Department of Mathematics, Duke University, and
Information Initiative at Duke (iiD)

11 342Program ID: Duke-DATA [#342]
Program Title: Data+ 2015
Program Type: Undergraduate program
Program Location: Durham, North Carolina 27708-0320, United States [map]
Subject Area: Interdisciplinary
Application Deadline: 2015/02/20 finished (posted 2014/12/07, updated 2015/09/27, listed until 2015/06/07)
Program Description:    

*** this program has been closed, and no new applications will be accepted. ***

The Data+ program is a nine-week undergraduate summer research experience. It is open to all Duke undergraduates in good standing.

Participants will receive a $5,000 stipend, out of which they must arrange their own housing and travel, as part of a Research Training Grant issued by the NSF, with matching funds provided by the Information Initiative at Duke (iiD) and the Social Science Research Institute (SSRI). The program runs from May 18 until July 25, 2015. The application deadline is Feb. 20, 2015, but we will evaluate applications on a rolling basis as they come in, so please apply as soon as you know that you're interested.

Students work in small teams (2-3 undergraduates per team) on data-driven, interdisciplinary projects, but they do so in a communal environment with about 10 other teams working in an extremely diverse set of subject areas. It is our hope that students will be able to both work deeply into their specific project and get a very broad picture of most of the skills needed for modern data science.

Here are the projects planned for summer 2015 (more will be added over the next month). Click on the links to read more about each project. Please indicate the number of the project you choose when you apply.

1) Gerrymandering : This project is about congressional district boundaries, and the different state-by-state processes that lead to their creation. The goal is to understand the effect of these processes on actual election results.

2) Prolific Pigs? : Two undergraduate students will spend 9 weeks studying historical archives and building a model to predict the price of pigs, relative to a number of interesting factors. Students with an interest in historical data reconstruction, and a basic familiarity with introductory statistics are encouraged to apply.

3) What Makes a Good Reservoir? : This is a project about water reservoirs, involving data curated by the Nicholas Institute at Duke. It should be of interest to students from a wide variety of backgrounds, including environmental science and/or policy, mathematics, and statistics. The team will be lead by Alireza Vahid, and Lauren Patterson will facilitate from the Nicholas Institute.

4) Shape-based Distances Between Bones : Next summer, two to three undergraduates will join a research group led by Douglas Boyer and Ingrid Daubechies, with the goal of testing and developing mathematical and statistical methodology for measuring similarities between bones and teeth. The project will be of clear interest to students from biology, evolutionary anthropology, mathematics and statistics. People with an interest in data visualization techniques are also encouraged to apply.

5) Challenges from Duke MOOC Data : The goal of this project is take a large amount of data from the Massive Open Online Courses offered by Duke professors, and produce from it a coherent and compelling data analysis challenge that might then be used for a Duke or nation-wide data analysis competition. A key component of this project will be learning how to prepare a proposal for IRB approval.

6) Risky Decision-Making : This project is about how personality traits predict how people make risky decisions. The goal is to build a powerful predictive model of behavior. Students with an interest in brain sciences and machine learning are encouraged to apply.

7) Interactive Environmental Data This project is about interactive data visualization. Two undergraduate students will develop data applications on multiple topics for use in introductory environmental science courses. Students with an interest in data wrangling and web visualization are encouraged to apply.

8) Quantifying the Science-Humanities Gap This project will use bibliometric data to help quantify the relationship between published work in the sciences and in the humanities

9) The Geometry of Weather This project will explore novel geometric, topological, and statistical methods for understanding powerful weather phenomena. Students with an interest in physical systems, geometry/topology, and/or scientific computing are encouraged to apply.

10) Food Choices and Behavorial Economics This project is about behavioral challenges posed by the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). Three students are invited to join a team, led by Prof. Matt Harding, that will use a large collection of WIC transaction data to understand how the choices made by program participants, retailers, and program operators translate into outcomes, including program costs, amount of participation, and level of satisfaction.

11) Documenting Data+ We think this summer's experience will be an amazing one, and we are looking for two students to make a documentary about it, under the guidance of Prof. Bruce Orenstein, artist in residence at the Center for Documentary Studies.

12) Solar Power Estimation through Remote Sensing This project team will examine an enormous collection of imagery data provided by the U.S. Geological Survey, and will use cutting-edge image recognition in an effort to detect the location of rooftop solar panels. These results, in combination with U.S. meteorological data, will allow an estimation of the total rooftop solar energy production in the country. This team will work heavily with Kyle Bradbury and other researchers at The Energy Initiative.

Application Materials Required:
Submit the following items online at this website:
And anything else requested in the program description.

Further Info:
Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320

© 2017 MathPrograms.Org, American Mathematical Society. All Rights Reserved.