This is a list of research projects that may have opportunities for undergraduate students. You can browse all the projects, or view only projects in the following categories:
Educational Research/Social Science
Constructing Large Scale Representative Social Networks
|Research categories:||Bioscience/Biomedical, Computational/Mathematical, Computer Engineering and Computer Science, Educational Research/Social Science, Industrial Engineering, Life Science, Physical Science|
|Desired experience:||At least one student with object-oriented programming, data structures, algorithm analysis, as well as familiarity with at least basic discrete mathematics, statistics and probability (graph theory, distributions, hypothesis testing, regression, etc). Experience using MPI/parallel computation would be highly advantageous, but not necessary. Familiarity with Linux and R would also be useful. A student with a background in epidemiology or applied mathematics would also be very strongly considered.|
|Number of positions:||1-2|
Facebook, Twitter, Orkut and LinkedIn are well known examples of cyber-social networks. However, social networks obviously exist outside of that domain and can represent the connections we make with the people around us. Unlike cyber-world social networks where the connections people make are fully known and observable, real-world networks must be inferred from limited statistical information as well as reasonable assumptions about human behavior. In both instances, a representative social network allows for the study of not only the network topological properties but also diffusive processes acting upon it, such as information spread, influence, disease, etc. There exists a gap in our ability to reconstruct real-world networks from partially observed, noisy and limited data.
This project will aid in developing efficient and scalable algorithms for constructing real-world social network representations at different scales and abstractions (up to global). An extensive literature review of existing capabilities and known social behaviors/mixing patterns will be conducted as part of the project, as will data acquisition and analysis.
Evaluating the Maintenance and Diffusion of Water Conservation Best Management Practices in the Great Bend of the Wabash River Watershed
|Research categories:||Agricultural, Educational Research/Social Science, Environmental Science|
|School/Dept.:||Forestry and Natural Resources|
|Preferred major(s):||no strong preference|
|Desired experience:||Prior experience with or knowledge of appropriate and sustainable water resource best management practices (BMPs) such as rain gardens and rain barrels a plus. Experience with outdoor field work also a plus.|
|Number of positions:||1|
This project will characterize the adoption, maintenance and diffusion of water quality and climate change BMPs in the Region of the Great Bend of the Wabash River Watershed (Tippecanoe County). The project has three primary objectives. First, it will determine what motivates urban and suburban landowners to adopt and maintain stormwater conservation BMPs. Second, it will identify how stormwater conservation BMPs spread or diffuse throughout a community. Third, it will determine specific watershed management planning recommendations for setting adoption goals and reaching potential adopters for the Wabash River Enhancement Corporation (WREC), an environmental non-profit organization working in the Region of the Great Bend of the Wabash River Watershed.
To understand what motivates the adoption and maintenance of these BMPs in this watershed, an assessment of both the property owner/manager and the actual practice will be conducted. The SURF student will aid in the assessments of the actual practices. Implemented projects will be photo-monitored by the student to document project maintenance and physical assessments of the BMP will be conducted. These physical assessments will include the quality of practice implementation, plant growth and cover assessment, erosion or compaction issue identification, and notation of any issues or problems with the BMP that may reduce its effectiveness.
Global Engineering Competency: Definitions, Development Paths, and Situational Assessment
|Research categories:||Educational Research/Social Science, Other|
|Desired experience:||Engineering and non-engineering students encouraged to apply. Previous coursework and/or experience in relevant social science fields (e.g., education, psychology, sociology) preferred but not required.|
|Number of positions:||1|
In a time of intensified globalization, engineering educators and employers face the formidable task of preparing engineers to be more effective in diverse national and cultural contexts. Responding to this challenge, our current research aims to: 1) generate a robust definition and developmental theory of global engineering competency, and 2) create a high quality situational judgment test (SJT) that can be used to assess multiple dimensions of global engineering competency. The undergraduate research assistant assigned to this project will contribute directly to this ambitious and exciting work, including by supporting analysis and reporting of quantitative and qualitative data collected through survey instrument pilots and expert interviews. The student selected for this position will also have ample opportunities to be mentored by and learn from both the lead faculty investigator and members of his large and vibrant research group, the Global Engineering Education Collaboratory (GEEC).