Transforming Analytical Learning in the Era of Big Data: A Summer Institute in Biostatistics and Data Science

大数据时代的分析学习变革：生物统计学和数据科学暑期学院

• 批准号: 10549365
• 负责人: Jian Kang
• 金额: $ 24.2万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10549365
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PROJECT SUMMARY The global pandemic that we are currently facing has further underscored the importance of harnessing information from heterogeneous data sources and turning them into actionable knowledge. Building a diverse, intellectually dynamic and socially progressive workforce in data science is more important than ever. We propose a six-week long undergraduate summer institute in Biostatistics and Data Science: “Transforming Analytical Learning in the Era of Big Data” to be held in person at the Department of Biostatistics, University of Michigan (U-M), Ann Arbor, with a group of approximately 30 undergraduate students from 2022-2026. The program builds on the success of our existing Big Data Summer Institute (BDSI) supported by a NIH BD2K Courses and Skills grant award (2016-2018) and a SIBS award from NHLBI (2019- 2021). Over the past five years we have trained 204 undergraduate students. Of the students who have finished their undergraduate degree, approximately 52% have pursued graduate education in a relevant discipline and 32 have already enrolled in a relevant graduate program at the University of Michigan. Our past cohort contains approximately 52% women and 17% underrepresented minority students. We plan to expose program students to diverse techniques, skills and problems at the intersection of Big Data and Human Health. We primarily focus on four genres of health Big Data arising in Electronic Health Records, Genomics, Infectious Disease Epidemiology and Imaging. The mentored research projects will be defined primarily in cardiovascular and infectious diseases in collaboration with clinicians and public health scientists. The trainees will be taught and mentored by a team of interdisciplinary faculty from Biostatistics, Statistics, Computer Science and Engineering, Epidemiology and Medicine, reflecting the shared intellectual landscape needed for Big Data research. At the conclusion of the program there will be a capstone symposium showcasing the research of the students via poster and oral presentation. There will be lectures by U-M researchers, outside guests and a professional development workshop to prepare the students for graduate school. There will be a series of panel discussions, focus groups and workshops on the importance of diversity, equity, inclusion and ethics in data science and interactive programming that discuss the role of data science in reducing health disparities. Along the way students are expected to form lasting bonds over shared research experiences and social activities. The program has strong institutional support from multiple units and centers on campus and leverages the cross-disciplinary intellectual richness of the University of Michigan. The resources developed for the summer institute, including lectures, assignments, projects, template codes and datasets will be freely available through a Wiki page and a YouTube channel so that this format can be replicated anywhere in the world. This democratic dissemination plan will lead to access of teaching and training material in this new field of health data science across the world. The overarching goal of our summer institute in big data is to recruit and train the next generation of data scientists using a non-traditional, active learning paradigm and engage them in influential research related to human health. We aspire to teach, mentor, grow undergraduate trainees in ways that will shape their vision for a career in data science. Our goal is to create an inspiring educational experience that will have a transformative impact on the future career trajectories of our trainees. Our long-term objective is to create a skilled and diverse research workforce to handle some of the pressing challenges in biomedical big data.

项目概要 当前，我们面临的全球大流行病进一步凸显了控制疫情的重要性。 来自异构数据源的信息并将其转化为可操作的知识。 数据科学领域多元化、智力活跃、社会进步的劳动力比 我们建议开设为期六周的生物统计学和数据科学本科生暑期学院： “大数据时代的分析学习变革”将在系亲自举行 安娜堡密歇根大学 (U-M) 生物统计学，以及大约 30 名本科生 该项目以我们现有的大数据暑期学院 (BDSI) 的成功为基础。 得到 NIH BD2K 课程和技能资助奖（2016-2018）和 NHLBI SIBS 奖（2019-2019）的支持 2021年），过去五年我们培养了204名本科生。 完成本科学位后，大约 52% 的人在某个领域继续研究生教育 相关学科，32人已就读于大学相关研究生课程 密歇根州，我们过去的队列中大约有 52% 是女性，17% 是少数族裔学生。 我们计划让项目学生接触大数据交叉领域的各种技术、技能和问题 我们主要关注电子健康记录中出现的四种健康大数据， 将确定基因组学、传染病流行病学和影像学指导的研究项目。 主要与封建和公共卫生科学家合作研究心血管和传染病。 学员将由来自生物统计学、统计学、 计算机科学与工程、流行病学和医学，反映了共享的知识格局 大数据研究所需的。项目结束时将举行一次顶点研讨会。 通过海报和口头报告展示学生的研究成果 密歇根大学将举办讲座。 研究人员、外部嘉宾和专业发展研讨会，帮助学生为毕业做好准备 学校将举办一系列关于多样性重要性的小组讨论、焦点小组和研讨会， 数据科学中的包容性、公平性和公平道德以及讨论数据科学作用的交互式编程 在此过程中，学生们有望通过共同研究建立持久的联系。 该计划得到了多个单位和中心的强有力的机构支持。 在校园内，并利用密歇根大学跨学科的丰富知识。 为暑期学院开发的资源，包括讲座、作业、项目、模板代码 数据集将通过 Wiki 页面和 YouTube 频道免费提供，以便这种格式可以 这一民主传播计划将在世界任何地方得到复制。 全球健康数据科学这一新领域的培训材料我们夏季的总体目标。 大数据研究所旨在利用非传统的、主动的方式招募和培训下一代数据科学家。 我们渴望教学，并让他们参与与人类健康相关的有影响力的研究。 导师，以塑造数据科学职业愿景的方式培养本科生。 是创造一种鼓舞人心的教育体验，对未来的职业产生变革性的影响 我们的长期目标是培养一支技术精湛、多元化的研究队伍， 应对生物医学大数据中的一些紧迫挑战。