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Undergraduate Research Program

The IMSE Smart Cities Undergraduate Student Research Program offers industrial engineers the opportunity to work directly for and with faculty on current research projects.  The Smart Cities initiative looks at ways to use advanced technologies, data, and communication to improve the quality and cost effectiveness of urban goods and services delivery.  Some possible projects include designing green buildings, improving diagnosis of Alzheimer's disease, and improving the design of complex systems.

Dallas Skyline

The program matches students with faculty and their research teams based on specific research interests.  Appointments as undergraduate research assistants are for one to two semesters.  Students will work directly with their faculty and graduate mentors and will be required to participate in the IMSE undergraduate research symposium at the end of the spring semester.  

Benefits to students: 

  • Gain experience in the research process, including: literature review, problem formulation, data collection and analysis, assessment, writing, and presenting;
  • Learn in-depth knowledge about areas of interest;
  • Interact directly with faculty, graduate students, and upper classmen, building a professional network; and
  • Earn money.

Students apply the semester they would like to participate.  They indicate their areas of interest and can apply for specific openings if appropriate.  Applications are uploaded where faculty can determine whom they’d like to meet.  The faculty will then interview candidates and make offers.

DFW Airport

During the semester of research, students report directly to their faculty mentor.  They meet with their mentor each week, and with other students (undergraduate and graduate) working on the same project as needed.  Assignments are for 5-10 hours/week, depending on the position.  Students receive reviews from faculty mentors at mid-term and the completion of the assignment (minimum).  Students also meet with the Undergraduate Research Program student group 2-3 times/semester.

Guidelines for Students:

  • Applications are submitted through the form below.  Students must submit a 1-page resume with their application.
  • If there is no match for a student with a faculty member, students can apply in future semesters.
  • Approximately 4-8 students will be matched with research projects during each semester.
  • Students must present findings at the end of the spring semester.
  • Students will earn $10/hour, and will have appointments of up to 10 hours/week, 100 hours/semester.

Applications are closed for the Fall semester.
Decisions should be made by Monday, Sept. 28.

Project Opportunities

  • Smart Cage: Automatic Behavior Assessment Using Statistical and Data Mining Techniques with Dr. Shouyi Wang
    • The study in this project will contribute to an intelligent decision-making system to achieve automated behavioral assessments of mouse models, which can be useful to relieve the bottleneck of mouse experiments in various new drug and pre-clinical studies.
  • Improving Diagnosis of Alzheimer's Disease Using Pattern Analysis of Brain Imaging Data with Dr. Shouyi Wang
    • The goal of this project is to investigate and implement some new computational methods or algorithms into the current pattern classification framework to improve the diagnostic performance of Alzheimer's Disease using fMRI brain imaging data.     
  • Directed Brain Network Modeling Using Time Series Casualty Analysis with Dr. Shouyi Wang
    • This project will help facilitate brain network analysis and will contribute a brain state identification framework, which can help neurologists to identify dysregulated functional connectivity and gain a greater understanding of the brain networks associated with some brain diseases. 
  • Intelligent Urban Parking System with Dr. Brian Huff
    • This undergraduate research project will develop the requirements for an intelligent parking system designed to direct system subscribers to suitable parking locations based on the real-time utilization of the parking resources in the system.  Once a set of requirements have been proposed, the undergraduate researcher will perform a functional analysis of a potential Intelligent Parking System that can reduce the time users spend searching for available parking and increase the utilization of the most desirable parking resources.
  • Smart Ground-Based Urban Search & Rescue with Dr. Brian Huff
    • This research project will investigate the use of unmanned ground vehicle (UGV) systems to search for simulated victims within a mock emergency environment.  The Undergraduate Researcher will assist in the design, fabrication, and testing of various UGV system configurations.  These different configurations will include various levels of system capabilities and complexity.  The student will also help design the mock emergency test environment.  A series of tests will be designed which will allow different UGV capability configurations to be evaluated within the test environment.  These tests will help UGV designers select the most appropriate UGV technologies for Urban Search & Rescue. 
  • Data Mining, Modeling, and Decision Making (DMD) from Real-World Behavioral Data with Dr. Aera LeBoulluec
    • This project will develop analytical solutions that address clients’ real marketing problems. The data needs cleansing, merging, data-creation and algorithm-implementation.  In addition, we provide novel analytic insights in relation to the client’s business domain and needs, algorithm implementation, etc.
    • The research will focus on better understanding the challenges related to diabetes patient self-management and patient monitoring as well as to help to identify options and perform tradeoffs between these options for self-management and monitoring. This is a complex systems problem given the various stakeholder requirements and expectations that must be balanced and the need to architect an effective solution within a situation that has various constraints.