Research Projects

Projects are posted below; new projects will continue to be posted through February. To learn more about the type of research conducted by undergraduates, view the 2017 Research Symposium Abstracts.

This is a list of research projects that may have opportunities for undergraduate students. Please note that it is not a complete list of every SURF project. Undergraduates will discover other projects when talking directly to Purdue faculty.

You can browse all the projects on the list, or view only projects in the following categories:



A dual-tuned, metamaterial-enhanced radiofrequency coil for MRI and phosphorus-31 spectroscopy

Research categories:  Bioscience/Biomedical, Chemical, Computational/Mathematical, Electronics, Innovative Technology/Design, Life Science, Material Science and Engineering
School/Dept.: Weldon School of Biomedical Engineering, School of Electrical & Computer Engineering
Professor: Joseph Rispoli
Preferred major(s): Electrical Engineering, Biomedical Engineering
Desired experience:   CAD modeling, soldering, circuit characterization

Magnetic resonance imaging (MRI) scanners can be used to acquire real-time localized metabolic information. This technique, known as magnetic resonance spectroscopy, can quantify the concentration of specific metabolites incorporating NMR-active nuclei. In this project, we will build a radiofrequency coil that will detect both typical proton (1H) and phosphorus-31 (31P) spectra using Purdue's 7T MRI scanner. The coil design will include metamaterial periodic structures to boost 31P sensitivity.

For this project, the SURF student will be part of the Magnetic Resonance Biomedical Engineering Lab (MRBEL) and work with Prof. Rispoli and a dedicated graduate student advisor. The SURF student's role will be to contribute to the final coil design (given electromagnetic modeling results from the graduate student advisor), to create a CAD model of the mechanical former, to prototype the former using our lab's 3D printer, to construct the required electrical circuitry on the former, and to validate the device on the 7T scanner. Familiarity with CAD software (Inventor/SolidWorks), soldering, analog circuits, metamaterials, and/or radiofrequency/microwave circuits is desired but not required.

More information:


Characterization of strain localization and associated failure of structural materials

Research categories:  Aerospace Engineering, Computational/Mathematical, Computer Engineering and Computer Science, Material Science and Engineering, Mechanical Systems
School/Dept.: School of Aeronautics and Astronautics
Professor: Michael Sangid
Preferred major(s): AAE, MSE, ME, CS

The research we do is building relationships between the material's microstructure and the subsequent performance of the material, in terms of fatigue, fracture, creep, delamination, corrosion, plasticity, etc. The majority of our group’s work has been on advanced alloys and composites. Both material systems have direct applications in Aerospace Engineering, as we work closely with these industries. We are looking for a motivated, hard-working student interested in research within the field of experimental mechanics of materials. The in situ experiments include advanced materials testing, using state-of-the-art 3d strain mapping. We deposit self-assembled sub-micron particles on the material’s surface and track their displacement as we deform the specimen. Coupled with characterization of the materials microstructure, we can obtain strain localization as a precursor to failure. Specific projects look at increasing the structural integrity of additive manufactured materials and increasing fidelity of lifing analysis to introduce new light weight materials into applications.


Data Science for Soccer Training

Research categories:  Computational/Mathematical, Computer Engineering and Computer Science
School/Dept.: ECE
Professor: Aly El Gamal
Preferred major(s): ECE, CS
Desired experience:   Probability, Statistics, Machine Learning

We are working on analyzing the data collected from the Women's soccer team's training sessions. The goal is to understand what factors are correlated with the stress level of the players, so that we can provide recommendations for a customized design of the training drills for each player or group of players.


Development of a machine learning tool to optimize thermal transport

Research categories:  Computational/Mathematical, Mechanical Systems, Nanotechnology
School/Dept.: Mechanical Engineering
Professor: Xiulin Ruan
Preferred major(s): Mechanical Engineering, Physics, Materials Sciences
Desired experience:   Knowledge of heat transfer and nanotechnology is a plus but not required.

Many heat transfer applications, such as thermoelectric energy conversion, thermal barrier coatings, and thermal management of electronics, require the optimization of thermal conductivity of the material to reach minimum or maximum. Conventionally, such optimization was done by exhausting different structures and compositions of the materials, hence it is a time consuming and even impractical task. Here, we aim to develop a machine-learning based optimization tool to minimize the thermal conductivity of a nanostructure called superlattice. By modeling a limited number of material structures and learn from the results, machine-learning will guide the design to new structures with likely better properties. The goal is to reach the same optimum design by searching only a fraction of the entire design space. We will convert a in-house code to a nanoHUB simulation tool.


Hololens Augmented Reality based Ultrasound Imaging

Research categories:  Bioscience/Biomedical, Computational/Mathematical, Computer Engineering and Computer Science, Industrial Engineering
School/Dept.: Industrial Engineering
Professor: Juan Wachs
Preferred major(s): CS, ECE, ME, IE
Desired experience:   Very good programming skills. Experience in computer graphics and vision is an advantage.

The project consists of using an ultrasound on a patient simulator and observe the medical imaging on an augmented reality headset (Hololens). This information will be used for teleconsultation.


Machine Learning for Wireless Communications

Research categories:  Computational/Mathematical, Computer Engineering and Computer Science
School/Dept.: ECE
Professor: Aly El Gamal
Preferred major(s): ECE, CS
Desired experience:   Probability, Signals and Systems, Digital Communications, Machine Learning

The goal of the project is to explore deep neural network architectures that are suitable for various wireless communication tasks. We currently are working on the problem of classifying the modulation type of wireless signals.

The project will also involve designing experiments for obtaining real data sets, as we are currently using simulated data sets.


Multiphase Fluid Flows in Tight Spaces

Research categories:  Bioscience/Biomedical, Chemical, Computational/Mathematical, Physical Science
School/Dept.: Mechanical Engineering
Professor: Ivan Christov
Preferred major(s): Mechanical Engineering, Chemical Engineering, Applied Mathematics, Computational Science
Desired experience:   1. Thorough understanding of undergraduate fluid mechanics. 2. Programming experience with high-level language such as Python or MATLAB. 3. Experience with shell/command-line environments in Linux/Unix; specifically, remote login, file transfers, etc. 4. Experience researching difficult questions whose answers are not found in a textbook. 5. Desire to learn about new fluid mechanics phenomena and expand computational skillset.

Multiphase flows are fluid flows involving multiple fluids, multiple phases of the same fluid, and any situation in which the dynamics of an interface between dissimilar fluids must be understood. Examples include water displacing hydrocarbons in secondary oil recovery, a mixtures of particle-laden fluids being injected into a hydraulically fractured reservoirs ("fracking"), introduction of air into the lungs of pre-maturely born infants to re-open their liquid-filled lungs and airways, and a whole host of other physico-chemical processes in biological and industrial applications.

The goal of this SURF project will be to study, using computational tools such as ANSYS Workbench and/or the OpenFOAM platform, how multiphase flows behave in tight spaces. To accomplish this goal, the SURF student will work with a PhD student. Specifically the dynamics of interfaces between different phases and/or fluids will be studied through numerical simulation, and the effect of the flow passage geometry will be addressed. Some questions that we seek to address are whether/how geometric variations can stabilize or destabilize an interface and whether/how geometry affects the final distribution of particles in particle-laden multiphase flow passing through a constriction/expansion. Applications of these effects to biological and industrial flows will be explored quantitatively and qualitatively.

More information:


Network for Computational Nanotechnology (NCN) / nanoHUB

Research categories:  Chemical, Computational/Mathematical, Computer Engineering and Computer Science, Electronics, Material Science and Engineering, Mechanical Systems, Nanotechnology, Other
Professor: NCN Faculty
Preferred major(s): Electrical, Computer, Materials, Chemical or Mechanical Engineering; Chemistry; Physics; Computer Science; Math
Desired experience:   Serious interest in and enjoyment of programming; programming skills in any language. Physics coursework.

NCN is looking for a diverse group of enthusiastic and qualified students with a strong background in engineering, chemistry or physics who can also code in at least one language (such as Python, C or MATLAB) to work on research projects that involve computational simulations. Selected students will typically work with a graduate student mentor and faculty advisor to create or improve a simulation tool that will be deployed on nanoHUB. Faculty advisors come from a wide range of departments: ECE, ME, Civil E, ChemE, MSE, Nuclear E, Chemistry and Math, and projects may be multidisciplinary. To learn about this year’s research projects along with their preferred majors and requirements, please go to the website noted below.

If you are interested in working on a nanoHUB project in SURF, you will need to follow the instructions below. Be sure you talk about specific NCN projects directly on your SURF application, using the text box for projects that most interest you.

1) Carefully read the NCN project descriptions (website available below) and select which project(s) you are most interested in and qualified for. It pays to do a little homework to prepare your application.

2) Select the Network for Computational Nanotechnology (NCN) / nanoHUB as one of your top choices.

3) In the text box for Essay #2, where you describe your specific research interests, qualifications, and relevant experience, you may discuss up to three NCN projects that most interest you. Please rank your NCN project choices in order of interest. For each project, specify the last name of the faculty advisor, the project, why you are interested in the project, and how you meet the required skill and coursework requirements.

For more information and examples of previous research projects and student work, click on the link below.


Role of Microbial Motility in Degradation of Dispersed Oil

Research categories:  Bioscience/Biomedical, Chemical, Computational/Mathematical, Life Science, Mechanical Systems, Physical Science
School/Dept.: Mechanical Engineering
Professor: Arezoo Ardekani
Preferred major(s): Biomedical engineering, chemical engineering, biology, environmental engineering
Desired experience:   bacteria/cell culture laboratory and/or transport phenomena and/or microfluidic experiments

Microbial biodegradation processes play an important role in reducing the harmful
effects of a marine oil spill. The fate and transport of spilled hydrocarbons in the ocean depends on a combination of nonlinear effects such as environmental factors, ocean flows, chemical and physical properties of the crude oil, and the distribution of the oil-degrading microbial community. The over-arching goal of this research project is to quantify the role of motility of marine bacteria in the initial stage in biodegradation of oil through experiments and/or computational modeling.


Seismic Design of Aboveground Storage Tanks

Research categories:  Aerospace Engineering, Civil and Construction, Computational/Mathematical, Mechanical Systems
School/Dept.: Lyles School of Civil Engineering
Professor: Sukru Guzey
Preferred major(s): Civil Engineering, Mechanical Engineering, Aerospace Engineering
Desired experience:   Statics (CE 297 or similar), Dynamics (CE 298 or similar), Mechanics of Materials (Strength of materials) (CE 270 or similar)

Cylindrical steel storage tanks are essential parts of infrastructure and industrial facilities used to store liquids. There are millions of welded steel tanks in the world storing flammable and or hazardous liquids in the petroleum, petrochemical, chemical and food industries across the world. Mechanical integrity and safe operation of these tanks very important because failure or loss of containment of such tanks may have catastrophic consequences to the human life and the environment. There are many procedures given in design standards to withstand the possible load effects, such as the hydrostatic pressure of the stored liquid, the external wind pressure, internal and external pressures due to process, and seismic events.

Investigators have a relatively well understanding on the load effects due to the hydrostatic, wind, and external/internal pressures due to process during normal operating levels. However, behavior of large, aboveground, steel, welded, liquid storage tanks under the presence of seismic loads introduce several critical failure criteria to the structure not exhibited during normal operating levels. Although many researchers investigated the liquid containers under dynamic excitations, the research on this subject still active. The bottleneck of this research topic is the intricate interplay between the flexible thin-walled tank wall and bottom, liquid inside the container, and the reinforced concrete or soil foundation supporting the container. Although, are many relatively recent research efforts, there is still a gap to find a viable solution to this problem.

To address this gap, the aim of this work is to perform a study on seismic design of aboveground storage tanks. Dr. Guzey with a team of one doctoral student and one undergraduate SURF student, shall perform analytical and numerical studies to study the behavior of liquid containers under dynamics excitations. We shall conduct numerical experiments using different levels of complexity and fidelity of multi-physics of these containers and compare the results to available analytical solutions, physical tests and current design standards. The undergraduate SURF student will work under the mentorship of Dr. Guzey and a graduate student. The SURF student compile a literature review, perform numerical simulations using FEA computer program ABAQUS, and write scientific research papers and conference presentations.


Surface Enhancement using Severe Plastic Deformation

Research categories:  Aerospace Engineering, Computational/Mathematical, Innovative Technology/Design, Material Science and Engineering, Mechanical Systems, Nanotechnology
School/Dept.: Materials Engineering
Professor: David Bahr
Preferred major(s): MSE, ME, or AAE
Desired experience:   Mechanical behavior courses, mechanical testing laboratory experience.

Modifying the surface of metals using shot peening, burnishing, and other plastic deformation processing is common in industry. However, we have limited ability to predict performance of how shot peened materials change properties due to complex interactions between residual stresses and microstructural changes. This project, tied to an industrial consortium, will focus on developing a combined model that predicts both recrystallization and residual stresses using a combination of experimental measurements and predictive computational models in common engineering alloys. The student will gain experience in preparing samples for metallographic inspection, performing hardness testing and optical microscopy, and using basic finite element simulations.


Virtual Reality Robotic Model using Gaming Technologies

Research categories:  Bioscience/Biomedical, Computational/Mathematical, Computer Engineering and Computer Science, Industrial Engineering
School/Dept.: Industrial Engineering
Professor: Juan Wachs
Preferred major(s): ECE, CS
Desired experience:   Very good programming skills

The student will have to develop an environment that can be visualized with the VIBE wearable headset and in which he can control a virtual and real robot to grasp objects and move around the environment.


When someone is skipping their medication, we know first!

Research categories:  Bioscience/Biomedical, Computational/Mathematical, Computer Engineering and Computer Science, Industrial Engineering
School/Dept.: Biomedical Engineering
Professor: Nan Kong
Preferred major(s): BME, IE, ECE, CS, Math
Desired experience:   Pattern Recognition, Data Mining, Systems and Signals, Signal Processing, Experimental Statistics, Stochastic Processes, Stochastic Operations Research, or equivalent.

Adherence to preventive medications prescribed after vascular or cardiac events such as acute myocardial infarction (AMI), transient ischemic attack (TIA) or acute ischemic stroke is low and non-adherence has been associated with poor outcomes. Wireless technology and behavioral approaches have shown promise in improving health behaviors. Understanding how best to deploy these interventions for maximum impact is lacking, however. In this project, we will learn how data mining techniques can help characterize the behavior of medication adherence for a diverse group of people based on emerging data collected from smart pill bottles.

Visit the website noted below and this one to learn more about the work: