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:

Innovative Technology/Design


Development of New Approaches for Biological Imaging and Materials Design using Mass Spectrometry

Research categories:  Chemical, Innovative Technology/Design, Material Science and Engineering
School/Dept.: Chemistry
Professor: Julia Laskin
Preferred major(s): Chemistry, biochemistry, chemical engineering, computer science, electrical engineering, materials engineering
Desired experience:   We are looking a different skill set for different aspects of the project. If you are excited about science and dedicated to research, you will find an excellent environment in our lab.

We have two projects in the lab. In one project, we develop new analytical approaches for imaging of numerous biomolecules in biological systems. We need help in running experiments, analyzing data, and development of new computational approaches, which will streamline data analysis and facilitate biological discoveries. In another project, we develop unique instruments for designing layered coatings using beams of complex ions. In this project, we need help with the synthesis of relevant precursor molecules, their characterization using mass spectrometry and other analytical techniques, ion deposition on surfaces, and surface characterization.


Human Factors Considerations: Older Adults and Autonomous Vehicle Systems

Research categories:  Computer Engineering and Computer Science, Industrial Engineering, Innovative Technology/Design
School/Dept.: Industrial Engineering
Professor: Brandon Pitts
Preferred major(s): Industrial Engineering
Desired experience:   Human Factors, Matlab, Transportation, some experience in statistics, some computer programming experience (in any language)

Automobiles are becoming increasingly autonomous. At the same time, the demographics of drivers using these advanced vehicles is changing. In particular, adults aged 65 years and older are the fastest growing age group worldwide and are expected to benefit from vehicle automation. However, age-related perceptual and cognitive difficulties may limit the extent to which these systems are useful for individuals in this age category. The goal of this project is, therefore, to quantify interactions between (older adult) drivers and autonomous driving systems in order to develop approaches that enhance roadway safety for various aging populations.

The SURF student will assist with collecting and analyzing data from human-subject experiments (using a laboratory driving simulator) and with writing any project publication. In addition, the student will meet regularly with faculty and graduate mentors to communicate his/her progress.


Low-cost user-friendly biosensors for animal health

Research categories:  Agricultural, Bioscience/Biomedical, Electronics, Innovative Technology/Design, Life Science, Material Science and Engineering, Mechanical Systems
School/Dept.: Agricultural and Biological Engineering
Professor: Mohit Verma
Preferred major(s): Biomedical engineering, biological engineering, electrical engineering, mechanical engineering, or other relevant fields
Desired experience:   To be successful at this position, you should have a GPA>3.5, prior experience working in a wet lab (ideally experience with bacterial culture and DNA amplification), experience building electromechanical devices, and the ability to work in a team.

Infectious diseases are a leading cause of economic burden on food production from animals. For example, bovine respiratory diseases lead to a loss of ~$480/animal. Current methods for tackling these diseases includes the administration of antibiotics by trial-and-error. This approach leads to failure of treatment in up to one-third of the cases. In addition, it also leads to a proliferation of antibiotic resistance in pathogens.

Our research project focuses on developing a low-cost user-friendly biosensor based on paper that can detect which pathogen is causing the disease and whether it exhibits antibiotic resistance. Such a biosensor would provide a readout to the farmer or the veterinary physician and suggest which antibiotics are likely to be successful.

The SURF student will have three objectives: i) design primers for detecting pathogens associated with bovine respiratory diseases, ii) build a device for processing the sample and extracting DNA that can be amplified by the biosensor, and iii) build a device for detecting colorimetric/fluorometric output from the biosensor.

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.


Smart Manufacturing using IoT and Machine Learning

Research categories:  Computer Engineering and Computer Science, Innovative Technology/Design, Mechanical Engineering
School/Dept.: Mechanical Engineering
Professor: Martin Jun
Preferred major(s): Mechanical Engineering, Computer Engineering, or Computer Science
Desired experience:   Virtual reality programming, mechatronics, CAD design and programming for graphics, signal processing and data analysis, machining, etc.

Autonomous operation and decision making during manufacturing processes and production are important. Using IoT technologies, machine-to-machine, machine-to-human communication and data generation are achieved and machine learning algorithms are used for data analysis and decision making. The student will work on virtual reality (VR) based visualization of data achieved from IoT devices connected to CNC machine and robots and analyze data using machine learning.


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.