| NSF Org: |
CCF Division of Computing and Communication Foundations |
| Recipient: |
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| Initial Amendment Date: | June 13, 2014 |
| Latest Amendment Date: | June 25, 2018 |
| Award Number: | 1433220 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Tracy Kimbrel
CCF Division of Computing and Communication Foundations CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | June 15, 2014 |
| End Date: | August 31, 2018 (Estimated) |
| Total Intended Award Amount: | $300,000.00 |
| Total Awarded Amount to Date: | $337,147.00 |
| Funds Obligated to Date: |
FY 2018 = $37,147.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
303 COOPER ST CAMDEN NJ US 08102-1519 (856)225-2949 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
311 N. 5th Street Camden NJ US 08102-1400 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Special Projects - CCF, Algorithmic Foundations |
| Primary Program Source: |
01001819DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
The "depth-first" educational approach allows students with almost no background in a particular subject to study advanced topics in that subject in a relatively short time. The PI has successfully used this approach to train undergraduate students in computer science at Rutgers University-Camden and inspired them to pursue graduate studies. The program in Theoretical Computer Science (TCS for short) provides an opportunity to translate the potential of promising students into measurable impact. The program introduces undergraduate and high school students to TCS in a depth-first manner. New students join the program each summer, with almost no background in computer science and are introduced to topics in discrete mathematics and algorithms. The meetings with the students continue during the academic year. Students who return to the program in subsequent years study advanced topics in theoretical computer science and participate in research. Students participating in this program gain robust exposure to the field of computer science and are ready to study advanced topics early in college, which will enable them to do substantive research before they graduate. The program has been quite successful in attracting and retaining female participants.
This project will continue to test the success of depth-first approach in training students to conduct research in TCS. Various research topics in optimization and approximation algorithms will be explored by high school and undergraduate students. In the end, a more diverse pool of students contribute to the research progress in TCS.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Intellectual Merit: The PI worked on optimization problems related to
scheduling and covering. The work involved designing algorithms that
yield near-optimal solutions (approximation algorithms) for the
problems and proving hardness of approximation results. On some
projects the PI worked with undergraduate students.
Broader Impact: The PI worked with high school students as part of the
Program in Algorithmic and Combinatorial Thinking (PACT) as well as
with undergraduate students at Rutgers-Camden. For the past two
summers there were about 100 participants during the summer.
In PACT, students study topics in theoretical computer science - new
students study topics in discrete mathematics during the summer, then
study Algorithm Design during the academic year, and then some of them
return for the second summer to study advanced algorithms. Most
students don't get a chance to learn these topics until they are in
college. By participating in PACT the students get an exposure to
Computational Thinking, which would help the students in any field
that they pursue. Students who continue studying in PACT after their
first summer get a chance to learn advanced topics which helps them
get involved in research while they are in high school or soon after
starting college.
Many students at Rutgers-Camden have a non-traditional
and/or disadvantaged background. The PI works closely with them
helping them build strong careers for themselves. The students who
have participated in this project have done well - several of them
have gone to top graduate programs in Computer Science after
graduation and some have won awards for their research.
The work done in this project is a strong indication that sustained
mentoring and training combined with giving opportunities to people
can help people turn around their careers/lives and consequently
increase the diversity in the community.
Last Modified: 01/12/2019
Modified by: Rajiv C Gandhi
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