We have just received preliminary notification that our program will be able to grow from 8 supported participants each year in 2010-2011 to 12 supported participants each year in 2012-2014. This is to be funded jointly by the National Science Foundation (NSF) and the National Security Agency (NSA). To accomodate this relative late notice on funding, we will continue to consider all applications that come in, also past the stated deadline. Do not hesitate to contact us with questions at firstname.lastname@example.org. --- Update: All available slots for the 2012 program have been filled by now. Please check back here for information on the 2013 program.
The REU Site: Interdisciplinary Program in High Performance Computing is located in the Department of Mathematics and Statistics at UMBC, just south of Baltimore, Maryland, in the heart of the Baltimore-Washington corridor of industry and government. The program is comprised of learning scientific, parallel, and statistical computing and of project work on interdisciplinary applications. All activities of the program are conducted by teams of students, closely supported by graduate teaching and reseach assistants as well as faculty.
For updates on the program, please check back at this webpage. If you have specific questions, do not hesitate to send an e-mail to email@example.com. Here is a printer-friendly flier in PDF format. We invite you to peruse the Summer 2010 and 2011 tabs above to see the research projects chosen that year, a list of special events including field trips, and an extensive photo album. This description tries to give the most realistic and concrete impression of the activities throughout the program from a student perspective. Or watch the YouTube Movie with opening remarks by our university president and testimonials from two 2010 participants, graciously produced for us by the UMBC New Media studio.
The detailed schedule gives an overview of the topics involved with the program and the activities planned during the 8 weeks of this REU Site program. In a first phase during Weeks 1, 2, and 3, students will focus on learning scientific, parallel, and statistical computing. A second phase focuses on project work on interdisciplinary applications. Week 8 is a third phase that is dedicated to preparing a technical report and a poster presentation of the work. This description tries to give the most realistic and concrete impression of the activities throughout the program from a student perspective.
All activities of the program will be conducted in teams of about 4 students, closely supported in all phases by graduate teaching and reseach assistants as well as by the directors of the program. The structured learning of scientific, parallel, and statistical computing will consist of classes, each of which is immediately followed by team work in a computer lab, during which the teams will work on assignments with the support of a graduate TA. The program includes credit for a senior-level three-credit course on parallel computing that corresponds to the 29 numbered classes in the detailed schedule.
During Weeks 1 and 2, teams will learn about several possible interdisciplinary projects with clients from application areas outside of the mathematical sciences. Examples of clients include faculty from other departments such as mechanical engineering or biology, researchers from industrial companies such as Northrop Grumman, researchers from government agencies or research labs such as the Environmental Protection Agency, the National Institutes of Health (NIH), or the National Institute of Standards and Technology (NIST). By the end of Week 2, each team will choose a project and propose a plan of attack. The project work will start during Week 3 and be the focus of Weeks 4, 5, 6, and 7. The team work on the interdisciplinary projects will be supported closely by a graduate RA and a faculty mentor for each team. Throughout the program, there will be plenty of opportunities to interact with all members of the program both in formal project updates, informal brainstorming sessions (including the morning social every weekday), and more. We also plan on several field trips to interesting sites, for instance, NASA Goddard Space Flight Center, a client's organization, and similar.
The last week of the program, Week 8, is dedicated to assembling the results of the project work. A technical report that will be posted on the Publications page of the UMBC High Performance Computing Facility will serve as the citable result of the work as well as the basis for the product delivered to the client. This technical report can also be an excellent basis for a journal article such as for the SIAM Undergraduate Research Online (SIURO) journal. Additionally, the work will be presented as a research poster at the Summer Undergraduate Research Fest (SURF) hosted by the College of Natural and Mathematical Sciences (CNMS) on Wednesday of Week 8.
The program also includes additional material presented to help support the project activities and to broaden the horizons for graduate school, such as an overview of the mathematical typesetting system LaTeX and other tools for presentations and report writing, a discussion of academic integrity in scientific work, insights into applying to graduate school, a GRE preparation course, and more. All material of this program is designed to include an introduction that assumes very little background in it but also very advanced material that will make it useful for experienced users. These broader aspects of the program are designed to make the project work more effective as well as to provide an excellent preparation for and impression of graduate studies in mathematics or statistics.
In total, the program of this REU Site, as summarized in the detailed schedule provides a combination of formal introduction to high performance computing in the mathematical sciences covering aspects of scientific, statistical, and parallel computing with team work on an interdisciplinary application project. This combination of aspects will give participants a powerful and exciting experience of how to combine learning with applying material to project work, all in an atmosphere of mutual support by all members of the project from undergraduate students, graduate students, faculty, to clients.