Irish Students

About the REU Program at Notre Dame

Undergraduates from Dublin City University, the National University of Ireland, Galway, Trinity College Dublin, University College Cork, and University College Dublin who are in the STEM disciplines and seeking to further their research abilities may pursue the summer Research Experiences for Undergraduates (REU) program at the University of Notre Dame.

The program lasts approximately 10 weeks over the summer. Students will receive a generous stipend for travel and living expenses.

Areas of Research

The University of Notre Dame offers several programs of research as part of this program.

More information on the programs that are available can be found at the following links:

Additionally, there are some Naughton-specific research programs available, as follows:

Prof. Patrick Fay
Title: Millimeter-wave Device Characterization and Modeling
Description: Millimeter-wave devices are increasingly important for communications, sensing, and other applications. This project will involve the student in measuring high-frequency millimeter-wave devices (from DC to 170 GHz) and developing a model suitable for circuit design based on these measurements. It is anticipated that the student will gain first-hand experience with DC measurement, measurements using mm-wave network analyzers, data analysis, and cad tools for circuit design.
Preferences: Students in electrical engineering or closely-related disciplines are preferred. Familiarity with RF/microwave software toolsets (e.g. Keysight ADS, NI/AVR/Cadence Microwave Office, etc.) is a plus but not required. Prior experience with vector network analyzers or semiconductor device probing is also a plus but not required.

Prof. Maria Holland
Title: Comparative neuroanatomy in non-human primates: segmentation and analysis
Description: Non-human primate brains exhibit a wide variety of shapes and sizes; however, they also bear significant resemblance to each other, likely stemming from universal physical laws. Through the establishment of a large library of three-dimensional brain surfaces from a wide range of non-human primate species and analyzing their morphology, we aim to shed light on the physical laws that govern brain development.
Expectations: Segmenting MRI images and reconstructing three-dimensional cortical surfaces is a time-consuming and demanding process. Using a collection of technologies promises to make this process more efficient. REU students will be expected to explore new technologies and modify code to aid in the segmentation and reconstruction process. They may also be involved in analysis of the resulting surfaces.
Preferences: familiarity with Python, background in mechanical engineering or neuroscience or computer science

Prof. Ed Kinzel
Title: Additive Manufacturing of Glass and Optical Materials
Description: The properties of glass are unique and highly advantageous for a number of engineering applications. These properties make glass challenging to form using conventional additive manufacturing techniques. We have created a filament-fed laser-heated technique, termed Digital Glass Forming (DGF), to print both optically-smooth, continuous transparent forms as well as free-standing complicated structures including trusses and tube networks. This has applications ranging from near-net manufacturing of free-form optics to integrated opto-fluidic devices. There are many opportunities to continue to improve the process including material handling, integration of pneumatics, in-situ optical characterization, continuum modeling of the process, improving feedback control, and understanding the thermal transport during printing, in addition to studying how to create functional devices. 
Expectations: There are currently several potential directions for students to explore. These include improving feedback control using a thermal camera and spectrometer, implementing computer-controlled pneumatics, developing new tool paths and procedures for pathing, improving the tube deposition process, and integrating metal seals.
Preferences: Students in mechanical, electrical, and materials science students as well as physics or optics-related disciplines. Laboratory experience, CAD, and/or familiarity in programming will be helpful.  Experience working with lasers/optics would be very welcome. 

Prof.  Yahya Kurama
Title: Seismic Testing of a Precast Concrete Buckling Restrained Brace Element
Description: To conduct large-scale laboratory experiments of a new diagonal brace element for seismic-resisting precast frames.
Expectations: Student will assist in hands-on work in the laboratory, including casting of concrete, erection of specimens, loading, sensor instrumentation, testing, and data acquisition/analysis
Preferences: Students must pursue an undergraduate degree program in Civil Engineering (with Structural Engineering emphasis). Students in a Mechanical Engineering program will also be considered.

Prof.  Yasemin Ozkan-Aydin
Title: The role of tail flexibility in the movement of a quadrupedal robot
Description: Terrestrial animals demonstrate a unique performance in using multiple propulsion elements (limbs and trunk) to generate thrust in a variety of environments [1,2]. Inspired by biology, several terres trial robot models that use animal locomotion techniques to solve real-world locomotion problems were developed [3–9]. For example, previous studies show that adding tails to legged robots would aid in locomotion (such as helping the robot adjust its airborne orientation or speed) and enhance their agility and versatility in complex environment [10–13]. However, when systems have joint limits, their ability to locomote depends on how effectively they can change their interaction with the environments during a gait cycle (a pattern of limb actions that an animal uses repetitively during locomotion). In this project, we aim to understand the principles of dynamics and control that couples legs’ motion with a body and tail motion. First, we will develop a low-cost, 3D printed quadrupedal robot with a flexible tail that propels itself around the world, similar to the capabilities of natural systems. In particular, we will focus on how a tail with passive and active stiffness facilitates the robot’s stability in a variety of environments, including a granular substrate and rough terrain where the system is intermittently in contact with the ground. The outcomes of this research will greatly advance the design of innovative robots, especially soft robots, that can navigate through the real world.
Expectations: The first expectation from an REU student is to build a 3D printed-legged robot under the guidance of the PI. The robot will be similar to the robots used in the previous study [9]. Using Arduino based controller, the student will learn how to program different gaits that allow the robot to walk on various terrains. The student will then design a flexible tail with different geometries and actuation mechanisms and test them on the robot. The student will test the performance of the robot through laboratory experiments. At the end of the program, the student will write a short research paper in a conference paper format.
Preferences: Electrical or Mechanical Engineering students with experience in Arduino programming and CAD design (such as Solidworks) are welcome.

Prof.  Chaoli Wang
Title: AI+VIS
Description:  Design and implement AI-enabled visualization and analytics programs to analyze and understand a wide variety of data (e.g., scientific simulation data, learning analytics data).
Expectations:  REU students will participate in the research projects and help to develop the prototype implementation that eventually leads to publications.
Preferences:  Basic deep learning and/or graphics and visualization knowledge, familiar with programming (PyTorch, OpenGL/GLSL/WebGL, D3.js) or visualization tools (ParaView, Tableau).

Prof.  Jianxun Wang
Title:  Physics-informed Artificial Intelligence for Fast Hemodynamic (Blood flow) Modeling
Description:  Optimization and uncertainty quantification have been playing an increasingly important role in computational hemodynamics. However, existing methods based on principled modeling and classic numerical techniques have faced significant challenges, particularly when it comes to complex 3D patient-specific shapes in the real world. First, it is notoriously difficult to parameterize the input space of arbitrarily complex 3-D geometries. Second, the process often involves massive forward simulations, which are extremely computationally demanding or even infeasible. We propose a novel deep learning solution to address these challenges and enable scalable geometric uncertainty quantification and optimization. Specifically, a statistical generative model for 3-D patient-specific shapes will be constructed based on a handful of available baseline patient geometries. An unsupervised shape correspondence solution is used to enable geometric morphing and a compact geometric design space can then be constructed by the statistical generative shape model. In order to build a fast forward map between geometric input space to the solution space of functional information, we propose a supervised deep learning solution, which will facilitate shape optimization and uncertainty quantification analysis in a massively scalable manner.
Expectations:  REU students will work closely with my graduate students on medical image segmentation and computational fluid dynamics (CFD) simulations.
Preferences:  Mechanical engineering or computational mathematics. Preferred lab skills: Computational fluid dynamics (CFD).

How to Apply

Naughton Fellowships for undergraduates are awarded by nomination from faculty advisors. Interested students should speak with their faculty supervisors for more details. 

All faculty supervisors must submit their student nominations to no later than the defined deadline.


Applications will open Monday, November 1, 2021.

Applications are due by 5:00 p.m. Eastern on Friday, February 18, 2022.

Selection Criteria

The selection of the Naughton Fellows will be administered by the Naughton Fellowship Committee, with the University's diversity statement in mind.

Significant importance and preference will be given to those candidates who demonstrate academic excellence. However, the committee will consider several criteria, including:

  • the interest, ability, and potential of the candidate to study their chosen field;
  • the candidate’s capacity to successfully complete the program of study; and
  • the candidate’s desire and ability to serve as a cultural ambassador abroad.

Candidates must have at least one year remaining in their undergraduate program in order to be considered.


The onus is on the candidate to complete the appropriate application form to demonstrate the degree to which he/she meets these criteria.

General Terms and Conditions

Each recipient must complete a summary report of his/her research accomplishments at the end of the program and give a presentation at the University's undergraduate research fair.


For questions about the REU program at Notre Dame, please contact