REU Site: Summer Undergraduate Program in Engineering Research at Berkeley (SUPERB): Collecting and Using Big Data for the Public Good

REU 网站:伯克利工程研究暑期本科生课程(SUPERB):为公共利益收集和使用大数据

基本信息

  • 批准号:
    1659833
  • 负责人:
  • 金额:
    $ 25.92万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-02-01 至 2020-01-31
  • 项目状态:
    已结题

项目摘要

It is evident to all of us that the widespread and growing availability of vast amounts of real-time data presents both a tremendous opportunity to improve our understanding of the world and make better automated decisions, as well as a great technical challenge to collect, communicate and process this data efficiently and reliably. Leading researchers in Electrical Engineering and Computer Science will mentor undergraduate students on their proposed REU projects. Potential impacts range from more efficient sensor networks, to improved wireless access to the data they produce, to better human robot interaction, to better analysis of medical data from microscopes, and even helping prevent nuclear war. The project seeks to address a multitude of societal problems that can be examined by collecting and using big data while inspiring students to dedicate themselves to this work. The project is committed to exposing a diverse group of undergraduate researchers that will expand the impact of this project and the engineering research pipeline. At the conclusion of the program, participants will be proficient in using big data to solve societal problems that have direct impacts on their communities. The goal of the Summer Undergraduate Engineering Research project in the Electrical Engineering and Computer Sciences Department is to prepare and motivate a group of diverse competitive candidates for graduate student. The focus of the REU site is electrical engineering and computer science to support collecting and using big date for the public good. Students spend nine weeks during the summer working on high caliber research projects addressing technical challenges arising in collecting, communicating and processing the vast amounts of data becoming available both efficiently and reliably. This project covers the entire range of challenges and opportunities, from better sensor networks to collect this data more efficiently; to improved wireless resource management to move the data; to machine learning techniques for processing the images, including from microscopes, that make up much of the new data; to designing robots that can learn to interact better with humans based on the data they collect; to better enforcement of the Comprehensive Nuclear Test Ban Treaty by analyzing seismic data used to detect underground nuclear tests. The project will have research contributions in areas such as communications and networking, human computer interaction, machine learning, robotics, scientific computing and visualization.
我们所有人都清楚,大量实时数据的广泛和不断增长的可用性既为提高我们对世界的理解和做出更好的自动化决策提供了巨大的机会,也为有效和可靠地收集,交流和处理这些数据带来了巨大的技术挑战。在电气工程和计算机科学的领先研究人员将指导本科生对他们提出的REU项目。潜在的影响范围从更有效的传感器网络,到改进对它们产生的数据的无线访问,到更好的人机交互,到更好地分析来自显微镜的医疗数据,甚至帮助防止核战争。该项目旨在通过收集和使用大数据来解决众多社会问题,同时激励学生致力于这项工作。该项目致力于培养多元化的本科研究人员群体,这将扩大该项目和工程研究管道的影响。在该计划结束时,参与者将熟练使用大数据来解决对其社区有直接影响的社会问题。电气工程和计算机科学系夏季本科生工程研究项目的目标是准备和激励一批具有竞争力的研究生候选人。 REU网站的重点是电子工程和计算机科学,以支持收集和使用公共利益的大数据。 学生们在夏季花了九个星期的时间从事高水平的研究项目,以解决在收集,交流和处理大量数据时出现的技术挑战,这些数据既有效又可靠。该项目涵盖了各种挑战和机遇,从更好的传感器网络到更有效地收集这些数据;改进无线资源管理以移动数据;处理图像的机器学习技术,包括来自显微镜的图像,这构成了大部分新数据;设计机器人,可以根据他们收集的数据学习更好地与人类互动。通过分析用于探测地下核试验的地震数据,更好地执行全面禁止核试验条约。该项目将在通信和网络、人机交互、机器学习、机器人技术、科学计算和可视化等领域做出研究贡献。

项目成果

期刊论文数量(0)
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专利数量(0)

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James Demmel其他文献

Fast multiplication of random dense matrices with sparse matrices
随机稠密矩阵与稀疏矩阵的快速乘法
Minimizing Communication in Linear Algebra
  • DOI:
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    0
  • 作者:
    James Demmel
  • 通讯作者:
    James Demmel
Writing programs that scale with increasing numbers of cores should be as easy as writing programs for sequential computers
编写随着内核数量的增加而扩展的程序应该像为顺序计算机编写程序一样简单
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    K. Asanović;Rastislav Bodík;James Demmel;T. Keaveny;K. Keutzer;J. Kubiatowicz;Nelson Morgan;David A. Patterson;Koushik Sen;J. Wawrzynek;David Wessel;K. Yelick
  • 通讯作者:
    K. Yelick
Automatic Performance Tuning for the Multi-section with Multiple Eigenvalues Method for the Symmetric Eigenproblem
对称特征值问题多段多特征值法的自动性能调优
Modeling the Bene ts of Mixed Data and Task Parallelism
模拟混合数据和任务并行性的好处
  • DOI:
  • 发表时间:
    1997
  • 期刊:
  • 影响因子:
    0
  • 作者:
    James Demmel;K. Yelick
  • 通讯作者:
    K. Yelick

James Demmel的其他文献

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{{ truncateString('James Demmel', 18)}}的其他基金

Collaborative Research:Frameworks: Basic ALgebra LIbraries for Sustainable Technology with Interdisciplinary Collaboration (BALLISTIC)
协作研究:框架:跨学科协作可持续技术的基本代数库(BALLISTIC)
  • 批准号:
    2004763
  • 财政年份:
    2020
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Standard Grant
SI2 SSI: Collaborative Research: Sustained Innovations for Linear Algebra Software (SILAS)
SI2 SSI:协作研究:线性代数软件 (SILAS) 的持续创新
  • 批准号:
    1339676
  • 财政年份:
    2013
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Continuing Grant
Collaborative Research: SDCI HPC Improvement: Improvement and Support of Community Based Dense Linear Algebra Software for Extreme Scale Computational Science
合作研究:SDCI HPC 改进:针对超大规模计算科学的基于社区的密集线性代数软件的改进和支持
  • 批准号:
    1032639
  • 财政年份:
    2010
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Standard Grant
Reliable and Scalable Software for Linear Algebra Computations on High End Computers
用于在高端计算机上进行线性代数计算的可靠且可扩展的软件
  • 批准号:
    0444486
  • 财政年份:
    2005
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Standard Grant
ITR/SI: Societal Scale Information Systems: Technologies, Design and Applications
ITR/SI:社会规模信息系统:技术、设计和应用
  • 批准号:
    0122599
  • 财政年份:
    2001
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Continuing Grant
Linear Algebra Algorithms and Tools for Emerging Computing Environments and User Communities
适用于新兴计算环境和用户社区的线性代数算法和工具
  • 批准号:
    9813362
  • 财政年份:
    1999
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Continuing Grant
Proposal for Toolboxes and Templated for Large Scale Linear Algebra Problems
针对大规模线性代数问题的工具箱和模板提案
  • 批准号:
    9313958
  • 财政年份:
    1994
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Continuing Grant
Parallelize a Global Atmospheric Chemical Tracer Model (Postdoctoral Research Associateship in Computational Science and Engineering)
并行化全球大气化学示踪剂模型(计算科学与工程博士后研究助理)
  • 批准号:
    9404748
  • 财政年份:
    1994
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Standard Grant
CISE 1994 Minority Graduate Fellowships Honorable Mention for Melody Ivory
Melody Ivory 获得 CISE 1994 少数族裔研究生奖学金荣誉奖
  • 批准号:
    9423174
  • 财政年份:
    1994
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Standard Grant
Mathematical Sciences: Analyzing Failures in Algorithms forGeneralized Eigenproblems Using Singularity Theory
数学科学:使用奇点理论分析广义本征问题算法中的失败
  • 批准号:
    9120852
  • 财政年份:
    1992
  • 资助金额:
    $ 25.92万
  • 项目类别:
    Standard Grant

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