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U.S.-India International Collaborative Research and Training for Computer Science Students

U.S.-India International Collaborative Research and Training for Computer Science Students
美印计算机科学专业学生国际合作研究与培训
批准号:
1050968
负责人:
Rajiv Gandhi
金额:
$4.99万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-10-01 至 2012-09-30

项目摘要

项目成果

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中文摘要
翻译
拉吉夫·甘地·奥伊斯-1050968美国-印度计算机科学专业学生国际合作研究与培训奖向计算机科学教授拉吉夫·甘地颁发的这一国际合作研究与培训奖将在印度孟买为来自罗格斯大学卡姆登分校的四名有前途的计算机科学专业学生提供独特的研究与教育经验。与PI一起,学生们将与导师Suneeta Sane,教授兼计算机技术系主任,Veermate Jijabai理工学院(VJTI)和塔塔基础研究所技术与计算机科学学院的教员一起研究NP-Hard问题(非确定性多项式时间)的近似算法。该小组打算解决的问题出现在临时网络和存储区域网络中。智能价值调度问题在通信网络设计中起着核心作用。其中许多问题是NP难的,因此产生接近最优解的有效算法具有内在的重要性。这种算法在可伸缩性和诸如带宽(和功率,在自组织网络的情况下)等有价值的资源的使用方面会对网络的性能产生重大影响。更广泛的影响--PI加入了罗格斯大学卡姆登分校的教职,这是一所文科院校,目的是专注于本科教育。拟议项目的核心部分是为罗格斯大学卡姆登分校的学生提供国际研究和教育体验。所有参与这一项目的学生都将继续攻读研究生课程。由于两名国际合作者是女性,这可能会对参与该项目的女学生的长期目标产生额外的积极影响。
英文摘要
Rajiv Gandhi OISE- 1050968 U.S.-India International Collaborative Research and Training for Computer Science Students This international collaborative research and training award to Computer Science Professor Rajiv Gandhi will provide a unique research and educational experience in Mumbai, India for four promising computer science students from Rutgers University-Camden. The students along with the PI will work on Approximation Algorithms for NP-hard problems (Non-deterministic Polynomial Time) with mentors Suneeta Sane, Professor and Head, Computer Technology Department, Veermate Jijabai Technological Institute (VJTI) and faculty at the School of Technology and Computer Science, Tata Institute of Fundamental Research. The problems that the group intends to work on arise in ad hoc and storage area networks. Intellectual Merit- Scheduling problems play a central role in the design of communication networks. Many of these problems are NP-hard and hence efficient algorithms that produce near-optimal solutions are of intrinsic importance. Such algorithms can have significant impact on the performance of the networks in terms of scalability and the usage of valuable resources such as bandwidth (and power, in case of ad hoc networks). Broader Impacts- The PI joined the faculty at Rutgers University Camden, a liberal arts institution, in order to focus on undergraduate education. The core component of the proposed project is to provide an international research and education experience to students at Rutgers University Camden. All students participating in this project are expected to pursue graduate studies. As two of the international collaborators are women, this is likely to have the additional positive impact on the long-term goals of the participating female students in this project.
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会议论文
AF:RUI:Small:Approximation Problems with Tree Outputs Under Parameterized Constraints
  • 批准号:
    1910565
  • 项目类别:
    Standard Grant
  • 资助金额:
    $33.06万
  • 财政年份:
    2019
  • 负责人:
    Rajiv Gandhi
  • 依托单位:
Transforming Potential into Promise: A Depth-First Approach
  • 批准号:
    1433220
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2014
  • 负责人:
    Rajiv Gandhi
  • 依托单位:
EAGER: Computer Science Research and Enrichment Program
  • 批准号:
    1048606
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.0万
  • 财政年份:
    2010
  • 负责人:
    Rajiv Gandhi
  • 依托单位:
RUI: Approximation Algorithms for Scheduling Problems
  • 批准号:
    0830569
  • 项目类别:
    Standard Grant
  • 资助金额:
    $15.0万
  • 财政年份:
    2008
  • 负责人:
    Rajiv Gandhi
  • 依托单位:
海外基金