Research Projects for Summer 2022

Duke's Pratt School of Engineering is offering research experience opportunities across each its four academic departments:

Grand Challenge REU participants have the opportunity to conduct research across a large spectrum of interdisciplinary topics broadly organized into five areas: energy, environment, health, national security, and learning—

Five topic areas of Grand Challenges REU program

The following is a list of research projects available during the summer 2023.

More projects will be added soon.


Brain Network Based Biomarkers for Neurodegenerative Conditions  

Grand Challenge: Reverse engineer the brain

Faculty Mentor: Alexandra Badea , Assistant Professor of Biomedical Engineering

The goal of this project is to familiarize students with interdisciplinary approaches to understand the brain. The main thrust is on developing computational approaches using graph analysis and visualization of diffusion tensor imaging and derived tracts. We will use human and animal brain high resolution diffusion tensor imaging. The goal is to build predictive models to help understand human neurological conditions, with a focus on neurodegeneration, and Alzheimer's disease. The students will use R, MATLAB, or python programming for model building and graph analyses (or his /her choice of a programming language), develop deep learning approaches, and compare several options for visualizing and assessing the quality of reconstructed tractography data. The ideal candidate will possess good quantitative, analytical, and programming skills (e.g., R, python, etc.).  

For additional information, please visit  

Exploring Custom Electrical Contact Interfaces to Semiconducting Nanomaterials

Grand Challenge: Engineer the Tools of Scientific Discovery

Faculty Mentor: Aaron Franklin , Professor of Electrical and Computer Engineering

The semiconductor chip shortage recently brought to light the importance of research, development, and manufacturing in the United States. To address the future need for high-performance chips operating at reduced energies, new materials are needed beyond silicon. Nanomaterials are attractive for future electronic device applications owing to their atomic thinness and unique electrical properties. These include 1D carbon nanotubes, 2D graphene, and many other 2D crystals that are semiconducting. One of the foremost challenges for nanomaterial-based devices is the inconsistency and relatively poor performance of the contact interfaces. While there has been some progress in improving the metal-nanomaterial contacts, much work remains, and this project will explore new approaches to establishing electrical interfaces with a variety of nanomaterials. In this project, the student will perform work in the cleanroom here at Duke, learning the basics of nanofabrication and electrical characterization. Several new contact structures will be studied by fabricating transistors from the nanomaterials and then characterizing the resultant properties via electron microscopy, atomic force microscopy, and spectroscopy techniques. These material characterization results will then be correlated with electrical characterization of the devices. The student will be an active contributor to this research and be expected to take part in discussions where results will be analyzed; and new ideas potentially formulated for inclusion in the project. The student will learn: 1) the ins and outs of characterizing semiconductor devices, 2) the basics of vacuum systems, and 3) data analysis skills related to understanding nanomaterial interfaces. An ideal candidate for this project would have some previous knowledge and experience in solid-state physics including carrier transport in semiconductors, previous knowledge and/or interest in electronics, and be competent in operating complex tools. They should also be self-motivated and maintain a strong work ethic in terms of commitment and follow-through. A collaborative, team player is a must.

For additional information, please visit 

First Steps towards Expanding the Use of Energy Harvesting

Grand Challenge: Make solar energy economical

Faculty Mentor: Earl Dowell , Professor of Mechanical Engineering and Materials Science

The goal of this project is to expand the use of energy harvesting in practice by developing a computational tool based on a multidisciplinary design optimization technique that can calculate the best configuration for a vibrating structure to enhance energy extraction from an external flow. The project will focus on the design process for this technology for a given operational condition instead of defining the best-operating conditions and the geometric constraints for a given configuration, as it is mostly done in current research. This will allow the design process to be more flexible for different applications. Students working on this project develop a more in-depth understanding of the principles of structural modeling for a vibration problem due to aerodynamic excitation. They will also apply computer modeling in the design process for a mechanical system. The students will work directly with a PhD Student from the Aeroelasticity Group and will have the opportunity to interact with other members of the laboratory working on aerospace research. The ideal research candidate should be able to work as both part of a team and independently as well as demonstrate curiosity and a hard-working attitude. Interest in Structural Dynamics and Energy Generation is welcome, and previous experience with coding in MatLab/Octave, or Python, is preferred.

For additional information, please visit 

Intelligent Augmented Reality

Grand Challenge: Enhance virtual reality

Faculty Mentor: Maria Gorlatova , Assistant Professor of Electrical and Computer Engineering

Augmented reality (AR) is a rapidly developing technology area with potential for transforming many daily human experiences. While promising, current AR systems are somewhat limited in their capabilities, in particular in multi-user experiences, high energy consumption, and general lack of robustness and adaptability. The goal of this project is to obtain in-depth experimental understanding of the limitations of current augmented reality experiences, and to establish how these limitations can be addressed. Students involved in this work will experiment with developing and experimenting with different augmented reality applications, experiences, and platforms; to understand the systems and network loads of different operations, key drivers of immersive user experiences, and the potential of edge and cloud computing platforms to address the discovered limitations. The project involves both the development of Unity-based holographic experiences, and real-world holographic deployments with Google ARCore mobile device platforms and Magic Leap One headsets. The project is best suited for students who have an experimental mindset and who enjoy obtaining in-depth understanding of system performance, physical phenomena, and human behavior. Relevant technical preparation includes general software development skills, a background in communications and/or networking (preferred but not required), and familiarity in machine learning (preferred but not required).

For additional information, please visit  

Interaction of nanoparticles with cells and protein

Grand Challenge: Engineer the tools of scientific discovery

Faculty Mentor: Christine Payne , Professor of Mechanical Engineering and Materials Science

The Payne Lab is working to understand the underlying molecular mechanisms by which cells interact with nanomaterials and then use this information to control cellular properties. Recent developments in a broad range of scientific disciplines including materials science, chemistry, microscopy, spectroscopy, cell biology, and structural biology have created a unique opportunity to probe this question directly. Students in the Payne Lab draw upon these scientific disciplines for a highly interdisciplinary research experience. REU students will work closely with graduate students to sample projects of interest and learn basic lab skills. After selecting a project, they will work with the graduate student and Prof. Payne to develop their own research question for the summer. The ideal research student will be curious, hardworking, and able to work as both part of team and independently. No specific lab skills are required. Experience with python is a plus.

For additional information, please visit 

Miniature mass spectrometry for oceanography and planetary exploration

Grand Challenge: Engineer the tools of scientific discovery

Faculty Mentor: Jason J. Amsden , Associate Research Professor in the Department of Electrical and Computer Engineering

We currently have projects miniaturizing mass spectrometers for two applications. First, we have a project where we will be developing an underwater mass spectrometer to detect methane and volatile organic compounds in the ocean. In particular the instrument will be used to determine how much methane might be released from methane clathrates on the ocean floor. Second, we are developing a next generation mass spectrometer for planetary exploration that we hope one day will visit another planet! The students will have the opportunity to work with members of the group on design, fabrication, and testing of these prototype instruments. The students will work on design, fabrication, and testing of our prototype instruments. Design work will include use of Fusion 360 for CAD and electronics modeling and finite element analysis simulations. Fabrication work will involve assembling parts into functioning prototypes, and testing will involve taking data with the instruments and analyzing data using Matlab and python scripts. The students will have the opportunity to write their own data analysis scripts. The ideal candidate will have experience with python, Matlab and/or electronics along with coursework in electricity and magnetism.

For additional information, please visit  

Optimized Parameters of Brain Stimulation

Grand Challenge: Reverse engineer the brain

Faculty Mentor: Warren Grill , Assistant Professor of Biomedical Engineering

The Grill lab specializes in analysis and design of devices that use electrical stimulation of the nervous system to restore function to individuals with neurological impairment. This project focuses on analysis and design of the parameters of stimulation, for example to treat the symptoms of Parkinson’s disease or to treat chronic pain. The project will make use of computer-based modeling. Students working in this research project will develop an understanding of the principles of electrical stimulation and the application of computer modeling to study electrical stimulation. Student with interest in neuroscience and medical devices are ideal candidates for this project. The students will work directly with a PhD student and / or Research Scientist and have the opportunity to interact with a diverse group of students and staff working across a broad array of neurodevices. Previous experience with writing computer code is extremely helpful.

For additional information, please visit