REU+ (REU for underrepresented undergraduate students) has a different page.
The REU application is available online.
Program Director: Loek Helminck
The NSF and the NSA provide generous funding and support for this REU program.
Stipend and support: $4,500 for 10 weeks, all housing provided, as well as a partial meal allowance. Travel funds up to $300 per participant provided as needed.
Topics for 2016 REU
Project 1: War-Gaming Applications for Achieving Optimum Acquisition of Future Space Systems
Project mentors: Tien M. Nguyen and Andy Guillen (The Aerospace Corporation), Hien Tran (NCSU)
Graduate student assistant: Amanda Coons
Recently U.S. Department of Defense (DOD) has released the Defense Innovation Initiative (DII) to focus the agency on five key aspects, namely, Aspect #1: People, Aspect #2: Reinvigorating war-gaming, Aspect #3: Initiate long-range research and development program, Aspect #4: Making DoD practices more innovative, and Aspect #5: Advance technology and new operational concepts. Per DII instruction, this proposed project plans to concentrate on the Aspect #2 and Aspect #4 by reinvigorate the war-gaming effort with a focus on an innovative approach for developing the optimum Program and Technical Baselines (PTBs) and their corresponding optimum acquisition strategies for future space systems. The goal of this project is to develop game engines using war-gaming concept to generate an optimum PTB solution and its corresponding acquisition strategy with associated contract incentives for a typical Fixed-Price Incentive Firm (FPIF) contract type and a Cost-Plus-Incentive-Fee (CPFF) contract type (if time permits). An “optimum solution” is obtained by compromising the system and acquisition objectives to achieve low lifecycle cost/total ownership cost, innovative design, decreased acquisition time, while meeting warfighter needs. The proposed project will expose REU participants to game theory, probability and statistics, non-linear programming and mathematical modeling components; as well as team approach to problem solving,
Project 2: Optimization of Chemical Structure Features for the Classification of Toxicological Endpoints
Project mentors: Hisham El-Masri (US Environmental Protection Agency), Hien Tran (NCSU)
Graduate student assistant: Glenn Sidle
Large datasets exist for chemicals and their associated toxicological endpoints that were accumulated through many years of biological research. These datasets include information that can be used to build computational predictive models. In order to develop these models, a machine learning classification model has to be developed where chemicals features are used as inputs to predict toxicological endpoints. There are several hundred features that can be used to uniquely describe each chemical. The mathematical problem that this research will address will be the optimization of the predictive classification model to the most feasible set of chemical features that can accurately predict toxicological endpoints. The research will include several steps that will initially require scrapping the initial datasets to the one that includes most useful information for the classification model. Next, chemical features based on chemical structure are generated. These features are then used to develop a classification model. Finally, an optimization is conducted on the classification model to reduce the number of features to the ones that are essential in the prediction of toxicological endpoints. The outcome of this research is the development of a machine learning predictive model that can be used to efficiently predict toxicological endpoints for chemicals, based on their most informative chemical features, without having to resort to resource-exhaustive animal experiments.
Project 3: Mathematical Modeling of Dermal Absorption for Consumer Products: Is Skin Metabolism an Important Factor?
Project mentor: Marina Villafane Evans (US Environmental Protection Agency)
Graduate student assistant: Ariel Nikas
Dermal exposure may be a major route of exposure for many consumer products, some products being used on a daily basis. Typically, there is very little toxicity information available for these chemicals. The US EPA has developed a research program devoted to predict toxicity effects from high throughput (HT) in vitro assays. The number of chemicals that show toxicity at the level of current exposure is currently about 2300 chemicals. Due to the large number of chemicals involved, computational methods will play a major role in dermal absorption predictions. One of the important questions remains whether the chemicals penetrate the skin, making the chemical available for general circulation inside the body. Mathematical modeling has mainly used diffusion for the in silico calculation of dermal parameters like permeability and lag time for penetration. Literature data is being searched to obtain as many dermal parameters for as many chemicals as possible. However, skin metabolism may also contribute to clearing chemicals and preventing them from entering the circulation. Current dermal models do not usually include skin clearance by metabolism. The task of this project is to add clearance to current dermal models being developed for HT absorption calculations. Literature searches will be performed to include potential enzymes involved in metabolism as chemical diffuses through dermal compartments. A method for quantifying clearance for dermal absorption will be an important addition to current dermal models.
Participant Background, Requirements and Selection
Participants are expected to meet the following criteria:
- Citizen or permanent resident of the United States or its possessions
- Full-time undergraduate mathematics major as of September 2014
- Committed to devote their full time to the program and not engage in any other course work or employment during the program
Participants will be selected on the basis of demonstrated mathematical creativity, motivation and good work habits as well as meeting the above requirements, as determined from the application materials and recommendation letters.
Week 1: REU Workshop on modeling. Reception with REU students and faculty.
Week 2: Introduction to projects and mentors. Project teams are determined and begin to work on projects.
Weeks 3–9: Work on projects. Progress reports are due each Friday. Every other week there will be presentations given by each group. In addition there may be seminars on:
- mathematics related to the student projects
- research ethics
- applying to graduate school
- how to give poster presentations
- how to give research talks
Week 10: Students complete their final reports and do poster presentations of their work.
Extracurricular activities may include weekly teas, organized game and movie nights, a trip to see the AAA Durham Bulls play a baseball game, as well as an excursion to the beach. The North Carolina beaches and North Carolina mountains are within 2 to 4 hours drive from Raleigh.
All applicants will be notified by email about the completeness of their application a couple of days after the deadline date. Unless previously notified, a final notification that the search is closed will be emailed after all positions have been filled and confirmed (this could take a month). If you have any questions about the status of your application, especially if you are trying to make a decision on accepting another summer position, please email the program director who will be happy to send you a prompt response.