Electrical and Computer Engineering REU

Research Experiences for Undergraduates – or REU – brings students from around the world into the research laboratories of the Department of Electrical and Computer Engineering each summer. These students work with a faculty member and their research group to tackle an innovative research project. Students admitted to the program receive a competitive monthly research stipend as well as arranged on-campus housing and a travel allowance. 

When to Apply

Applications are due in January.


Domestic and international students are invited to apply. The program is designed for students who are juniors in the spring before their REU summer, but exceptional sophomores will also be considered. Students should be majoring in ECE or a related discipline relevant to their area of research interest.

Dates and Stipend

  • Applicants will be notified of decisions no later than February 15
  • Dates for the summer 2016 REU: Sunday May 29, 2016 to Saturday, July 30, 2016
  • Stipend: $4,500
  • Travel: Up to $400 domestic travel, up to $800 international travel
  • Housing: Shared apartments are provided in Duke’s Central Campus Apartments

Research Opportunities

The following projects were available in 2016. Questions about any of the projects or the REU program in general should be directed to Amy Kostrewa (amy.kostrewa@duke.edu).

Heterogeneous Datacenter Design and Deployment

Demand for computing capacity is driven by the data deluge. Over the past 45 years, computer engineers have transformed exponentially increasing transistor density into exponentially increasing capacity. At present, energy costs jeopardize further scaling. The U.S. Environmental Protection Agency estimates datacenters already consume 1.5 percent of total nationwide electricity—comparable to the consumption of 5.8 million U.S. households. No combination of existing datacenter architectures can improve computing capacity by the desired three orders of magnitude within datacenter power budgets, which are already at megawatt scales.

This project examines the design and deployment of heterogeneous datacenter architectures that improve efficiency by 10x. Heterogeneity deploys a mix of specialized hardware for a mix of software needs, improving efficiency as unnecessary hardware resources are eliminated. To build heterogeneous datacenters, we explore design spaces for processors, memory, network, and storage using techniques in statistical inference and machine learning. To deploy heterogeneous datacenters, we use multi-agent markets in which applications bid for heterogeneous architectures, maximizing utility.

REU students participating in this project may participate in data collection and analysis. Responsibilities may include (1) analyzing performance and power for a variety of processor and memory designs, (2) simulating future processor and memory designs, and (3) performing data analysis and design optimization. While not required, some knowledge in computer architecture and a major programming language (e.g., C, C++, Java) is helpful.

Faculty contact: Dr. Benjamin Lee (benjamin.c.lee@duke.edu)

Materials and Device Characterization of Organic Solar Cells Deposited by Resonant-Infrared Matrix-Assisted Pulsed Laser Evaporation (RIR-MAPLE)

RIR-MAPLE is an organic-based thin-film deposition technique appropriate for polymeric optical coatings (such as anti-reflective coatings) and organic optoelectronic devices (such as solar cells). RIR-MAPLE is expected to improve the device performance of organic solar cells due to nanoscale domains of donor and acceptor materials that enhance charge separation of photogenerated excitons.

In this project, the student will investigate the materials properties and device performance of organic solar cells deposited by RIR-MAPLE using atomic force microscopy, UV-visible absorption spectroscopy, photoluminescence spectroscopy, external quantum efficiency and solar cell fill factor measurements.

Faculty contact: Dr. Adrienne D. Stiff-Roberts (astiff@ee.duke.edu)

Improving Contact Interfaces to Nanomaterials for Nanoelectronic Transistors

Nanomaterials offer considerable advantages over traditional bulk materials for next-generation electronic devices.  In particular, field-effect transistors (FETs) used for high-performance computing must be able to operate at low voltages and sub-20 nm dimensions.  Carbon nanotubes (CNTs), 2D transition metal dichalcogenides (TMDs), and graphene are the most promising nanomaterials for implementation into FETs.  One of the foremost challenges for such nanoelectronic transistors is the prohibitively high contact resistance, which results from poorly understood/controlled electron injection at the metal contact-nanomaterial interface that ultimately limits voltage scaling.

In this project, the interface between the metal source/drain contacts to certain nanomaterials will be modified to improve carrier injection.  Using a custom materials deposition system that includes electron-beam evaporation (e-beam evap) and a broad beam ion source, novel contact interfaces will be fabricated and characterized.  The student involved in this project will use this custom deposition tool to study the impact of preconditioning nanomaterial surfaces with a low energy ion beam prior to (and during) e-beam evap of contact metals.  The impact of the ion beam surface preparation will be studied using materials characterization tools, including Raman spectroscopy and atomic force microscopy.  In addition to performing this fabrication of custom contact interfaces to nanoelectronic devices, the student will also be trained on a low-temperature probe station and will characterize the FET devices to extract information regarding carrier transport behavior and overall device performance.  The student will also be expected to take part in discussions where results will be analyzed and new ideas potentially formulated for inclusion in the project.

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 nanoelectronics and nanofabrication, 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.

Faculty Contact: Dr. Aaron Franklin (aaron.franklin@duke.edu)

Machine Society Interfaces: Live Multi-Person Tracking

For Governments and Performers there is a desire to trace the path an individual has taken through groups and society. Government motivations cover a spectrum from the beneficial, through benign, and belligerent. An Institution able to locate a lost Alzheimer's patient is also able to follow dissidents and detractors. Performers being tracked by the stage environment can influence the overall performance (music, lights, video, objects) in ways currently impossible, enabling interactive and evolutionary performances, with the added benefit of a real-time digital archive.

We are instrumenting a space (The Slippage Lab) with the core technology to investigate the state-of-the-art in live multi-person tracking to explore new research directions.             

Students can participate with MATLAB software, high definition video hardware and integration of the two into a tool for live performance.  We have been using multi core parallel processing and CUDA graphics processors to implement solutions that are real time for live performance.

Faculty Contact: Dr. Martin Brooke (martin.brooke@duke.edu)

Nano Probe Array for Molecular Imaging

We are developing an device to image nanoscale objects.  It is sort of like a CAT scan for molecules. Current status is we are testing a prototype and need help with programming and doing the tests.

You can find more information about the project here: http://bit.ly/1JWxV4s     

Tasks needed

  1. Programming using MATLAB to take the data from the probe array
  2. Data analysis to form images
  3. Setup of RF test equipment for taking data
  4. Design of final molecule probe.

 Skills Required:

  • Curiousity about molecular imaging
  • Curiousity about RF and microwave
  • MATLAB programming skills

Faculty Contact: Dr. Martin Brooke (martin.brooke@duke.edu)

​Heavy Lift Drone

We are building a hybrid powered multi rotor drone for deploying ocean sensors. The drone is based on open source pixhawk platform from 3D robotics.  We will be hacking the code to make the craft triply redundant and able to use three hybrid power gas electric generators.  You can view photos of the project here: https://goo.gl/photos/Xkazh8WxsmaQGHGW6

Faculty Contact: Dr. Martin Brooke (martin.brooke@duke.edu)

Ocean Sensor Platform Development

We are building sensors for measuring pH and Chlorophyll-a.  The sensors are low cost and based on open source hardware and software.

You may view a current presentation about the sensor here: https://drive.google.com/open?id=1EBt5xRcFg2KqvLjsKDp5F3h2aF-IylrAX6055R8DkCg 

Faculty Contact: Dr. Martin Brooke (martin.brooke@duke.edu)

Modeling Reliability of Cloud Infrastructure Software

There is a growing dependance on cloud computing: currently, many clouds are build using an amalgamation of Open-source software.  In this project, we aim to investigate the Git-Hub and bug repositories for a number of these OpenSource projects: Linux, KVM, Docker, and OpenStack. The goal is to create a taxonomy of failures across the entire ecosystem and more importantly to understand how bugs ripple across this ecosystem.  Moreover, we intend to generate failure and operation statistics for the different classifications. For example, we intend to investigate the number  The project will consist of a mixture of Natural Language processing and clustering techniques to process and create cluster of data.  The end result of this project will be

  1. a set of algorithms that take as input ‘free form’ meta-data from Cloud infrastructure bug repositories and create classifications and produce metrics for the different classifications.  
  2. a set of scripts to generate statistics about the different classifications discovered and more importantly to compare the statistics from the different classifications.

Faculty Contact: Dr. Theophilus Benson (tbenson@cs.duke.edu)

Student-Proposed REU Project

Prospective Duke ECE REU students are invited to propose a project to work on under the advisement of one of our Duke ECE faculty members. In addition to the application form and your CV, please use a format similar to the projects above to submit a proposal including the following:

  • The name of the faculty member(s) you propose to work with
  • The description of a project that can be completed within or reach a reasonable stopping point at the end of a nine-week period
  • An explanation of an expected product or outcome from the project
  • A list of any necessary supplies or materials

Staff contact: Amy Kostrewa (amy.kostrewa@duke.edu)