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进一步强调了利用的重要性 来自异质数据源的信息，并将其转化为可行的知识。建筑 潜水员，智能动态和社会进步的数据科学劳动力比 曾经。我们提出了一个为期六周的生物统计学和数据科学本科夏季研究所： “在大数据时代改变分析学习”将亲自举行 密歇根大学（U-M）的生物统计学，安阿伯（Ann Arbor），大约有30个本科生 2022 - 2026年的学生。该计划以我们现有的大数据夏季研究所（BDSI）的成功为基础 由NIH BD2K课程和技能授予奖（2016-2018）和NHLBI的SIBS奖（2019-- 2021）。在过去的五年中，我们培训了204名本科生。有学生 完成了他们的本科学位，大约有52％的人从事研究生教育 相关学科和32个已经参加了大学的研究生课程 密歇根州。我们过去的队列中有大约52％的女性和17％的少数民族学生。 我们计划在大数据交集中将计划学生暴露于潜水技术，技能和问题 和人类健康。我们主要关注四种在电子健康记录中产生的健康大数据的流派， 基因组学，传染病流行病学和成像。将定义讨论的研究项目 主要与临床医生和公共卫生科学家合作进行心血管和传染病。 由生物统计学，统计学， 计算机科学和工程，流行病学和医学，反映共享的智力格局 大数据研究所需。该计划结束时，将有一个盖石研讨会 通过海报和口头演讲展示学生的研究。 U-M将有讲座 研究人员，外部客人和专业发展研讨会，以便学生为研究生做好准备 学校。关于多样性重要性的一系列小组讨论，焦点小组和研讨会， 数据科学和交互式编程中的公平，包容和道德，讨论数据科学的作用 减少健康分布。一路上期望学生对共同的研究形成持久的纽带 经验和社交活动。该计划在多个单位和中心都有大力的机构支持 在校园里，并利用了密歇根大学的跨学科知识丰富。 为夏季学院开发的资源，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，以便该格式可以是 在世界任何地方复制。这项民主传播计划将导致教学的机会 在全球卫生数据科学的新领域培训材料。我们夏天的总体目标 大数据研究所是使用非传统的，主动的招募和培训下一代数据科学家 学习范式并吸引他们与人类健康有关的有影响力的研究。我们渴望教书， Menor，成长本科学员，以影响他们对数据科学职业的愿景。我们的目标 是创造鼓舞人心的教育经验，将对未来职业产生变革性的影响 我们受训者的轨迹。我们的长期目标是创建一个熟练和多样化的研究劳动力 处理生物医学大数据中的一些紧迫挑战。