REU Site: Computational Methods for Discovery Driven by Big Data

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As participants in the University of Minnesota (UMN) REU Site program, students will engage in research that develops computational methods for scientific discovery across disciplines that are driven by big data. In this 10-week summer program, in addition to immersion in research, students will receive technical training and professional development that encourages and prepares them for a sustained career in the sciences. This includes Big Data Colloquia, Communicating Science workshops, career mentoring, and public dissemination of research findings. Towards an objective of increased participation and broader impacts, this program will bring together nationally recruited students and those from UMN and local institutions to establish a cohort with diverse academic and cultural backgrounds. A Big 10 University situated in a large urban environment, UMN has a strong research community that encourages transdisciplinary research within and outside the boundaries of the institution.Closely mentored by a member of the Computer Science and Engineering (CS&E) faculty, each student will contribute to active research that addresses open questions in computational complexity, machine learning, parallel and distributed computing, mobile and cloud computing, or graphics and visualization. A UMN REU participant might use observation data to simulate crowd behavior, analyze genomic sequence data to better understand microbial communities, develop tools to analyze chemical-genetic interaction networks, improve spatial perception in a virtual environment, develop visualization techniques to better understand massive data sets, enhance parallel distributed processing through algorithm development or by harnessing the computational power of a network of mobile devices, or use graph-based approaches to better understand climate change. The diverse research of CS&E faculty represents collaboration across the University with faculty in genetics, chemistry, climate science, neuroscience, architecture, medicine, and biomedical engineering to propel all of these disciplines and computer science towards previously unattainable insights and discoveries. The web site http://www-users.cs.umn.edu/~boley/big-data-reu/index.html has more information on this project.