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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

基本信息

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
项目类别：
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
关键词：
Active Learning Adverse drug effect Area Arts Award Awareness Bachelor&apos s Degree Behavioral Sciences Big Data Big Data to Knowledge Biological Markers Biology Biometry Cardiovascular Diseases Case Study Clinical Code Collaborations Collection Communicable Diseases Communities Computing Methodologies Data Data Science Data Scientist Data Set Data Sources Development Discipline Disease Diverse Workforce Education Educational process of instructing Educational workshop Electronic Health Record Engineering Enrollment Epidemiology Epigenetic Process Equity Ethics Exposure to Faculty Female Focus Groups Future Generations Genetic Genomics Goals Graduate Education Grant Health Health Sciences Human Image Infectious Disease Epidemiology Influentials Institution Knowledge Learning Literature Medical Medicine Mentors Methodology Michigan Minority Groups National Heart, Lung, and Blood Institute Natural Language Processing Neurosciences Oral Participant Persons Prevention Problem Sets Public Health Public Health Informatics Public Health Schools Reduce health disparities Research Research Personnel Research Project Grants Resources Role STEM program Schools Science Science, Technology, Engineering and Mathematics Scientist Seminal Series Shapes Social Behavior Social Justice Societies Statistical Methods Student Selections Students Talents Techniques Training Underrepresented Minority United States National Institutes of Health Universities Vaccines Vision Woman Work big biomedical data big-data science burden of illness career cluster computing cohort college computer science current pandemic data integration data management data mining data visualization design equity, diversity, and inclusion experience graduate school health data heterogenous data high dimensionality improved infectious disease model instructor interest lectures mathematical model member metabolomics network models next generation novel therapeutics open source tool pandemic disease personalized medicine population health posters programs recruit skills social statistical and machine learning statistics success summer institute symposium tool undergraduate student underrepresented minority student wiki

项目摘要

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.

项目总结