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.

项目摘要 我们目前面临的全球大流行病进一步突出了利用 从异构数据源中获取信息，并将其转化为可操作的知识。建设 在数据科学领域，多元化、充满智力活力和社会进步的劳动力比 史以来我们提出了一个为期六周的生物统计学和数据科学本科暑期学院： “在大数据时代转变分析学习”将亲自在教育部举行 生物统计学，密歇根大学（U-M），安阿伯，一组约30名本科生 学生2022-2026该计划建立在我们现有的大数据暑期研究所（BDSI）的成功基础上 由NIH BD 2K课程和技能资助奖（2016-2018）和NHLBI的SIBS奖（2019- 2019）支持。 2021年）。在过去的五年里，我们培养了204名本科生。的学生中 完成本科学位后，大约52%的人在一个 相关学科和32已经在大学的相关研究生课程就读 密歇根我们过去的队列包含大约52%的女性和17%的代表性不足的少数民族学生。 我们计划让项目学生接触大数据交叉点的各种技术、技能和问题 和人类健康。我们主要关注电子健康记录中出现的四种健康大数据， 基因组学、传染病流行病学和成像。指导研究项目将被定义 与临床医生和公共卫生科学家合作，主要用于心血管和传染病。 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，反映了共享的知识景观 需要大数据研究。在节目结束时将有一个顶点研讨会 透过海报及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，外部客人和专业发展研讨会，为学生准备研究生 学校将举行一系列关于多样性重要性的小组讨论、重点小组和讲习班， 数据科学中的公平、包容和道德以及讨论数据科学作用的交互式编程 减少健康差距。沿着这条路，学生们有望在共同的研究中形成持久的联系 经验和社会活动。该计划有多个单位和中心的强大机构支持 在校园里，并利用密歇根大学的跨学科知识财富。 为暑期学院开发的资源，包括讲座，作业，项目，模板代码 和数据集将通过维基页面和YouTube频道免费提供，以便这种格式可以 在世界上任何地方都可以复制。这一民主传播计划将使人们有机会接受教育， 在世界各地的健康数据科学这一新领域的培训材料。我们夏天的首要目标 大数据研究所的目标是招募和培养下一代数据科学家， 学习范式，让他们参与与人类健康有关的有影响力的研究。我们渴望教书， 指导，培养本科学员，以塑造他们在数据科学领域的职业愿景。我们的目标 是创造一个鼓舞人心的教育经验，这将对未来的职业生涯产生变革性的影响 我们学员的轨迹。我们的长期目标是建立一支熟练和多样化的研究队伍， 应对生物医学大数据中的一些紧迫挑战。