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Students Across the Country
We work with talented high school, undergraduate, graduate, and post-doctoral students from various institutions across the country. As a research university, part of our mission is to educate and mentor students in all phases of their academic careers. They bring fresh perspectives and invaluable insights to our work, while their experiences help prepare them for their future careers. In short, they help us get the job done.
Here are a few examples of ways we’ve worked with a variety of students in 2024.
K–12 students
We regularly give tours to groups of local junior high and high school students, such as the one pictured above.
Andrew Chen, summer high school intern, worked with human models and figured out how to animate pedestrians in Unreal Engine (not pictured).
The FIRST Tech Challenge, shown here, is a high school state robotics competition held in our area each year. Chris Schwarz, our director of engineering and modeling research, is a volunteer judge.
Undergraduate students
Grant Ernst and Kenneth Reichert, both mechanical engineering majors, University of Iowa
Ernst (pictured here) and Reichert both assisted in the assembly of miniSims. Ernst is shown working on a minSim cab for the University of California, Irvine. He helped with the build, installed the braking system, and made various electrical connections.
Matthew Wu, electrical engineering major, University of Alabama
Wu converted virtual vehicle models to Unreal Engine, a game engine that provides more trueto-life renderings of our virtual environments. He updated wheels, vehicle lights, and surface reflections for more realistic simulations.
Faythe Evans, clinical psychology major, University of Iowa
Evans, shown here with staff design engineer Alec La Velle, worked on building and troubleshooting scenarios for the simulator and learned about our research process. In our scenario development tool, she learned to create merges onto an interstate, lane changes, and changes in speed limits.
“I’m getting a lot more familiar with research working here,” Evans said. “I’m gaining experience working with data, with variables ... and just learning the research process will definitely help me after graduation and allow me to apply that knowledge to other roles.”
Annika Veit, biology major, Luther College
Veit researched advanced driver assistance systems on specific makes and models, looking up safety feature warnings, blind spot warnings, collision mitigation, human machine interfaces (HMIs), etc.
Irene Agusti, mathematics major; Brad Carlton, mathematics and economics major; and Minh Nguyen, computer science major, Grinnell College
This experience has significantly enhanced my prospects for a career in machine learning or data science, and it has broadened my perspective on the practical applications of my technical skills in a real-world research environment.
—Irene Agusti, Grinnell College
A small group of Grinnell College students used machine learning (ML) models on data from some of DSRI’s cannabis and alcohol impaired driving studies. They were mentored by Grinnell assistant professor Ryan Miller and DSRI’s director of drugged driving research Tim Brown.
“Being able to partner with DSRI is tremendously valuable to have that data for our students to work with,” said Miller. “Many of our students are aspiring to get jobs where they need to show that they’ve worked with large, complex data sets.”
In their first project, the students aimed to assess ML models meant to identify drivers who were impaired based on vehicle behavior, focusing on determining which factors are important in identifying impairment such as the type of input (lateral position, speed, etc.), method of summarization (mean, range, rolling range, etc.), and measurement duration.
In their second project, they looked at data augmentation approaches to improve the training of ML models meant to identify impaired drivers. By overcoming the challenges associated with a lack of labeled impaired driving data, they were able to improve the performance of these models on new, unseen data.
The students themselves coded, ran experiments on PCs, analyzed data, discussed results, planned next steps, and assisted with decision-making and writing.
Graduate students
Jimin (Joy) Kim, University of Iowa
Kim completed her PhD from the University of Iowa Department of Industrial and Systems Engineering in the spring of 2024. She is shown here with her advisor and DSRI director Dan McGehee.
Her main research focused on the safety concerns surrounding the transfer of learning and knowledge gaps around new vehicle technologies.
She is now a postdoctoral research associate at the University of Wisconsin-Madison, working on enhancing drivers’ mode awareness while using driving automation.
Haolan (Lan) Zheng, PhD student, University of Florida
Zheng is working with DSRI researcher Justin Mason and exploring the effects of training on drivers’ understanding and use of adaptive cruise control (ACC).
He has taken a systematic approach to developing and providing training to drivers to better understand the ingredients included in the training material and thus better understanding the effects of training on ACC use.
