Undergrad Research

IOE Project 1 (For 1-2 students)

Data analytics for variation pattern monitoring, prediction, and diagnosis

Faculty Mentor(s): Judy Jin jhjin@umich.edu

research mode: In-Lab

Prerequisites:

Knowledge about Statistics and Machine Learning methods, familiar with Matlab, R or Python computational programming language

Project description

This project is to analyze multisensor signals and 3D point cloud data for quality variation pattern analysis and root causes diagnosis, which include feature extraction, data pattern modeling and prediction, and root causes inferences.

IOE Project 2 (For 2-4 students)

Computational Cognitive Modeling

Faculty Mentor(s): Yili Liu yililiu@umich.edu

research mode: In Lab, Online, Remote, Hybrid

Prerequisites:

Python programming skills

SURE students will work with Professor Yili Liu and graduate and undergrad students to develop and test computational models of:

• cognitive human performance and human-machine interaction
• human-automation interaction
• and/or human-robot interaction.

Excellent Python programming skill is essential; experience with SimPy, TkInter, MatPlotLib is important. Course work in IOE474 simulation is desirable though not necessarily required depending on the students’ other skills and backgrounds.

IOE Project 3 (For 1-4 students)

Cultural Aspects of Systems Engineering and Design

Faculty Mentor(s): Yili Liu yililiu@umich.edu

research mode: In Lab, Online, Remote, Hybrid

Prerequisites:

None specified

Project description

SURE students will work with Professor Yili Liu and graduate and undergrad students to study some cultural issues in systems engineering and design through literature review, data collection and analysis, and/or model/software development, and/or controlled lab experiments. Proficiency in two or more languages (I mean human languages for this project, not Python or Cobra…) is highly desirable, though not necessarily required, depending on the student’s other experiences. Meticulous attention to details, high level of motivation and creativity, and excellent writing and data organization skills are essential. Excellent GPA and strong cultural interests and experiences are desirable.

IOE Project 4 (For 1-2 students)

Applications of Industrial Engineering to Medical Decision Making and Strategic Healthcare Planning

Faculty Mentor(s): Mariel LAVIERI LAVIERI@umich.edu

research mode: Remote, Hybrid

Prerequisites:

None specified

Project description

My research team addresses a variety of questions related to the development and application of Industrial Engineering methodology to support medical decision making and other healthcare decisions. Sample questions investigated include: how to decrease the gap between supply and demand of organs for transplantation and how to monitor and treat patients suffering from chronic conditions. These questions are addressed both from a patient’s and a system’s perspective.

The student(s) involved in this research will support model development, validation, and implementation, potentially including (but not limited to):

• literature searches
• data gathering/data mining
• performance of statistical analysis
• development and coding of algorithms
• development of simulation and/or other operations research models
• validation of findings
• development of user-friendly tools to implement findings (through possibly web-based applications)

IOE Project 5 (For 1 student)

Soccer Analytics

Faculty Mentor(s): RAED AL KONTAR alkontar@umich.edu

research mode: In Lab

Prerequisites:

None specified

Project description

Analyzing Soccer Data

IOE Project 6 (For 1-2 students)

Trust-driven human-robot interaction

Faculty Mentor(s): X. Jessie Yang xijyang@umich.edu

research mode: In Lab, Hybrid

Prerequisites:

None specified

Project description

The use of autonomous agents to assist human performance is growing unprecedentedly. As the capabilities of autonomy advance, it would function as a full-fledged team member to perceive and analyze information, make decisions, and execute actions. For the human-autonomy/robot team to perform optimally, appropriate trust should be established between the two partners. This research aims to model trust between humans and autonomous agents and facilitate human-autonomy interaction.

IOE Project 7 (For 2-4 students)

APPLIED OPTIMIZATION PROJECTS AT THE CENTER FOR HEALTHCARE ENGINEERING AND PATIENT SAFETY

Faculty Mentor(s): AMY M COHN amycohn@umich.edu

research mode: In Lab

Prerequisites:

None specified

Project description

The Center for Healthcare Engineering and Patient Safety (CHEPS) brings together multi-disciplinary teams to improve healthcare delivery and patient experiences. As a student researcher, you will contribute invaluable skills and knowledge to help ensure project success. We will work on the application of modeling and operations research techniques to applied, real-world problems. Prior projects have included work in transplant surgery, emergency medicine, and precision health. Students will have the opportunity to work with a wide variety of other students as well as experts from the application domains (e.g. physicians, nurses, clinical managers). Dependent on funding, there may be the opportunity to continue the position into the next academic year.

Desired Qualifications:

• Interest in applying IOE to healthcare
• Ability to manage a project and supervise a project team
• Strong communication skills
• Interest in working in a multi-disciplinary collaborative environment

Student employees at CHEPS:

• work closely with faculty and other students from many different backgrounds
• learn about complex systems and how different people view and contribute to healthcare
• get hands-on experience in a wide range of clinical environments
• contribute skills and knowledge while learning from others

IOE Project 8 (For 1 student)

Soccer Analytics

Faculty Mentor(s): ALbert Berahas aberahas@umich.edu

research mode: In Lab, Online, Remote, Hybrid

Prerequisites:

None specified

Project description

In this project we will be working with the Men’s and Women’s University of Michigan soccer teams. The goal is to do data analytics for the team and help them prepare for the Fall 2024 season.