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 2018 Research Symposium Abstracts.

2019 projects will continue to be posted through January!

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:



Computational Modeling of Photon Transport in Nanocomposites

Research categories:  Computational/Mathematical, Material Science and Engineering, Mechanical Engineering, Nanotechnology
School/Dept.: Mechanical Engineering
Professor: Xiulin Ruan
Preferred major(s): Mechanical Engineering, Materials Sciences, Physics, Electrical Engineering, Computational Engineering
Desired experience:   The student should have an intermediate level of scientific computing experience (i.e. MATLAB or Python knowledge), strong analytical and numerical skills, and an interest in parallel computing. Completed coursework in Physics (Electricity & Magnetism) and Heat Transfer will be helpful, but not required.

This project will aid in an ongoing effort to achieve ultra-efficient nanocomposites for radiative cooling applications. Achieving radiative cooling requires engineering optical properties of nanocomposites to reflect and emit in certain regions. This work will focus on how to optimize the nanocomposites through computational modeling to achieve the optimal optical properties.


Computational modeling of mechanosensitive behaviors of cells

Research categories:  Bioscience/Biomedical, Computational/Mathematical, Life Science
School/Dept.: Weldon School of Biomedical Engineering
Professor: Taeyoon Kim
Preferred major(s): Mechanical Engineering
Desired experience:   C language, MATLAB, and other coding skills

Cells are able to sense surrounding mechanical environments. For example, a number of experiments have demonstrated that nano- and micro-patterns can guide migration of cells. This cell behavior is called the contact guidance and plays an important role in various physiological processes. In this research project, we aim to develop a rigorous computational model to study mechanisms of the contact guidance.


Design and Analysis of Novel Approaches for Packaging of Li-Ion Batteries for Automotive Applications

Research categories:  Computational/Mathematical, Mechanical Engineering, Mechanical Systems, Other
School/Dept.: School of Mechanical Engineeing
Professor: Thomas Siegmund
Preferred major(s): Mechanical Engineering

E-mobility is a key driver of future transportation systems. E-vehicles rely on energy storage in batteries, and such batteries packages need to be integrated into the overall vehicle structure under consideration of structural and thermal design considerations. This research project will advance novel solutions to do so. The SURF student will work on CAD model design, simulations and experiments on simulated Li-ion battery packages for mechanical and thermal safety.


Geodesic convolution with various applications in 3D data analysis

Research categories:  Computational/Mathematical, Computer Engineering and Computer Science, Mechanical Engineering
School/Dept.: Mechanical Engineering
Professor: Min Liu
Preferred major(s): ME, ECE, CS
Desired experience:   python, c++ code, experience with convolutional neural networks

The scope this project is to explore the mechanics of geodesic convolution (in contrast to the standard Euclidean space convolution) for deep neural networks. The objective is to research for a more efficient, robust and shape-aware filter to support various applications for 3D vision data analysis, E.g. Autonomous CAR, robot navigation, and Augmented realities.


Lake Michigan Ecosystem Modeling

Research categories:  Civil and Construction, Computational/Mathematical, Environmental Science, Mechanical Engineering, Physical Science
School/Dept.: Civil Engineering
Professor: Cary Troy
Preferred major(s): Civil, Environmental, or Mechanical Engineering
Desired experience:   Proficiency in Matlab; Good communication skills, written and oral; Exposure to differential equations

This is an NSF-funded project examining the role of turbulence in the Lake Michigan ecosystem. Particularly, the project is quantifying the interactions between water column turbulence and the ability of invasive quagga mussels to filter nutrients and plankton out of the water column. The SURF research will involve the development of a 1-D biogeochemical model that models the temporal and vertical distribution of nutrients (e.g. phosphorus), phytoplankton, and zooplankton in Lake Michigan. The successful SURF applicant will be responsible for the coding and development of the model in Matlab, as well as potentially participating in data collection on Lake Michigan and the analysis of this data.


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:


SMART (Social Media Analytics Response Toolkit)

Research categories:  Computational/Mathematical, Computer Engineering and Computer Science, Innovative Technology/Design
School/Dept.: Electrical and Computer Engineering
Professor: David Ebert
Preferred major(s): Computer Science, Electrical and Computer Engineering
Desired experience:   For this project, the ideal candidate will have good working knowledge of some of the modern web development technologies, including client-side technologies such as HTML5, SVG, JavaScript, AJAX, and DOM, and D3 as well as server-side components such as PHP, Tomcat, MySQL, etc. Experience in web services development and web based visualization APIs is a plus. Students should have a GPA of 3 or higher.

This visual analytics application provides interactive (Twitter) social media analysis and visualization capabilities through topic extraction, combination of filters, cluster analysis and stream categorization. Analysts can also create custom classifiers to extract social media messages relevant to specific events or topics. Many first responder groups in the U.S. use this platform.


The Arequipa Nexus Sustainable Viticulture

Research categories:  Agricultural, Computational/Mathematical, Computer Engineering and Computer Science, Environmental Science, Innovative Technology/Design
School/Dept.: Electrical and Computer Engineering
Professor: David Ebert
Preferred major(s): Flexible: Computer Science, Food Science, Agronomy, Environmental Science, GIS, Electrical and Computer Engineering
Desired experience:   We are looking for applicants with a strong background in either of the following: GIS (Geographic Information Systems), food sciences, agronomy (soil oriented), web development or python programming (e.g. HTML/JavaScript, Leaflet, D3). Students should have a GPA of 3 or higher. Applicants with Spanish fluency are encouraged to apply.

The Universidad Nacional de San Agustín (UNSA) in Arequipa, Peru and Purdue through Discovery Park’s Center for the Environment (C4E) have partnered to create a new research, education and innovation institute to work together on key challenges for a sustainable future for the citizens of Arequipa. The Nexus Institute applies collaborative, data-driven, interdisciplinary science, technology and innovation to help chart a new course toward a sustainable future. Our lab works with key stakeholder groups to develop data, provide (winery and vineyard farm) guidelines, simulation models, and decision support tools for vineyard management through state-of-the-art data sets, GIS and remote sensing, and environmental decision tools. We are also developing a system to provide farmers with more accurate information than previously possible, helping growers to optimize crop yields and minimize use of water and other resources. The system will be first tested in Peru to create precision agriculture-based viticulture test-beds.


Using Unmanned Aircraft Systems (UAS) to Monitor Crop Development

Research categories:  Agricultural, Computational/Mathematical, Environmental Science
School/Dept.: Agricultural and Biological Engineering
Professor: Keith Cherkauer
Preferred major(s): Agricultural Engineering, Environmental Engineering, Civil Engineering
Desired experience:   Knowledge of programming (e.g., MatLab or Python), electrical circuits, and digital imagery is desired but not required.

Global food production must continue to increase in order to support a growing world population. The integration of data science, sensors and automated sensing platforms into breeding programs allows science and engineering to work together to increase the speed and accuracy of seed selection for future development into commercial products. Unmanned Aircraft Systems (UAS) provide a platform to collect very-high resolution remote sensing image data from fields frequently during the growing season. The student selected for this project will work with an experienced team of graduate students and faculty to collect imagery and supporting ground reference data from multiple crop fields. They will learn how to setup ground targets, collect additional ground reference data (including soil moisture and leaf porosity measurements), manage large datasets, and process imagery to extract metrics per plot, which can be correlated to the specific seed variety in each plot within the field containing each experiment. As part of this project, the student will be responsible for collecting ground reference data and processing UAS imagery. They will use their data to assess the usefulness of one metric used for monitoring crop development that will be selected at the start of the summer.