2023 Research Projects
Projects are posted below; new projects will continue to be posted. To learn more about the type of research conducted by undergraduates, view the archived symposium booklets and search the past SURF projects.
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:
Other (48)
360 degree video streaming research testbed
Description:
360 degree video streaming is a new form of video streaming where video is captured using a 360 degree video camera, and users may select which perspectives are of interest to them. Using traditional approaches to video streaming can result in 5X-6X bandwidth overhead. It is desirable to only show a user the portion of the video relevant to her, but user motion can lead to stalls, or degraded experience. We are developing new algorithms and solutions for 360 degree streaming with smooth user experience while achieving significant bandwidth savings.
In the summer project, we are looking to build a complete end to end prototype, where users can engage in 360 streaming from mobile devices and Oculus headsets. We would like to work with real content producers (e.g., Purdue commencement) to perform field trials of our 360 video streaming system. Doing so can also allow for A/B testing of different algorithms and provide data on how users engage with such content.
In the summer project, we are looking to build a complete end to end prototype, where users can engage in 360 streaming from mobile devices and Oculus headsets. We would like to work with real content producers (e.g., Purdue commencement) to perform field trials of our 360 video streaming system. Doing so can also allow for A/B testing of different algorithms and provide data on how users engage with such content.
Research categories:
Human Factors, Mobile Computing, Other
Preferred major(s):
- Computer Engineering
Desired experience:
The main skillsets are: (i) strong Computer Engineering skills, especially in systems and software building; and (ii) an interest and passion in building working real-world research prototypes and evaluations among real users. Strong background in C++ is preferred, and an ability to develop code for mobile devices, and devices such as Oculus headsets will be required.
Desired course work include: Operating Systems, and Computer Networking.
Other requirements include C++/Java (ECE 30862/39595) and Data Structures (ECE 368).
School/Dept.:
Electrical and Computer Engineering
Professor:
Sanjay
Rao
More information: https://engineering.purdue.edu/~isl/
AAMP-UP Project 10: Detonation Wave Shaping
Description:
This research topic seeks to explore the interaction with detonation waves with inclusions (voids, inerts, other explosives). It will involve advanced sample preparation, including microscale machining of energetic materials, as well as high rate experiments including high-speed imaging including streak imaging. The REU student would work closely with Research Scientists and graduate students to design experiments, perform experiments, analyze data, and report/share these results.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 11: Post Detonation Fireballs and Explosive Driven Shock Waves
Description:
This research topic seeks to explore the reactions and induced gas shocks occurring after a detonation. This includes It will involve advanced sample preparation of the explosives and added metal fuels or other additibes, and dynamic experiments. This project will focus on applying advanced laser diagnostics to both the induced shock and post-detonation reactions. The REU student would work closely with Research Scientists and graduate students to design experiments, perform experiments, analyze data, and report/share these results.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 12: Computational study of energetic materials
Description:
Overarching Goal: Enable discovery of the physical mechanisms driving impact-induced reactions in explosives (such as interparticle relative velocities and contact pressures) and their correlation with material properties, formulation, and processing.
Project Description: Energetic materials used in the propulsion industry, and particle-binder composites in general, consist of (explosive) crystals in a binder matrix. The mechanical properties and performance of these materials are strongly correlated to their microstructure. Specifically, the mechanical response under weak impact loads is characterized by long-range microstructural correlations (typical of granular materials) that need to be resolved with high statistical significance in order to understand how complex phenomena (such as detonation) emerges from local simpler interactions. The interplay between these long-range interactions and local mechanisms (such as deformation, failure and, ultimately, hot spot formation) is responsible for the sensitivity of the material.
A mesoscale modeling methodology, capable of modeling the dynamic response of large energetic composites (>50,000 crystals) by analytically upscaling complex crystal-binder deformation and failure mechanics into closed-form contact laws, will be used to build time-dependent multivariate probability distribution functions of microstructural features.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Project Description: Energetic materials used in the propulsion industry, and particle-binder composites in general, consist of (explosive) crystals in a binder matrix. The mechanical properties and performance of these materials are strongly correlated to their microstructure. Specifically, the mechanical response under weak impact loads is characterized by long-range microstructural correlations (typical of granular materials) that need to be resolved with high statistical significance in order to understand how complex phenomena (such as detonation) emerges from local simpler interactions. The interplay between these long-range interactions and local mechanisms (such as deformation, failure and, ultimately, hot spot formation) is responsible for the sensitivity of the material.
A mesoscale modeling methodology, capable of modeling the dynamic response of large energetic composites (>50,000 crystals) by analytically upscaling complex crystal-binder deformation and failure mechanics into closed-form contact laws, will be used to build time-dependent multivariate probability distribution functions of microstructural features.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Marcial
Gonzalez
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 13: Conducting Polymer Energetic Binders
Description:
The overarching objective of this project is to create polymeric binders that have robust electrical and mechanical properties. This will be achieved by modifying commercially-available materials as well as synthesizing next-generation conducting polymers. By developing the appropriate structure-property-processing relationships, we will develop, and eventually deploy, binders with electronically-triggerable properties. Specifically, the student associated with this project will focus on the design and mechanical testing of polymers and polymer-based binders for energetic materials applications.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Chemical Engineering
Professor:
Bryan
Boudouris
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 14: Direct Visualization of Stress Fields in Model Composite Systems
Description:
When a polymer matrix composite is deformed, the stresses in the matrix near the reinforcing phase can vary significantly from those in the bulk. Utilizing molecular force sensors known as mechanophores, we have developed a method to measure the local stress field in a deformed composite comprised of a rigid spherical particle in a silicone matrix. This REU project will continue this research by investigating the local stress field that develops around two particles in close proximity to one another. Understanding the changes in the stress field between two particles will allow us to develop more comprehensive models of composite deformation modes. The student will be responsible for fabricating samples and performing micromechanical samples over a fluorescent microscope. The student will learn mechanical testing methods and analysis, laser scanning confocal microscopy, and image analysis techniques.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Materials Engineering
Professor:
Chelsea
Davis
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 15: In-situ Diagnosis of Additive Manufacturing with 3D Vision Sensor
Description:
This project aims at designing a 3D printer that can incorporate a high-end customized 3D vision sensor for close-loop controls. Undergrads will closely work with graduate students on both software and/or hardware development depending upon interest. Hardware work involves component identification, system design, fabrication, and integration. Software work includes algorithms for fault diagnosis and closed-loop control strategies.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Song
Zhang
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 16: Additive Manufacturing
Description:
This research project seeks to additively manufacture (3D print) highly viscous materials using a novel 3D-printing method: Vibration Assisted Printing (VAP). This technique uses high frequency vibrations concentrated at the tip of the printing nozzle to enable flow of viscous materials at low pressures and temperatures. VAP has the potential to create next-generation munitions with more precision, customizability, and safety than traditional additive manufacturing methods. The objective of this project is to design formulations which are capable of being vibration-assisted printed, maintain energetic performance, and retain desirable mechanical properties after printing. The REU student would be mentored by graduate students and work within a team to design experiments, perform experiments, analyze data, and disseminate the results. The REU student will have the opportunity to present the findings in regular meetings, poster sessions, formal presentations, and papers.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Jeff
Rhoads
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 17: Computational Studies of Polymer Stability
Description:
The students working on this project will learn how to use state-of-the-art computational tools for characterizing the degradation mechanisms of polymers. Students will use these tools to understand structure-stability relationships of new polymers. Depending on progress, the data generated from these studies will be used to train machine learning models to accelerate predictions on new systems.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Chemical Engineering
Professor:
Brett
Savoie
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 18: Polymer Derived Ceramics Additive Material Systems for SHM
Description:
Additive manufacturing and real-world applications have been seen in the past as two
separate entities that are increasing coalescing over the years. With more recent advancements in 3D-printing technology, the two paths have now come to an intersection. Specifically, in the case of resin 3D-printing, the amount of detail possible allows for practical components to
be manufactured from advanced engineering materials for a wide variety of applications. In
this particular work, the focus has been is to define manufacturing methods that allow for the
embedding of sensors into ceramic media as well as show the feasibility of doing so.
The ADAMs lab is currently exploring techniques to create multi-functional material systems utilizing SLA. Candidate projects include embedded piezoelectric actuator for sensing applications and shape memory alloy sheets to create localized structural changes in a ceramic structure. The created systems will be tested to see if they can detect real time ballistic events.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
separate entities that are increasing coalescing over the years. With more recent advancements in 3D-printing technology, the two paths have now come to an intersection. Specifically, in the case of resin 3D-printing, the amount of detail possible allows for practical components to
be manufactured from advanced engineering materials for a wide variety of applications. In
this particular work, the focus has been is to define manufacturing methods that allow for the
embedding of sensors into ceramic media as well as show the feasibility of doing so.
The ADAMs lab is currently exploring techniques to create multi-functional material systems utilizing SLA. Candidate projects include embedded piezoelectric actuator for sensing applications and shape memory alloy sheets to create localized structural changes in a ceramic structure. The created systems will be tested to see if they can detect real time ballistic events.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
James
Gibert
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 19: A Design of Experiments (DOE) Approach to Obtain Repeatedly Homogeneous Propellant Formulations
Description:
The United States mixes propellants the same way they did in WWII, i.e., with bladed batch mixers. This project optimizes the mixing settings for a safer, bladeless, Dual Asymmetric Centrifuge (DAC) mixer with remote operation capabilities. Specifically, a Design of Experiments (DOE) approach is applied to identify process settings to uniformly mix a mock propellant formulation. Response variables measured include temperature, viscosity, concentration, and mixer motor torque. This study establishes an efficient FlackTek Speedmixer (DAC mixer) procedure for mixing modified double-base propellants.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Chemical Unit Operations, Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Chemical Engineering
Professor:
Stephen
Beaudoin
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 1: Dynamic mechanical properties of mock polymer bonded explosives systems
Description:
Polymer bonded explosives contain a high percentage of explosive particulates bound in a polymer binder, which allows for increased formability and machinability. Understanding how these systems fail during mechanical shock is paramount for continued safe use. This research area explores the behavior of cast and additively manufactured polymer bonded explosives systems through the use of 3 point bend testing. During this project, the student will complete a literature review researching particle based composites, 3D printing of them, and three-point bending tests. The student will work with graduate student advisors to design samples and the testing series, with potential augmentation including preliminary micro X-ray computed tomography for 3-D sample internal visualization, in situ high speed imaging of fracture, and post experimentation failure analysis.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Material Processing and Characterization, Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Materials Engineering
Professor:
Weinong
Chen
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 20: Understanding Adhesion of Energetic Particles
Description:
This project is focused on quantifying the van der Waals adhesion of energetic particles to surfaces of interest. Better understanding how energetic particles adhere to surfaces can improve explosive detection systems and help enhance the performance of polymer-bonded explosives. Atomic force microscopy is used to directly measure the adhesion between energetic particles and binders.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Chemical Unit Operations, Chemical Catalysis and Synthesis, Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Chemical Engineering
Professor:
Stephen
Beaudoin
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 21: Energetic Particle Adhesion via Enhanced Centrifuge Method
Description:
Composite solid propellants, consisting of energetic particles embedded in a polymeric binder, are utilized extensively in projectile devices. Additive manufacturing of these propellants is a promising method to enhance their reliability and effectiveness; however, such materials often fail during launch due to insufficient adhesion between components. Hence, it is of utmost importance to maintain a high adhesive force between the particles and the surrounding binder, which would ensure that the required combustion reactions take place even as the projectile moves at high speeds. Thus, we seek to quantify how the adhesive behavior of the particles changes using the enhanced centrifuge method, which implements experimental and computational techniques in order to map apparent centrifugal forces to intermolecular van der Waals forces.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Chemical Unit Operations, Chemical Catalysis and Synthesis, Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Chemical Engineering
Professor:
Stephen
Beaudoin
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 2: In-situ nanoindentation of 3D printed vs cast particulate composites
Description:
Polymer bonded explosives contain a high percentage of explosive particulates bound in a polymer binder, which allows for increased formability and machinability. Understanding how these systems fail during mechanical shock is paramount for continued safe use. This research area explores the behavior of cast and additively manufactured polymer bonded explosives systems through the use of nanoindentation and bulk hardness. During this project, the student will complete a literature review researching particle based composites, 3D printing of them, and hardness testing. The student will work with graduate student advisors to design samples and the testing series, with potential augmentation including pre and post experiment micro X-ray computed tomography for 3-D sample internal visualization, Characterization of surface quality of samples, and post experimentation failure analysis.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Material Processing and Characterization, Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Materials Engineering
Professor:
Weinong
Chen
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 3: Machine Learning and Data Collection
Description:
Machine learning (ML) tools are playing an increasingly important role in science and engineering, revealing patterns and providing predictive capabilities not achievable otherwise. This research area explores the utility of machine learning algorithms in the design, development, and characterization of various energetic material systems. Particular emphasis is placed on bringing a data science formalism to the field, with an eye toward both future capability development and more intelligent (and appreciably faster) material formulation and system design. The REU student would work closely with a Research Scientist and graduate student to gather data, analyze it using ML tools, and share these results.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Big Data/Machine Learning, Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 4: Advanced High-Density Fuels in Energetic Materials
Description:
High density fuels, typically metals, are commonly added to propellants and explosives to improve their performance, as well as other factors such as sensitivity and toxicity. This research topic explores the development, small-scale manufacturing, and characterization of high-density fuels in energetic materials. Particular emphasis is placed on emergent material systems, such as aluminum-lithium alloys, oxide-free coated nano-aluminum, and mechanically activated (MA) fuels. The REU student would work closely with Research Scientists and graduate students to design experiments, perform experiments, analyze data, and report/share these results.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 5: Detonation Dynamics
Description:
This research topic seeks to explore the high-rate mechanics of detonating energetic materials, or under impact or shock. It will involve advanced sample preparation, including microscale machining of energetic materials, as well as high rate experiments. The REU student would work closely with Research Scientists and graduate students to design experiments, perform experiments, analyze data, and report/share these results.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 6: Reactive Wires to Tailor Propellant Burning Rate
Description:
Of the many techniques that have been employed to increase burning rates, embedding thermally-conductive and/or reactive wires appears to be the approach to do so without increasing sensitivity. We are utilizing our additive manufacturing capabilities, including vibration assisted printing (VAP), to produce both the wires and the propellant. These “wires” may not actually be metals, but include thermally conductive materials such as graphene. The objective of this project is to use both fused deposition modeling (FDM) and direct writing 3D printing techniques to tailor the surface area of propellants dynamically using conductive and reactive wire deposition. The REU student would work closely with Research Scientists and graduate students to design experiments, perform experiments, analyze data, and report/share these results.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 7: Piezoelectric Energetic Materials
Description:
Piezoelectric energetic materials (piezoenergetics or PEMs) offer the potential for a new generation of smart propellants and pyrotechnics with multifunctional capabilities that can be actively controlled via external stimuli. However, the fundamental physics and chemistry governing energy transfer, energy repartitioning, and chemical reactions/kinetics resulting from external stimulation of PEMs are not well understood. It is envisioned that, by coupling piezoelectric behavior and nanoenergetics, truly smart and switchable materials can result. Specifically, we envision reactive piezoelectric materials with multifunctional properties with reactivity and microstructure that can be controlled and altered by external stimuli including stress, temperature, or electromagnetic fields; while enabling integrated in situ sensing. The REU student would be mentored by two graduate students and would design experiments, perform those experiments, collect data and present/share those results.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 8: Characterization of Material for 3D Printing
Description:
The objective of this project would be to determine the similarity of mass flow rate for a variety of inert and reactive materials, including Ammonium Perchlorate (AP) based propellants. The undergraduate would help 3D print and test these inert mixtures. The undergraduate student would gain experience researching relevant literature, mixing samples, designing experiments, and analyzing the data for the mock materials as well as assisting with the same tests using energetic materials.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Material Processing and Characterization, Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
AAMP-UP Project 9: Advanced Solid Fuels for Hypersonic or RDE Propulsion
Description:
Solid fuels have some potential applications in both hypersonic and rotating detonation engine (RDE) application. Material fabrication, as well as some small-scale testing will be performed. Particular emphasis is placed on emergent material systems, such as materials that can produce the desired gaseous fuels. The REU student would work closely with Research Scientists and graduate students to design experiments, perform experiments, analyze data, and report/share them.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
This project is from the AAMP-UP summer program, which is a different program than SURF. AAMP-UP is a 10-week summer program that provides STEM undergraduates the chance to participate in national defense and military research. The program is sponsored by the U.S. Army Research Laboratory in Aberdeen, MD.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
AAMP-UP asks that each student applicant have finished 1 semester of higher education, be currently enrolled in a college or university, and graduate after August 2023. In addition, students must be U.S. Citizens or U.S. Persons. No prior experience with the U.S. military is required.
No summer classes are allowed.
School/Dept.:
Mechanical Engineering
Professor:
Steven
Son
More information: https://engineering.purdue.edu/Energetics/AAMP-UP/index_html
Bone Fracture and Microscale Deformation Processes
Description:
We seek to modify the deformation characteristics of bone through a pharmacological treatment. This project would demonstrate such a concept using animal bone. Treated and untreated bone will be made available for the interrogation of bone by x-rays. Students will be engaged in the data interpretation of x-ray scattering experiments on bone, not subjected to mechanical loads or subjected to mechanical loads.
Research categories:
Biological Characterization and Imaging, Biological Simulation and Technology, Material Modeling and Simulation, Material Processing and Characterization, Other
Desired experience:
Materials Characterization, X-ray techniques; Experience in lab work
School/Dept.:
School of Mechanical Engineering
Professor:
Thomas
Siegmund
More information: https://engineering.purdue.edu/MYMECH
Cognitive State Modeling of Human Machine Interactions in a Level II Driving Simulator
Description:
Effective human-automation interaction (HAI) holds great promise for improved safety, performance, and efficiency across a variety of domains, ranging from transportation to healthcare to manufacturing. These settings have in common a vision of shared autonomy between human and automation. However, realizing the promise of HAI rests on first addressing the fundamental challenge of enabling automation to be aware of, and responsive to, the human with whom it is interacting. Dr. Jain’s research group is thus trying to develop a mathematical control-oriented model for human cognitive states that include trust, self-confidence, mental workload and perceived risk that will allow level II autonomous vehicles to appropriately calibrate these states so that a human’s reliance behavior on the automation is consistent with the reliability of the automation. The goal of this SURF project will be to develop a level II self-driving car simulator using Unreal Engine 5 that will be used as an experimental testbed. The most important criteria for consideration for this position will be prior game development experience using Unreal Engine. Applicants will be presented with a detailed document outlining the functionality requirements of the simulator if their applications are under consideration for the position. Pending the student’s interest, there will be opportunities for the student to contribute the experiment ideation and data analysis.
Research categories:
Human Factors, Other
Preferred major(s):
Desired experience:
Exceptional programming skills, with experience in video game development (preferably) in Unreal Engine.
School/Dept.:
School of Mechanical Engineering
Professor:
Neera
Jain
More information: https://engineering.purdue.edu/JainResearchLab/
Control and Learning of Autonomous Blimps (C-LAB)
Description:
The student will build a small blimp from scratch with additional control board, then design control algorithms for the blimp to auonomously navigate from A to B, and also area exploration based on AI algorithms. The autonomous blimp will also be able to coordinate with human operators, i.e. integrate human's preference/correction
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
basic mathematics; dynamics and control; some previous research experience involving UAVs and human.
School/Dept.:
AAE
Professor:
Shaoshuai
Mou
More information: https://engineering.purdue.edu/AIMS
Data Free Model Extraction
Description:
*** Desired experience: Strong coding skills and motivation in research are required. Background in deep learning, security, and natural language processing is not required but a plus.
*** Possible industry involvement: Some of these projects are funded by Meta/Facebook research awards and J.P.Morgan AI research awards. *** We especially encourage applications from women, Aboriginal peoples, and other groups underrepresented in computing.
*** Project 1. Data-Free Model Extraction
Many deployed machine learning models such as ChatGPT and Codex are accessible via a pay-per-query system. It is profitable for an adversary to steal these models for either theft or reconnaissance. Recent model-extraction attacks on Machine Learning as a Service (MLaaS) systems have moved towards data-free approaches, showing the feasibility of stealing models trained with difficult-to-access data. However, these attacks are ineffective or limited due to the low accuracy of extracted models and the high number of queries to the models under attack. The high query cost makes such techniques infeasible for online MLaaS systems that charge per query.
In this project, we will design novel approaches to get higher accuracy and
query efficiency than prior data-free model extraction techniques.
Early work and background can be found here:
https://www.cs.purdue.edu/homes/lintan/publications/disguide-aaai23.pdf
*** Project 2. Language Models for Detecting and Fixing Software Bugs and Vulnerabilities
In this project, we will develop machine learning approaches including code language models to automatically learn bug and vulnerability patterns and fix patterns from historical data to detect and fix software bugs and security vulnerabilities. We will also study and compare general code language models and domain-specific language models.
Early work and background can be found here:
Impact of Code Language Models on Automated Program Repair. ICSE 2023. Forthcoming.
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair. ICSE 2023. Forthcoming.
https://www.cs.purdue.edu/homes/lintan/publications/cure-icse21.pdf
https://www.cs.purdue.edu/homes/lintan/publications/deeplearn-tse18.pdf
*** Project 3. Inferring Specifications from Software Text for Finding Bugs and Vulnerabilities
A fundamental challenge of detecting or preventing software bugs and vulnerabilities is to know programmers’ intentions, formally called specifications. If we know the specification of a program (e.g., where a lock is needed, what input a deep learning model expects, etc.), a bug detection tool can check if the code matches the specification.
Building upon our expertise on being the first to extract specifications from code comments to automatically detect software bugs and bad comments, in this project, we will analyze various new sources of software textual information (such as API documents and StackOverflow Posts) to extract specifications for bug detection. For example, the API documents of deep learning libraries such as TensorFlow and PyTorch contain a lot of input constraint information about tensors. Language models may be explored.
Early work and background can be found here:
https://www.cs.purdue.edu/homes/lintan/projects.html
*** Project 4. Testing Deep Learning Systems
We will build cool and novel techniques to make deep learning code such as TensorFlow and PyTorch reliable and secure. We will build it on top of our award-winning paper (ACM SIGSOFT Distinguished Paper Award)!
Machine learning systems including deep learning (DL) systems demand reliability and security. DL systems consist of two key components: (1) models and algorithms that perform complex mathematical calculations, and (2) software that implements the algorithms and models. Here software includes DL infrastructure code (e.g., code that performs core neural network computations) and the application code (e.g., code that loads model weights). Thus, for the entire DL system to be reliable and secure, both the software implementation and models/algorithms must be reliable and secure. If software fails to faithfully implement a model (e.g., due to a bug in the software), the output from the software can be wrong even if the model is correct, and vice versa.
This project aims to use novel approaches including differential testing to detect and localize bugs in DL software (including code and data) to address the testing oracle challenge.
Early work and background can be found here: https://www.cs.purdue.edu/homes/lintan/publications/eagle-icse22.pdf https://www.cs.purdue.edu/homes/lintan/publications/fairness-neurips21.pdf https://www.cs.purdue.edu/homes/lintan/publications/variance-ase20.pdf https://www.cs.purdue.edu/homes/lintan/publications/cradle-icse19.pdf
*** Possible industry involvement: Some of these projects are funded by Meta/Facebook research awards and J.P.Morgan AI research awards. *** We especially encourage applications from women, Aboriginal peoples, and other groups underrepresented in computing.
*** Project 1. Data-Free Model Extraction
Many deployed machine learning models such as ChatGPT and Codex are accessible via a pay-per-query system. It is profitable for an adversary to steal these models for either theft or reconnaissance. Recent model-extraction attacks on Machine Learning as a Service (MLaaS) systems have moved towards data-free approaches, showing the feasibility of stealing models trained with difficult-to-access data. However, these attacks are ineffective or limited due to the low accuracy of extracted models and the high number of queries to the models under attack. The high query cost makes such techniques infeasible for online MLaaS systems that charge per query.
In this project, we will design novel approaches to get higher accuracy and
query efficiency than prior data-free model extraction techniques.
Early work and background can be found here:
https://www.cs.purdue.edu/homes/lintan/publications/disguide-aaai23.pdf
*** Project 2. Language Models for Detecting and Fixing Software Bugs and Vulnerabilities
In this project, we will develop machine learning approaches including code language models to automatically learn bug and vulnerability patterns and fix patterns from historical data to detect and fix software bugs and security vulnerabilities. We will also study and compare general code language models and domain-specific language models.
Early work and background can be found here:
Impact of Code Language Models on Automated Program Repair. ICSE 2023. Forthcoming.
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair. ICSE 2023. Forthcoming.
https://www.cs.purdue.edu/homes/lintan/publications/cure-icse21.pdf
https://www.cs.purdue.edu/homes/lintan/publications/deeplearn-tse18.pdf
*** Project 3. Inferring Specifications from Software Text for Finding Bugs and Vulnerabilities
A fundamental challenge of detecting or preventing software bugs and vulnerabilities is to know programmers’ intentions, formally called specifications. If we know the specification of a program (e.g., where a lock is needed, what input a deep learning model expects, etc.), a bug detection tool can check if the code matches the specification.
Building upon our expertise on being the first to extract specifications from code comments to automatically detect software bugs and bad comments, in this project, we will analyze various new sources of software textual information (such as API documents and StackOverflow Posts) to extract specifications for bug detection. For example, the API documents of deep learning libraries such as TensorFlow and PyTorch contain a lot of input constraint information about tensors. Language models may be explored.
Early work and background can be found here:
https://www.cs.purdue.edu/homes/lintan/projects.html
*** Project 4. Testing Deep Learning Systems
We will build cool and novel techniques to make deep learning code such as TensorFlow and PyTorch reliable and secure. We will build it on top of our award-winning paper (ACM SIGSOFT Distinguished Paper Award)!
Machine learning systems including deep learning (DL) systems demand reliability and security. DL systems consist of two key components: (1) models and algorithms that perform complex mathematical calculations, and (2) software that implements the algorithms and models. Here software includes DL infrastructure code (e.g., code that performs core neural network computations) and the application code (e.g., code that loads model weights). Thus, for the entire DL system to be reliable and secure, both the software implementation and models/algorithms must be reliable and secure. If software fails to faithfully implement a model (e.g., due to a bug in the software), the output from the software can be wrong even if the model is correct, and vice versa.
This project aims to use novel approaches including differential testing to detect and localize bugs in DL software (including code and data) to address the testing oracle challenge.
Early work and background can be found here: https://www.cs.purdue.edu/homes/lintan/publications/eagle-icse22.pdf https://www.cs.purdue.edu/homes/lintan/publications/fairness-neurips21.pdf https://www.cs.purdue.edu/homes/lintan/publications/variance-ase20.pdf https://www.cs.purdue.edu/homes/lintan/publications/cradle-icse19.pdf
Research categories:
Big Data/Machine Learning, Cybersecurity, Deep Learning, Other
Preferred major(s):
- Computer Science
- Computer Engineering
- software engineering
School/Dept.:
https://www.cs.purdue.edu/homes/lintan/
Professor:
Lin
Tan
More information: https://www.cs.purdue.edu/homes/lintan/
Disaster Response and Recovery for Water Systems
Description:
Undergraduate students supported by this project must be citizens or permanent residents of the United States or its possessions.This project will involve helping the Professor compile all the information associated with damage and recovery from wildfires in an ongoing project. The student will also help support a separate building plumbing testing and decontamination guidance document being created.
Activities will include reading, analyzing documents, writing a report and presenting results at the end of summer SURF symposium. This project may also have a laboratory component to examine the chemical contamination and decontamination of plumbing materials. The main driver of this undergraduate position is helping the Professor pull together and summarize the studies and efforts the team has completed over the past 3 years. Final reports and analyses are due by the end of summer for the externally funded projects.
Experience with technical writing is preferred.
Activities will include reading, analyzing documents, writing a report and presenting results at the end of summer SURF symposium. This project may also have a laboratory component to examine the chemical contamination and decontamination of plumbing materials. The main driver of this undergraduate position is helping the Professor pull together and summarize the studies and efforts the team has completed over the past 3 years. Final reports and analyses are due by the end of summer for the externally funded projects.
Experience with technical writing is preferred.
Research categories:
Other
Preferred major(s):
- No Major Restriction
School/Dept.:
EEE
Professor:
Andrew
Whelton
Earth Dam Damage during Earthquake
Description:
The safety of embankments and earth dams relies on an adequate assessment of seismically-induced deformations. When subjected to earthquake loading, embankments and earth dams may settle, deform laterally and longitudinally, and may exhibit cracking in the longitudinal and/or transverse directions. Cracks are considered one of the most hazardous consequences of strong earthquake shaking on earthen dams, as they can lead to piping failure due to increased seepage and internal erosion through the cracks. Observed cracks in earth dams after an earthquake are most often associated with tensile stresses and strains resulting from earthquake-induced permanent deformations. Current methods to estimate earthquake-induced cracking seem inadequate, given the widespread damage observed in thousands of dams during the 2008 Wenchuan earthquake. The research is geared at advancing our understanding of the cracking processes in embankments and earth dams during an earthquake and at providing improved tools for practitioners. An important outcome of the work is an updated database of case studies, as well as guidelines and protocols for collection of future information.
The work will combine existing information in the form of case studies and empirical recommendations, and outcomes from numerical simulations. It will expand and modernize databases, update and improve empirical methods, and perform detailed dynamic three-dimensional numerical analyses of actual dams, namely Lenihan Dam in California and Gatun Dam in the Panama Canal.
The student is expected to participate in all aspects of the project, with focus on the analysis of current data and providing recommendations to estimate intensity of cracking.
The work will combine existing information in the form of case studies and empirical recommendations, and outcomes from numerical simulations. It will expand and modernize databases, update and improve empirical methods, and perform detailed dynamic three-dimensional numerical analyses of actual dams, namely Lenihan Dam in California and Gatun Dam in the Panama Canal.
The student is expected to participate in all aspects of the project, with focus on the analysis of current data and providing recommendations to estimate intensity of cracking.
Research categories:
Engineering the Built Environment, Other
Preferred major(s):
- Civil Engineering
Desired experience:
one course in soil mechanics preferred
School/Dept.:
Lyles School of Civil Engineering
Professor:
Antonio
Bobet
Evaluation of Motor Learning in Response to a Wearable Passive Feedback System
Description:
This project involves the analysis of motion capture data and the development of human motor learning metrics to evaluate a wearable system developed by a company sponsor. Specifically, the undergraduate role is to assist in data collection and analysis. The student must take ethics courses and training to be approved for limited participation in human research and be comfortable interacting with healthy human subjects.
Project is co-advised by Dr Laura Blumenschein and Deva Chan
Project is co-advised by Dr Laura Blumenschein and Deva Chan
Research categories:
Biological Characterization and Imaging, Human Factors, Learning and Evaluation, Medical Science and Technology, Other
Preferred major(s):
- Biomedical Engineering
- Mechanical Engineering
- Kinesiology
- Health Science PreProfessional
- Health and Disease
- Occupational Health Science
- Rehabilitation Engineering
- Pre-physical Therapy
- Applied Exercise and Health (Pre)
Desired experience:
Human subjects, physiology, data analysis, statistics, motor learning
School/Dept.:
Mechanical Engineering
Professor:
Laura
Blumenschein
More information: https://lhblumen.wixsite.com/website-1
Evaluation of cartilage mechanics after ACL rupture in a mouse model of osteoarthritis
Description:
Osteoarthritis affects over 32.5 million American adults, impacting mobility and quality of life, and costs over $16.5 billion in direct medical costs in hospitals within the United States. Osteoarthritis is hallmarked by degradation of the various tissues of the joint, formation of bony structures called osteophytes, and joint pain or stiffness – often in that order of progression. Knee osteoarthritis is most common among these, and approximately 1 in 8 cases of osteoarthritis are considered post-traumatic, meaning that degeneration of the tissues in the joint is precipitated from an injury, such as tearing of the anterior cruciate ligament (ACL). To model this disease process, our lab uses mechanical loading to rupture the ACL. We also use atomic force microscopy to characterize changes to the surface profile and biomechanical behavior of tissues. The student working on this project will use AFM to characterize the changes that occur in mouse articular cartilage after ACL injury.
Research categories:
Medical Science and Technology, Other
Preferred major(s):
- Biomedical Engineering
Desired experience:
Biomechanics, imaging and image processing, data analysis, technical writing and communication
School/Dept.:
Biomedical Engineering
Professor:
Deva
Chan
More information: https://engineering.purdue.edu/ChanLab
Exploring Views of Engineering Ethics
Description:
The project will involve reviewing qualitative data to identify how individuals view or experience ethics in engineering. The SURF student will thus learn to conduct educational research with a concerted focus on applying qualitative research methods. Subjects of this research study include faculty members in biomedical, electrical, or computer engineering. The outcome of this research will include better understandings of views and perceptions on ethics in engineering. The ultimate objectives of this work will be to translate these findings to improve engineering ethics instruction.
Research categories:
Learning and Evaluation, Other
Preferred major(s):
- No Major Restriction
Desired experience:
Prior course work in engineering ethics;
Interest in learning more about education research methods;
Good writing and communication skills
School/Dept.:
Engineering Education
Professor:
Justin
Hess
Fabrication and simulation of the efficient joining of dissimilar materials
Description:
The student will start with the metallographic preparation training and make many samples for the experiments. The student will then fabricate the samples using the patented equipment in the lab. The student will work with graduate students on material characterization. The student will also develop the finite element model to simulate the thermal and stress fields. Except the experiments and simulations, the student is expected to read literatures, make a presentation in the weekly meeting, write progress reports.
Research categories:
Composite Materials and Alloys, Material Modeling and Simulation, Material Processing and Characterization, Thermal Technology, Other
Preferred major(s):
- No Major Restriction
School/Dept.:
Nuclear Engineering
Professor:
Yi
Xie
More information: https://engineering.purdue.edu/MINE
Generating efficient data layouts for distributed programs
Description:
This project is part of a larger effort to generate efficient data structures and data layouts to make applications more efficient. Students who join this project will improve their functional programming skills, as well as their knowledge of compilers.
For this project, the student will be working with the gibbon compiler
infrastructure. She will work on writing some benchmarks in a subset
language of Haskell. These benchmarks would be like microservices
benchmarks, aligned with the future focus of developing a
compiler(gibbon) for microservices.
Benchmarking will involve writing significant code in the gibbon front
end language. It will involve making sure that the program output is
correct and matches a similar compiler such as GHC.
We would also like to get timings of these benchmarks and make sure
that the results are as expected. Knowledge of concepts such as
speedups, Amdahl’s law etc. are useful but can be learned as time
progresses.
Optionally, if the student wishes to debug compiler passes, there are
some open issues in the gibbon compiler that can be worked upon.
This would get the student familiarized with the gibbon pipeline and
how to write compiler passes in gibbon. It would also enhance
programming skills in a functional programming language like
Haskell.
For this project, the student will be working with the gibbon compiler
infrastructure. She will work on writing some benchmarks in a subset
language of Haskell. These benchmarks would be like microservices
benchmarks, aligned with the future focus of developing a
compiler(gibbon) for microservices.
Benchmarking will involve writing significant code in the gibbon front
end language. It will involve making sure that the program output is
correct and matches a similar compiler such as GHC.
We would also like to get timings of these benchmarks and make sure
that the results are as expected. Knowledge of concepts such as
speedups, Amdahl’s law etc. are useful but can be learned as time
progresses.
Optionally, if the student wishes to debug compiler passes, there are
some open issues in the gibbon compiler that can be worked upon.
This would get the student familiarized with the gibbon pipeline and
how to write compiler passes in gibbon. It would also enhance
programming skills in a functional programming language like
Haskell.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
Programming skills in a functional programming language,
preferably Haskell.
• Knowledge of a compiler.
• Understanding of the pipeline of compiling a source program to a
binary.
• Version control, such as, git.
School/Dept.:
Electrical and Computer Engineering
Professor:
Milind
Kulkarni
Human-AI interactions for designing
Description:
Student will co-develop human and AI interactions for creativity understanding and development of designs using Chat GPT as a framework. The student will collect the data with the Ph.D. student and do analysis of the data. Additionally student will explore the use of chat gpt to create virtual reality based designs.
Research categories:
Other
Preferred major(s):
- No Major Restriction
School/Dept.:
School of Mechanical Engineering
Professor:
Karthik
Ramani
Mobility Evolution in the US: Evidence from Bike-sharing and Electric Vehicle Adoption
Description:
The project goal is to investigate the trends in next generation mobility in the US as evidenced by bike-sharing ridership and electric vehicle (EV) ownership. Objectives include: i) exploring the effect of the urban built environment and demographical fabric on the usage of bike-sharing; ii) forecasting EV ownership rates in the future considering the influence of incentives, new technologies, and barriers. The student candidate will collect historical data available from public sources such as US Census, US Department of Energy, FHWA and other sources and compile with bike-sharing ridership data from an open- source website, EV registration data and other survey data collected by the mentor/faculty advisor. Using these data, a baseline model (which can be a time series model, or any machine learning model) will be developed that will incorporate the effects of influencing factors affecting bike-sharing ridership and/or EV ownership. The student will get an opportunity to work with scholars in the STSRG group as well as to collaborate with the ASPIRE Engineering Research Center.
Research categories:
Big Data/Machine Learning, Energy and Environment, Engineering the Built Environment, Other
Preferred major(s):
- No Major Restriction
Desired experience:
- Knowledge of MS Excel and programming (R, Python, C++, Java)
- Basic knowledge or course work in statistics (regression, time series)
- Data analysis skills including downloading, cleaning, and merging different datasets
School/Dept.:
Civil Engineering
Professor:
Nadia
Gkritza
More information: https://engineering.purdue.edu/STSRG; https://engineering.purdue.edu/ASPIRE
Model and control strategy development to modernize the pharmaceutical tablet manufacturing process
Description:
The pandemic, such as COVID-19 crisis, has highlighted the requirement for smart manufacturing in pharmaceuticals. Continuous manufacturing is a highly promising solution given its lower capital cost, smaller footprint, and higher efficiency compared to batch manufacturing. Instead of relying on frequent off-line quality tests of samples from each batch, designing an effective and efficient process with knowledge and optimal control strategies becomes increasingly important. Ultimately, an automated smart system can be built to produce high-quality drug products with minimized errors from human intervention.
In a dry granulation tableting line, the powders are transformed into granules before being compressed into tablets. The granulation step can increase the powder flowability by enlarging particle size and improving the powder blend's content uniformity by minimizing segregation. The goals of this project include (1) investigating the impact of granulation on final tablet qualities and building high-fidelity models using first principles and machine learning, and (2) developing soft sensors to predict critical quality attributes such as tensile strength in real time. (3) Implementing model-based process control strategy to control end-to-end pharmaceutical manufacturing processes. All the research works will be conducted in Purdue's newly installed tablet manufacturing pilot plant at the FLEX Lab in Discovery Park.
In a dry granulation tableting line, the powders are transformed into granules before being compressed into tablets. The granulation step can increase the powder flowability by enlarging particle size and improving the powder blend's content uniformity by minimizing segregation. The goals of this project include (1) investigating the impact of granulation on final tablet qualities and building high-fidelity models using first principles and machine learning, and (2) developing soft sensors to predict critical quality attributes such as tensile strength in real time. (3) Implementing model-based process control strategy to control end-to-end pharmaceutical manufacturing processes. All the research works will be conducted in Purdue's newly installed tablet manufacturing pilot plant at the FLEX Lab in Discovery Park.
Research categories:
Big Data/Machine Learning, Chemical Unit Operations, Other
Preferred major(s):
- No Major Restriction
Desired experience:
Basic skills in programming (Python or MATLAB) and powder characterization experience would be a plus, but they are not necessary. All students are welcome if they are interested in hands-on experiments and pharmaceutical processes.
School/Dept.:
Chemical Engineering
Professor:
Gintaras
Reklaitis
Modernization of Pharmaceutical Drug Product Manufacturing
Description:
The continuous mode of manufacturing for pharmaceutical products represents the future of the pharmaceutical industry; it ultimately leads to cheaper and safer drugs, as well as a more reliable drug supply chain. To realize these advantages, however, effective fault detection and diagnostic systems need to be in place, so intervention strategies can be implemented in case the system goes malfunctions.
In this project, we will investigate the ribbon splitting phenomenon in a roller compactor, which is a phenomenon can adversely affect that quality of the product granules coming out of the roller compactor. Little is known about its impact on the product quality as well as the predictability of the phenomenon. The ability to predict this phenomenon can be a boon to effective implementation of condition-based maintenance strategies that have been accepted to be a critical requirement for the successful shift to continuous pharmaceutical manufacturing. This study requires particle technology expertise, which will be provided by Prof. Marcial Gonzalez in Mechanical Engineering, as well as process systems engineering expertise provided by Prof. Rex Reklaitis and Prof. Zoltan Nagy in Chemical Engineering.
In this project, we will investigate the ribbon splitting phenomenon in a roller compactor, which is a phenomenon can adversely affect that quality of the product granules coming out of the roller compactor. Little is known about its impact on the product quality as well as the predictability of the phenomenon. The ability to predict this phenomenon can be a boon to effective implementation of condition-based maintenance strategies that have been accepted to be a critical requirement for the successful shift to continuous pharmaceutical manufacturing. This study requires particle technology expertise, which will be provided by Prof. Marcial Gonzalez in Mechanical Engineering, as well as process systems engineering expertise provided by Prof. Rex Reklaitis and Prof. Zoltan Nagy in Chemical Engineering.
Research categories:
Big Data/Machine Learning, Chemical Unit Operations, Material Processing and Characterization, Other
Preferred major(s):
- No Major Restriction
Desired experience:
Python programming/coding experience is a PLUS, but not required, although enthusiasm to learn is a must. Students interested in a career in powder processing and/or pharmaceutical manufacturing, are encouraged to apply.
School/Dept.:
Davidson School of Chemical Engineering
Professor:
Gintaras
Reklaitis
Operation and characterization of SPT-100 Hall thruster
Description:
Hall thrusters are widely utilized for spacecraft propulsion. Mars exploration missions currently planned by NASA utilize Deep Space Transport which is going to be propelled by Hall thruster technology. In Hall thruster neutral gas propellant is ionized and accelerated in ExB-field configuration to reach high propellant exhaust velocities in the range 10 - 50 km/s.
In this project student will work with Hall thruster SPT-100. The project will include operating the thruster and hollow cathode neutralizer, and measurements of electrical parameters of the thruster, exhaust plasma jet properties, and thrust. The student will use Langmuir probes (and other diagnostics) for measurements of plasma parameters and hanging pendulum thrust stand for the thrust measurements. In addition, the student is going to prepare and update related documentation for AAE 521 Plasma Lab.
In this project student will work with Hall thruster SPT-100. The project will include operating the thruster and hollow cathode neutralizer, and measurements of electrical parameters of the thruster, exhaust plasma jet properties, and thrust. The student will use Langmuir probes (and other diagnostics) for measurements of plasma parameters and hanging pendulum thrust stand for the thrust measurements. In addition, the student is going to prepare and update related documentation for AAE 521 Plasma Lab.
Research categories:
Other
Preferred major(s):
- No Major Restriction
School/Dept.:
AAE
Professor:
Alexey
Shashurin
More information: https://engineering.purdue.edu/EPPL
Plastics in infrastructure and the environment
Description:
Submitted via email
Research categories:
Other
Preferred major(s):
- No Major Restriction
School/Dept.:
Lyles School of Civil Engineering
Professor:
Andrew
Whelton
Quantum Characterization Setup Software Development
Description:
Our research group is in the midst of constructing new quantum optics characterization setups. These setups are used to characterize the photoluminescence properties of different quantum emitters down to the single photon level! This single emitter level property characterization is critical in the development of quantum optical computing, sensing, and communications! We are looking for an undergraduate student that can help with the development of software to control the various parts of the setup and to write the drivers to interface the hardware to the upper-level analysis software required to control the setup.
Research categories:
Big Data/Machine Learning, Deep Learning, Fabrication and Robotics, Material Processing and Characterization, Nanotechnology, Other
Preferred major(s):
- No Major Restriction
Desired experience:
Experience with embedded systems programming, analog to digital conversion experience, driver experience, python software experience.
School/Dept.:
Electrical and Computer Engineering (ECE)
Professor:
Vladimir
Shalaev
RCAC Anvil REU Internship (x6)
Description:
Internship opportunities:
1. Data analytics: Instrument and perform analysis of scientific application workloads on the Anvil system
2. High Performance Computing (HPC): Extend the Anvil system to burst scientific workflows into the Microsoft Azure cloud
3. Kubernetes: To support science gateways applications, extend Anvil’s Kubernetes-based composable subsystem to use cloud-based Kubernetes clusters
4. Containers to Support Education: Enable the use of large-scale notebook deployments to provide interactive access to Anvil in support of education
Applicants must be U.S. citizens. Open to undergrad students from all backgrounds.
1. Data analytics: Instrument and perform analysis of scientific application workloads on the Anvil system
2. High Performance Computing (HPC): Extend the Anvil system to burst scientific workflows into the Microsoft Azure cloud
3. Kubernetes: To support science gateways applications, extend Anvil’s Kubernetes-based composable subsystem to use cloud-based Kubernetes clusters
4. Containers to Support Education: Enable the use of large-scale notebook deployments to provide interactive access to Anvil in support of education
Applicants must be U.S. citizens. Open to undergrad students from all backgrounds.
Research categories:
Big Data/Machine Learning, Computer Architecture, Internet of Things (IoT), Other
Preferred major(s):
- No Major Restriction
Desired experience:
Linux command line experience preferred. However, programming experience is not a requirement for our REU. We seek students with a range of computational backgrounds and will provide research opportunities appropriate for beginner to advanced levels in computing. Our REU is designed to help you develop these computational skills.
School/Dept.:
RCAC
Professor:
Amanda
Hassenplug
More information: https://www.rcac.purdue.edu/anvil/reu
SCALE System-on-Chip: SoC design, verification, programming, and test
Description:
This project is one of several SCALE SURF research projects. By applying to this project, you can be considered for any of the SCALE projects with one application. See https://nanohub.org/groups/scale/research_su23 to view all of the SCALE SURF research projects for summer 2023.
System on Chip Extension Technologies (SoCET) is a long running chip design team intended primarily for undergraduates to get experience in as many aspects of chip design, fabrication, and test as possible. The team is organized like a small chip design company with sub-teams for logic design, verification, chip-layout, analog design, printed circuit board (PCB) design, test, software, and special research projects in collaboration with research groups in ECE. Special projects include applications in hardware security and GPU design. Based on your interests and background, team leaders will work with you to assign you to an appropriate sub-team or special project. Because of the wide range of projects, the experience and skill requirements for SoCET are flexible. Almost any kind of background in circuit design, logic design, circuit simulation, computer architecture, and microcontroller programming will be useful in some part of the team. For more details on possible projects and sub-teams, see https://engineering.purdue.edu/SoC-Team.
In your application, please specify which of the SCALE technical areas you are most interested in. The
technical areas are:
• Radiation Hardening
• System-on-Chip (indicate this if you are interested in SoCET)
• Heterogenous Integration/ Advanced Packaging
• Program Evaluation
Be sure to name any specific SCALE projects you are interested in, and include information about how you meet the required and desired experience and skills for each of these projects. For US citizen students who are interested: you can become part of the Purdue microelectronics program called SCALE, sponsored by the Department of Defense. In SCALE, you will have opportunities for continuing research (paid or for credit) and industry and government internships throughout your time at Purdue. Please apply to SCALE here: https://research.purdue.edu/scale/.
System on Chip Extension Technologies (SoCET) is a long running chip design team intended primarily for undergraduates to get experience in as many aspects of chip design, fabrication, and test as possible. The team is organized like a small chip design company with sub-teams for logic design, verification, chip-layout, analog design, printed circuit board (PCB) design, test, software, and special research projects in collaboration with research groups in ECE. Special projects include applications in hardware security and GPU design. Based on your interests and background, team leaders will work with you to assign you to an appropriate sub-team or special project. Because of the wide range of projects, the experience and skill requirements for SoCET are flexible. Almost any kind of background in circuit design, logic design, circuit simulation, computer architecture, and microcontroller programming will be useful in some part of the team. For more details on possible projects and sub-teams, see https://engineering.purdue.edu/SoC-Team.
In your application, please specify which of the SCALE technical areas you are most interested in. The
technical areas are:
• Radiation Hardening
• System-on-Chip (indicate this if you are interested in SoCET)
• Heterogenous Integration/ Advanced Packaging
• Program Evaluation
Be sure to name any specific SCALE projects you are interested in, and include information about how you meet the required and desired experience and skills for each of these projects. For US citizen students who are interested: you can become part of the Purdue microelectronics program called SCALE, sponsored by the Department of Defense. In SCALE, you will have opportunities for continuing research (paid or for credit) and industry and government internships throughout your time at Purdue. Please apply to SCALE here: https://research.purdue.edu/scale/.
Research categories:
Computer Architecture, Microelectronics, Nanotechnology, System-on-a-Chip, Other
Preferred major(s):
- Electrical Engineering
- Electrical Engineering Technology
- Computer Engineering
- Computer Engineering Technology
- Computer Science
Desired experience:
Almost any kind of background in circuit design, logic design, circuit simulation, computer architecture, and microcontroller programming will be useful on some part of this project.
School/Dept.:
Electrical and Computer Engineering
Professor:
Mark
Johnson
Solar Cells for Field Applications
Description:
Solar Cells for Field Applications
Research categories:
Other
Preferred major(s):
- No Major Restriction
School/Dept.:
Elmore Family School of Electrical and Computer Engineering
Professor:
Peter
Bermel
Structural Engineering for Blast Resistant Design
Description:
Today’s structures are highly engineered buildings and bridges capable of carrying everyday and extreme loads. In this project, students will get to work on understanding blast engineering design with a special focus on building materials like concrete and steel. Undergraduate researchers will work day-to-day alongside graduate students and permanent staff to create test plans, fabricate test specimens, and test large-scale structures to failure. Students will leave this summer with a greater understanding of engineering principles including structural dynamics, impact and blast loading, and composite behavior.
Research categories:
Composite Materials and Alloys, Energy and Environment, Engineering the Built Environment, Other
Preferred major(s):
- No Major Restriction
- Civil Engineering
- Mechanical Engineering
- Mechanical Engineering Technology
- Aeronautical and Astronautical Engineering
- Aeronautical Engineering Technology
- Construction Engineering
- Construction Management Technology
- Engineering (First Year)
- Materials Engineering
Desired experience:
Willing to work in a large-scale structural testing facility which may include some manual labor.
School/Dept.:
Civil Engineering
Professor:
Amit
Varma
More information: https://engineering.purdue.edu/~ahvarma/
TEST 2023 Project: DO NOT APPLY
Description:
Words and stuff
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
all the things
School/Dept.:
Something here
Professor:
Kayla
Kobak
Understanding Lyman Alpha Emitting Galaxies with Spectroscopy
Description:
This project is aimed at understanding the selection of Lyman-alpha-emitting galaxies in the distant universe, selected from the ODIN survey. Using spectroscopic surveys, including HETDEX and DESI, we will validate the selection, and quantify contamination from lower-redshift line emitters and from active galactic nuclei. Additionally, the use of spectroscopy will allow us to confirm young forming clusters of galaxies in the distant universe.
Research categories:
Other
Preferred major(s):
- Physics
Desired experience:
basic coding skills, in particular, with Python
sophomore-to-junior level knowledge in astronomy and astrophysics
School/Dept.:
Physics and Astronomy
Professor:
Kyoung-Soo
Lee
Using network science for precision learning intervention
Description:
The goal of this project is to develop precision learning intervention technology that leverages semantic network science to support early language learning and early intervention for developmental language disorder (DLD). DLD affects approximately 7% of the population, and results in lifelong risks for poor biomedical, educational, and professional outcomes, leading to tremendous costs to individuals and society. Our group seeks to combine recent theoretical and technical advances to develop methods for early identification and intervention of this common, yet understudied condition. Student will participate in coding / development of automated tools that tune early language learning targets according to the knowledge of the learner and will help pilot and assess efficacy of different intervention approaches. Student will work with senior members of the lab (postdocs and lab manager) to develop and acquire data to support the submission of a larger grant application in the Fall.
Research categories:
Big Data/Machine Learning, Medical Science and Technology, Other
Preferred major(s):
- No Major Restriction
Desired experience:
Preferred qualifications include: proficiency in R and/or Python, familiarity with Gitlab, exposure to or interest in learning about network science, and an interest in using remote technology to create engaging and effective early learning interventions in children under the age of 5.
School/Dept.:
SLHS
Professor:
Arielle
Borovsky
Vectorization for secure multiparty computation
Description:
This project will investigate the problem of vectorization in secure multiparty computation (MPC). MPC allows users to compute over encrypted data for security reasons. Unfortunately, this kind of computation is slow. As a result, we are investigating how to speed up MPC programs through compiler optimizations like vectorization. A student working on this project will help implement and benchmark new optimizations. They will gain skills in cryptography, programming languages, and compilers.
Research categories:
Other
Preferred major(s):
- No Major Restriction
Desired experience:
Programming skills
Interest in learning about compilers and programming languages
School/Dept.:
Electrical and Computer Engineering
Professor:
Milind
Kulkarni