U.S.-India International Collaborative Research and Training for Computer Science Students
U.S.-India International Collaborative Research and Training for Computer Science Students
批准号:
1050968
负责人:
Rajiv Gandhi
金额:
$4.99万
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
中文摘要
拉吉夫·甘地OISE- 1050968美国-印度国际合作研究和培训计算机科学的学生这个国际合作研究和培训奖,以计算机科学教授拉吉夫甘地将提供一个独特的研究和教育经验,在孟买,印度的四个有前途的计算机科学的学生从罗格斯大学卡姆登。 学生沿着PI将与导师Suneeta Sane,教授和负责人,计算机技术系,Veermate Jijabai技术研究所(VJTI)和塔塔基础研究所技术与计算机科学学院的教师一起研究NP难问题(非确定性多项式时间)的近似算法。 该小组打算研究的问题出现在ad hoc和存储区域网络中。 智能优点-调度问题在通信网络的设计中起着核心作用。 这些问题中的许多是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。 这样的算法可以在可扩展性和有价值的资源,如带宽(和功率,在自组织网络的情况下)的使用方面对网络的性能有显着的影响。更广泛的影响-PI加入了罗格斯大学卡姆登,一个文科机构的教师,以专注于本科教育。 拟议项目的核心组成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经验。 所有参加该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妇女,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.
期刊论文(0)
专著(0)
科研奖励(0)
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