系列精心策划的本科学习和研究机会，涵盖了一系列人类服务，如循证智能健康、数据授权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族裔学生和女性，对数据分析影响社会结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，支持学术和社会关系，支持协作团队环境。这些学生将住在新泽西理工大学48英亩的校园里，这对一群城市通勤学生来说可能是一次改变生活的经历。学生的工作任务是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，学生的家乡院校也将从中受益。学生们还将成为一个新的数据科学学习社区的成员，这个社区将利用社交网站和定期的网络研讨会，继续这个夏天对该领域关键问题的探索，并关注潜在的职业机会。最后，REU网站的毕业生将有潜力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。该网站结合了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深度专业知识，以及霍夫斯特拉大学在人类服务和商业方面的杰出项目。每年夏天，10名有才华的学生将在专家教师和研究生的指导下，以小组形式进行精心策划的研究经验。学生可选择的课题包括环境癌症风险研究、透过自动评估改善学习、设计智慧线上广告，以及建构行车安全路边感测器等。除了基于项目的研究，学生们还将体验到丰富多样的研讨会、讲习班和行业参观，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对数据科学的关键知识和技能以及主要研究方法有具体的了解。他们将使用描述性和推断性统计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，并研究研究过程，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，学生们将加深对数据科学领域及其概念联系的了解，并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未被充分代表的学生开辟新的研究和职业轨道，以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 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 NJIT's fully-wired 48 acre campus, which may well be a life-changing experience for a group of urban commuter students. The students' home institutions 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.