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HDR DSC: Collaborative Research: Creating and Integrating Data Science Corps to Improve the Quality of Life in Urban Areas

HDR DSC: Collaborative Research: Creating and Integrating Data Science Corps to Improve the Quality of Life in Urban Areas
HDR DSC:协作研究:创建和整合数据科学团队以提高城市地区的生活质量
批准号:
1923986
负责人:
Sharad Sharma
金额:
$18.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2023-07-31

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中文摘要
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英文摘要
The goal of this project is to develop a team-based data science corps program for undergraduate students from Computer Science, Information Systems, and Business integrating both academic training as well as hands-on experience through real-world data science projects. This project is a collaborative effort with the University of Maryland Baltimore County as the coordinating as well as an implementing organization, and the University of Baltimore, Towson University, and Bowie State University as implementing organizations. This project focuses on the city of Baltimore as an exemplar for other cities in the US and across the globe. The project team will collaborate with a number of communities in the city of Baltimore to integrate real-world data science projects into classroom instruction in data science. The specific objectives of this project are as follows: (i) Develop the technical, analytical, modeling, and critical thinking skills that are key to success as a data science professional; (ii) Connect a cohort of students to communities, organizations, and projects that can benefit from the power of data science; (iii) Nurture and support innovative thinking in solving some of the key challenges facing the real world; (iv) Promote a better understanding of the power and pitfalls of data-driven discoveries to improve the quality of life in urban communities; (v) Increase the data science workforce capacity to support this critical area that is of growing importance in society; and finally, (vi) Evaluate the effect of the proposed data science corps on student learning. This project will create a core set of knowledge that will be valuable in developing solutions for real-world urban settings with the understanding that not all projects will require the application or use of every topic covered in the data science corps program. The core set of knowledge includes data collection and cleaning, data analysis using machine learning and deep learning techniques, data visualization including geospatial data and virtual reality, data privacy and security, and infrastructure for smart cities including IoT-based sensor networks. The proposed data science corps program will have two main phases: instructional phase (10 modules in total) and real-world team projects (5 modules in total). The project teams consist of students who have taken a course in at least one of the following areas: data collection and analysis, big data, machine learning including deep learning, smart cities, cybersecurity, geospatial data analysis and visualization, and virtual reality. Examples of team projects include: (i) developing community-based indicators that are compiled from open data portals and parametric and non-parametric statistical techniques to understand the relationship between urban sustainability and a range of factors including cleanliness and environment, crime and safety, business and economics, social and political, housing, health, and education; (ii) combining deep learning models such as convolutional neural networks (CNN) and long term short term memory recurrent neural networks (LSTM-RNN) to develop prediction models for derelict buildings that are likely to become vacant; (iii) combining sensor data and social media for automated information extraction, validation, and quality checks that can be beneficial to both citizens and emergency managers in crisis situations such as flash floods; (iv) developing smart streetlights that are networked LED systems that can be adjusted based on time of day and motion and can report outages back to central operations; and (v) developing augmented reality-based systems that leverage systems such as Microsoft HoloLens and mobile devices for building evacuation.NSF's Harnessing the Data Revolution Data Science Corps program focuses on building capacity for harnessing the data revolution at the local, state, national, and international levels to help unleash the power of data in the service of science and society. Projects in this program are being jointly funded by the NSF's Harnessing the Data Revolution Big Idea; the Directorate for Computer and Information Science and Engineering, Division of Information and Intelligent Systems; the Directorate for Education and Human Resources, Division of Undergraduate Education; the Directorate for Mathematical and Physical Sciences, Division of Mathematical Sciences; and the Directorate for Social, Behavioral and Economic Sciences, Office of Multidisciplinary Activities and Division of Behavioral and Cognitive Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(20)
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科研奖励(0)
会议论文
DOI: 10.29007/mq54
发表时间: 2019-09
期刊:
影响因子: --
作者: [S. Bodempudi;Sharad Sharma;A. Sahu;R. Agrawal]
通讯作者: S. Bodempudi;Sharad Sharma;A. Sahu;R. Agrawal
Mobile augmented reality system for object detection, alert, and safety
用于物体检测、警报和安全的移动增强现实系统
DOI: 10.2352/ei.2023.35.12.ervr-218
发表时间: 2023
期刊: Electronic Imaging
影响因子: --
作者: [Sharma, Sharad, Engel, Don]
通讯作者: Engel, Don
Active shooter response training environment for a building evacuation in a collaborative virtual environment
在协作虚拟环境中进行建筑物疏散的主动射手响应训练环境
DOI: 10.2352/issn.2470-1173.2020.13.ervr-223
发表时间: 2020
期刊: Electronic Imaging
影响因子: --
作者: [Sharma, Sharad, Bodempudi, Sri Teja, Scribner, David, Grazaitis, Peter]
通讯作者: Grazaitis, Peter
Situational awareness of COVID pandemic data using virtual reality
使用虚拟现实对新冠肺炎大流行数据进行态势感知
DOI: 10.2352/issn.2470-1173.2021.13.ervr-177
发表时间: 2021
期刊: Electronic Imaging
影响因子: --
作者: [Sharma, Sharad, Bodempudi, Sri Teja]
通讯作者: Bodempudi, Sri Teja
19
    FW-HTF-P: Immersive Virtual Reality Instructional Modules for Response to Active Shooter Events
    • 批准号:
      2321539
    • 项目类别:
      Standard Grant
    • 资助金额:
      $13.24万
    • 财政年份:
      2023
    • 负责人:
      Sharad Sharma
    • 依托单位:
    HDR DSC: Collaborative Research: Creating and Integrating Data Science Corps to Improve the Quality of Life in Urban Areas
    • 批准号:
      2321574
    • 项目类别:
      Standard Grant
    • 资助金额:
      $18.0万
    • 财政年份:
      2023
    • 负责人:
      Sharad Sharma
    • 依托单位:
    Collaborative Research: CISE-MSI: RCBP-RF: CPS, CNS: Emergency Response and Evacuation Training for Active Shooter Events
    • 批准号:
      2319752
    • 项目类别:
      Standard Grant
    • 资助金额:
      $18.0万
    • 财政年份:
      2022
    • 负责人:
      Sharad Sharma
    • 依托单位:
    Collaborative Research: CISE-MSI: RCBP-RF: CPS, CNS: Emergency Response and Evacuation Training for Active Shooter Events
    • 批准号:
      2131116
    • 项目类别:
      Standard Grant
    • 资助金额:
      $18.0万
    • 财政年份:
      2021
    • 负责人:
      Sharad Sharma
    • 依托单位:
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    • 批准号:
      82372246
    • 项目类别:
      面上项目
    • 资助金额:
      49万元
    • 批准年份:
      2023
    • 负责人:
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    DSC2功能缺失在原发性右心室扩张型心肌病的作用及机制研究
    • 批准号:
      82370357
    • 项目类别:
      面上项目
    • 资助金额:
      49万元
    • 批准年份:
      2023
    • 负责人:
      戴宇翔
    • 依托单位:
    基于DSC-MRI、DCE-MRI及DKI生理参数与ZEB1表达的关联机制实现复发胶质母细胞瘤ZEB1表达可视化的研究
    • 批准号:
      --
    • 项目类别:
      青年科学基金项目
    • 资助金额:
      30万元
    • 批准年份:
      2022
    • 负责人:
      王宝
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