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The Office of Undergraduate Research (OUR) continues the research scholarship program to recognize undergraduate student engagement in original research, scholarship, or creative work under the guidance of a Purdue faculty or approved mentor. These annual, non-renewable, academic scholarships, in the amount of $1,000 ($500 per semester) and disbursed through the Division of Financial Aid, are funded through an equal matching agreement between the OUR and each of the participating Colleges and Schools.
OUR Scholars are full-time undergraduate researchers who excel in their programs. OUR Scholars are determined for a full academic year and must meet certain program requirements, such as presenting at the annual Spring Undergraduate Research Conference and completing two 1-hour credit courses.
Applicant Information
- Contact: John Lumkes
- Contact: John Lumkes
Applicant Information
- Contact: Toni Rogat
- Contact: Toni Rogat
This program is not currently accepting project proposals.
Applicant Information
- Contact: Kay Kobak
- Contact: Kay Kobak
This program is not currently accepting student applications to its projects.
Applicant Information
- Contact: Amanda Warmbold
- Contact: Pat Hein
Applicant Information
- Contact: Chaonan Liu
- Contact: Chaonan Liu
Applicant Information
- Contact: Will Sartore
- Contact: Will Sartore
Applicant Information
- Contact: Carole Tolley
- Contact: Clarence Maybee
Applicant Information
- Contact: Kelly Blanchard
- Contact: Kelly Blanchard
This program is not currently accepting student applications to its projects.
Applicant Information
- Contact: Ryan Altman
- Contact: Ryan Altman
This program is not currently accepting student applications to its projects.
Applicant Information
- Contact: Emily Meyers
- Contact: Jim Tanoos
Applicant Information
- Contact: Kristy Brewer
- Contact: Kristy Brewer
Applicant Information
- Contact: Susan Mendrysa
- Contact: Susan Mendrysa
This program is not currently accepting student applications to its projects.
Projects
| Term | Active? | Program | Location | Project | Supervisor | Research Area | Description | Type of Work | Actions |
|---|---|---|---|---|---|---|---|---|---|
| Academic Year 2026 | Yes | Honors | West Lafayette | JMHC Afterschool Needs Assessment and Strategic Planning | Temitope Folasade Adeoye Olenloa | Education, Youth Development, Mixed Methods, Longitudinal | The Heads Up Tutoring & Life Skills program is an afterschool program in east Lafayette. We support K-12 youth in Greater Lafayette by providing homework help, mentoring, and summer enrichment opportunities. This community-based research project partners with Heads Up to analyze survey, focus group, and grade reflection forms to support Heads Up in developing a strategic plan and program redesign. Dr. Adeoye Olenloa is currently recruiting undergraduate and graduate students interested in gaining longitudinal, mixed (qualitative and quantitative) research skills. | There is room to propose research questions, engage in data collection and analysis, publish and present research in academic venues, and create a scholarly project with this research. | Apply JMHC Afterschool Needs Assessment and Strategic Planning (1794) |
| Academic Year 2026 | Yes | Polytechnic Institute | West Lafayette | Hacking human behaviour. | Shobhan Shah | Behaviour Design for "Future Work and Learning" | We can’t simply ‘technology’ our way to solving every problem. People hold beliefs, feel emotions, and ascribe meanings to things — and these beliefs can make people reject, underuse, or misuse the solutions we engineer for them. (For example: No matter how many tools have been created to reduce screen addition or social media overuse, people still suffer from these.) So, besides technologies and tools, people have regularly hacked+invented interactions, habits, and even rituals to affect behaviour change. We will continue in that tradition, with a focus on hacking human and inventing behaviours to address modern problems like screen addiction, rage-bait, continuous context-switching, etc. Specifically, we will focus on behaviours related to "future work/learning", e.g. try to make students/workers feel less stressed, exhausted, or demotivated (since this is classified as an impact-area within the Polytechnic). | 1. Behaviour design is a well-established field. We will wade into this space as noobs, and start off by grounding ourselves in some existing research. After which, we will dive headfirst into learning-by-making... 2. We will analyse everyday problems to determine when, how, and why instructional or technological solutions are insufficient to solve these problems — describing at least two examples from personal or observed experience. 3. Through hands-on projects, we will understand a "ritual framework" for understanding human behaviour (and learn how we can hack human behaviour as if it was a regular design problem). We will deconstruct existing rituals, and we will design and prototype "hacks" to overcome selected problems. 4. We will justify various components of our "hacks" on the basis of cultural context, technological constraints, and emotional goals. 6. We will test our "hacks" (with oneself and/or actual people), and iteratively improve them. 7. We will communicate our "hacks" to people who may benefit from them: by producing instruction leaflets and demo videos. | Apply Hacking human behaviour. (1796) |
| Academic Year 2026 | Yes | Science | West Lafayette | Investigating Interdisciplinary Identity Development of STEM Graduate Students in Interdisciplinary Biology Integration Institutes | Emily Nicole Georgopoulos | Biology Education, Social Science | Interdisciplinary (ID) STEM research enables scholars to cross disciplinary boundaries and generate new knowledge For STEM graduate students, participation in such research can shape both disciplinary and ID researcher identities, influencing professional trajectories, belonging, and ability to navigate complex scientific landscapes. However, developing an ID identity presents challenges as students balance conflicting expectations across sociocultural contexts. For example, training in graduate programs and research labs may conflict with perceived outcomes in interdisciplinary centers. Biology Integration Institutes (BIIs) provide innovative spaces for graduate students to engage in ID training and collaboration, serving as incubators for scientific breakthroughs (NSF, 2022) and shaping identity development. Grounded in Figured Worlds theory (Holland et al., 1998), Science Identity theory (Carlone & Johnson, 2007), and Identity-Trajectory theory (McAlpine, 2012), this study examines how graduate students position themselves as ID researchers in BIIs. Using a multiple case study approach, we conducted semi-structured interviews with seven students from different institutions, labs, and personal backgrounds to explore how graduate students in Biology Integration Institutes (BIIs) define and contrast different figured worlds (university, discipline/lab, BII, faculty and peer relationships) and their influence on the development of an interdisciplinary researcher identity. | Mentees will gain experience with qualitative research methods, academic writing, and critical analysis while actively engaging with the research process. Responsibilities will include: 1. Literature review and background research to become familiar with the theories and exemplar studies guiding the work 2. Data collection support, including note-taking, transcription, and organizing qualitative data. You might also sit in during interview sessions with participants. 3. Data analysis, helping to code qualitative data using thematic analysis and using NVivo software 4. Organizing and managing Data, keeping track of transcripts, field notes, and other research materials in a structured and secure manner 5. Assisting in writing literature reviews, methodology sections, or summaries for presentations or publications. 6. Participating in regular meetings to discuss findings, challenges, and next steps -- one-on-one and whole research group meetings if schedule allows. 7. Prepare materials for presentations, conferences, or research posters. | Apply Investigating Interdisciplinary Identity Development of STEM Graduate Students in Interdisciplinary Biology Integration Institutes (1797) |
| Academic Year 2026 | Yes | Honors | West Lafayette | StreamCI Integration for Ecological Data | Kristen Marie Bellisario | Computer Science, Cyberinfrastructure, Ecology, Conservation | This project situates undergraduate research within the NSF-funded National Science Foundation Cyberinfrastructure for Sustained Scientific Innovation (CSSI) initiative, StreamCI, which aims to enable scalable, AI-ready data pipelines for scientific applications. As a participating domain science, our goal is to adapt unstructured ecological datasets—particularly acoustic recordings and camera trap imagery—for integration into the StreamCI framework. These data are central to ongoing conservation efforts focused on species such as the bobcat, gray wolf, and American black bear, where large volumes of sensor data are collected but remain difficult to standardize and analyze at scale. Enabling these data within StreamCI supports a broader “Conservation in Action” goal: transforming raw environmental observations into actionable ecological insight. | The undergraduate researcher will play a central role in transforming unstructured ecological data into structured, machine-readable formats suitable for streaming data pipelines. This includes examining raw datasets to identify patterns, inconsistencies, and missing metadata; defining appropriate data fields and schema; and evaluating how these design choices affect downstream analysis. A key component of the project is student-driven inquiry. The researcher will develop an independent research question related to data representation, selection, or preprocessing in ecological monitoring systems. They will select datasets, implement data transformations, and test how different schema and preprocessing strategies influence the performance of analytical or algorithmic workflows within StreamCI. Through this work, the student will contribute to enabling multimodal ecological data (audio and imagery) to function effectively within a national cyberinfrastructure platform. The project advances both domain-specific knowledge in ecological informatics and broader goals of reproducible, scalable data science in support of wildlife conservation. | Apply StreamCI Integration for Ecological Data (1798) |
| Academic Year 2026 | Yes | Education | West Lafayette | Talk Now, Tech Later: Exploring AI-Supported Math and Language Learning in Early Childhood | Brenda Sarmiento Quezada | Early Childhood Education, Bilingual/Multilingual Education, Language & Literacy Development, Educational Technology / AI in Education | This project explores how young children (ages 3–5) and their families engage in everyday math and language interactions at home, especially in bilingual (Spanish-English) contexts. In the first phase of the project, we study how families naturally use storytelling, play, and daily routines (like cooking or organizing) to support early learning. In this second phase, we will begin to explore how interactive technologies, such as conversational tools or early childhood robots, can support and extend these interactions in meaningful ways. As an undergraduate researcher, you will be part of a team working directly on this next phase of the project. You will help us understand how technology can be designed to support (not replace) family interaction, language development, and early math learning. | Assist with organizing and managing research data (audio, video, transcripts) Support transcription and basic coding of interactions Help prepare materials for working with families (activities, prompts, guides) Assist with data collection in community or family settings Contribute to literature reviews on early childhood, bilingualism, and AI in education Participate in regular research meetings and discussions | Apply Talk Now, Tech Later: Exploring AI-Supported Math and Language Learning in Early Childhood (1799) |
| Academic Year 2026 | Yes | Liberal Arts | West Lafayette | Fear of police violence in the United States | Christopher Han-Fai Seto | Sociology, Criminology | This study will examine how fear of police violence among the US public has evolved from 2014 to 2023. The analysis will draw on nine waves of nationally representative survey data (N=10,612) to explore patterns and dynamics across time, particularly how ethno-racial and political identities have shaped fear of police during the study period. , we show that the stark ethno-racial divide in fear of police violence became particularly pronounced in 2017, corresponding with a widening partisan divide around that same time. Three-way interaction models show that the divergence was largely driven by non-white Democrats and non-white Independents, highlighting how both ethno-racial and political identities jointly shape fear of police—an outcome which is also highly dynamic over time. | Quantitative data analysis (Stata), literature review, writing for academic publication | Apply Fear of police violence in the United States (1800) |
| Academic Year 2026 | Yes | Education | West Lafayette | A multi-informant qualitative inquiry on intergenerational identity integration in LGBTQ+ parent families | Xiang Zhou | Counseling Psychology | How do parent(s)' identities influence who their children become? This research project explores how identity, family, and belonging are developed across generations in LGBTQ+ parent families. We examine how adult children of LGBTQ+ parents make sense of their parent(s)' identities and how these experiences influence their own sense of self. Through in-depth interviews with both LGBTQ+ parents and adult children, this study centers real stories to better understand how families create meaning, navigate identity, and build connection over time. This project highlights the strengths, resilience, and richness of diverse family experiences. | Students will be involved in multiple stages of the research process and will work closely with a collaborative research team. Responsibilities may include: -Coding and analyzing interview transcripts using a structured codebook -Participating in team-based coding meetings and consensus discussions -Assisting with literature reviews related to identity, family relationships, and LGBTQ+ populations -Contributing to conversations about interpreting findings and research implications -Receiving training in qualitative research methods and developing skills in coding, consensus-building, and cross-case analysis Through this experience, students will gain hands on training in qualitative research methods, develop strong analytical and critical thinking skills, and learn how research translates into impact in psychology and family health. Students will also receive mentorship and guidance throughout the research process, with opportunities for deeper involvement (e.g., conference presentations or manuscripts) based on interest and engagement. | Apply A multi-informant qualitative inquiry on intergenerational identity integration in LGBTQ+ parent families (1801) |
| Academic Year 2026 | Yes | Education | West Lafayette | It Takes a Village: Supporting Positive Racial Identity Development in Early Childhood | Amber M. Neal-Stanley | Education; human development and family studies, psychology | It Takes a Village is a community-based research initiative designed to strengthen racial socialization practices among parents and caregivers of Black children ages 3 and 5 in Tippecanoe County, Indiana. Research shows that children notice racial differences as early as three months and can internalize bias during the preschool years, yet many families lack access to structured, culturally grounded resources to support early racial identity development. This project positions parents as their children's first educators and seeks to understand existing family practices, challenges, and needs. The study employs a qualitative, multiple case study design, using semi-structured interviews with approximately 20 parents, guardians, and caregivers. Interviews will explore caregivers' home literacy practices, early childhood experiences, conversations about race and identity, engagement with schools or daycare, and interactions with the larger community. Data collected will be audio- and video-recorded, transcribed, and analyzed thematically to identify patterns, strengths, and gaps in family racial socialization. Findings from the interviews will directly inform the development of the Parent Village program, a six-month culturally affirming workshop series that provides caregivers with research-based tools, curated children's literature, guided activities, and a Family Racial Literacy Toolkit to foster children's positive self-concept, emotional well-being, and school readiness. This project contributes to the fields of education, human development and family studies, psychology, and Black studies by generating context-specific knowledge on Black family processes, supporting culturally responsive parenting interventions, and promoting equitable educational and developmental opportunities for young Black children. | Undergraduate students will serve as research assistants on this project and will support multiple aspects of study implementation and analysis. Their responsibilities may include scheduling and attending virtual interviews, manually transcribing interview recordings, and assisting with coding and thematic analysis of qualitative data. They may also help conduct literature reviews on early childhood racial socialization and related topics and contribute to the development of the Parent Village program, including preparing workshop materials, curating culturally affirming resources, and supporting parent and child activities. All tasks will be performed under supervision and with strict adherence to confidentiality and ethical research practices. | Apply It Takes a Village: Supporting Positive Racial Identity Development in Early Childhood (1803) |
| Academic Year 2026 | Yes | Polytechnic Institute | West Lafayette | AI Competency Development: Using the 5E Instructional Model to Integrate AI-Focused Online Discussions into the Face-to-Face STEM Class | Lisa B Bosman | Future Work and Learning | This study seeks to enhance students' engagement and understanding of AI's best practices in the workplace through structured online discussions. This innovative educational practice was implemented in an advanced project management course delivered to upper-level undergraduate technology students as part of Purdue's AI Working Competency. The motivation behind this initiative stems from the rapidly growing importance of artificial intelligence (AI) in the project management field and the need for effective pedagogical strategies that can bridge theoretical knowledge and practical application. The online discussions were structured according to the 5E instructional model (Engage, Explore, Explain, Elaborate, and Evaluate). Each three-week module corresponds to a specific phase in the instructional model, commencing with an introduction to AI in project management during the Engage module. This approach is unique because it blends asynchronous online learning with synchronous in-person instruction, enabling students to interact meaningfully with course content while fostering a sense of community and collaboration outside the classroom. The implementation of this practice was motivated by the need to enhance student engagement and ensure that the complexities of AI are adequately addressed in the curriculum. The integration of online discussions in this course aligns with current literature advocating for blended learning environments that enhance learner engagement and satisfaction. Research indicates that such environments significantly benefit from the incorporation of social constructivism principles, where collaboration and interaction among peers are crucial for fostering a sense of community. Additionally, studies have shown that peer-to-peer interactions in online settings contribute positively to students’ overall satisfaction and perceived learning outcomes. | This study will be evaluated using a mixed-methods approach. At the end of each module, students (n=28) completed a quantitative retrospective post-then-pre survey along with a narrative reflection to gauge perceived learning gains, relevance, and engagement levels. SPSS will be used for quantitative analysis and NVivo will be used for qualitative analysis. Preliminary feedback suggests that students feel more connected to the material, enhancing their understanding of AI's applications in project management. The research will be disseminated as follows: (1) Fall 2026 Purdue Undergraduate Research Symposium, (2) Spring 2027 Purdue Undergraduate Research Symposiums, (3) June 2027 American Society of Engineering Education (ASEE) conference proceeding, (4) Journal of Purdue Undergraduate Research, and (5) a peer-reviewed journal article. If additional time allows, future work will focus on validating and disseminating additional prompts, delivery approaches, assessments, and further exploring the role of ethics across industry examples. | Apply AI Competency Development: Using the 5E Instructional Model to Integrate AI-Focused Online Discussions into the Face-to-Face STEM Class (1804) |
| Academic Year 2026 | Yes | Polytechnic Institute | Indianapolis | Bridging Theory and Practice: Developing a Cross-Disciplinary Experiential Learning Framework in STEM Education | Esra Tepeli | Experiential Learning, Cross-disciplinary Education | Project description: This project aims to design and test a cross-disciplinary experiential learning framework in STEM education. The framework will specify core components (e.g., mentorship, reflective scaffolding, assessment design, and industry/community partnerships), alignment criteria (linking learning outcomes with experiential activities), and assessment metrics that enable institutions to evaluate and scale experiential learning across multiple departments. Using a mixed-methods approach, the study will integrate a literature review of exemplary experiential models with case studies at Purdue, including surveys and interviews with faculty and students engaged in experiential learning. The goal is to provide a structured, scalable framework that strengthens critical thinking, engagement, and retention among STEM students while aligning with accreditation standards such as ABET. Despite the recognized value of active and experiential learning in fostering problem-solving, engagement, and retention, most existing approaches remain fragmented and discipline-specific. Few studies offer a validated, cross-disciplinary operational framework that defines transferable components and alignment criteria (Borda et al., 2022; Sircar and Orr, 2024). Research also highlights inconsistent outcome measures and a lack of commonly adopted tools for assessing the impact of experiential learning across departments (Santhosh et al., 2023). In addition, institutional barriers (such as faculty workload, resource constraints, and limited coordination structures) remain underexplored, leaving gaps in understanding how to implement and scale experiential learning effectively (Naseer et al., 2025). Approach: This study will employ a mixed-methods design: - First, a comprehensive literature review will identify exemplary experiential-learning models across disciplines in STEM fields. - Second, case studies at Purdue will be conducted through surveys and interviews with faculty and students engaged in STEM experiential learning activities. - Finally, the project will synthesize findings into a cross-disciplinary framework synthesizing best practices, highlighting transferable strategies that support effective implementation across diverse STEM contexts. Comparative analysis will reveal commonalities and outcomes across departments to identify transferable components of effective experiential learning. Expected Contribution: The result will be a structured, evidence-based framework in STEM education enabling institutions to design, implement, assess, and scale experiential learning initiatives across academic departments. It addresses fragmented, discipline-specific approaches by offering systemic strategies to enhance engagement, persistence, and transferable skills. The outcomes have the potential to enhance student persistence in STEM, foster industry readiness, and improve the overall quality of higher education. This project is innovative in three ways: 1.Clarity of transfer: It explicitly defines transfer at both the framework level (institutional practices across departments) and the student level (knowledge and skills gained in one context applied in others). 2.Cross-disciplinary integration: It moves beyond fragmented, discipline-specific approaches by offering a system-wide framework aligned with accreditation and workforce readiness outcomes (Borda et al., 2022). 3.Implementation focus: It systematically examines institutional barriers and mechanisms of transfer, providing practical guidance for sustainable adoption (Sircar and Orr, 2024). The expected impact is a validated framework that higher education institutions can adopt to design, implement, and assess cross-disciplinary experiential learning initiatives. This will contribute to improving student persistence in STEM, enhancing workforce readiness, and advancing the overall quality of higher education. References: - Borda, E., Haskell, T., Boudreaux, A. (2022). Cross-disciplinary learning: A framework for assessing application of concepts across science disciplines. Journal of College Science Teaching, 52(1). - Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall. - Naseer, F., Tariq, R., Alshahrani, H. M., et al. (2025). Project-based learning framework integrating industry collaboration to enhance student future readiness in higher education. Scientific Reports, 15, 24985. https://doi.org/10.1038/s41598-025-10385-4 - Santhosh, M., Farooqi, H., Ammar, M., et al. (2023). A meta-analysis to gauge the effectiveness of STEM informal project-based learning: Investigating the potential moderator variables. Journal of Science Education and Technology, 32(4), 671–685. - Sircar, M., Orr, S. (2024). Conceptualizing an initial framework to support discipline-rich project-based learning in STEM. Education Sciences, 14(7), 793. | Undergraduate research assistants will engage in: - Conducting targeted literature reviews of experiential learning frameworks and assessment practices. - Designing and piloting student/faculty surveys and interview protocols. - Assisting with data collection, coding, and analysis. - Supporting the development of the cross-disciplinary logic model that illustrates inputs, activities, outputs, and impacts of experiential learning. - Collaborating in drafting sections of the framework and dissemination materials (conference posters, brief reports). | Apply Bridging Theory and Practice: Developing a Cross-Disciplinary Experiential Learning Framework in STEM Education (1806) |
| Academic Year 2026 | Yes | Health & Human Sciences | West Lafayette | Next Gen Milks: Flavor and Glycemia | Cordelia A Running | Nutrition, Sensory Science, Health, Diabetes | We are studying how modern types of milk could influence taste and blood glucose responses. We will use commercially available milks, focusing on "A2-type" and ultra-filtered milks compared to "regular" milk. We are testing if people can tell apart these milks based on flavor, as well as whether these milks have different impacts on blood glucose. | Procure and/or prepare samples of milks, label items for testing, schedule participant visits, collect study data, recruit participants, work with graduate student on all these study activities, apply continuous glucose monitors, learn and then conduct data analysis, read scientific papers, participate in lab meetings, complete safety and ethics training | Apply Next Gen Milks: Flavor and Glycemia (1810) |
| Academic Year 2026 | Yes | Science | West Lafayette | Characterization of Microplastics | Gouri Gouri Prabhakar | Atmospheric Science, Air quality, Cloud microphysics | In recent years plastics have been detected in some of the most remote locations on the planet – from the national parks in the United States to Antarctica. It has been hypothesized that the long-range atmospheric transport of micro and nano-sized plastics is one of the mechanisms that can explain their ubiquitous presence. The goal of this project is to understand the role atmospheric microplastics (AMPs) play in cloud formation through laboratory-based cloud condensation experiments. Experiments will be conducted with a set of laboratory created standards. | The student will contribute to the project through laboratory experiments and data analysis. They will be trained initially on laboratory instruments. The student will be required to: • Complete lab safety training required by the mentors • Conduct experiments and maintain a digital logbook. Instruments the student will be operating: Scanning Electrical Mobility Spectrometer and the Cloud Condensation Nuclei Counter. • Perform extensive data analyses on data collected • Regularly meet with the mentors. • Write a technical report of the work completed. | Apply Characterization of Microplastics (1812) |
| Academic Year 2026 | Yes | Science | West Lafayette | Automating Residential Lawn Care in a Drone-Robot-Human Loop | Chunyi Peng | AI, Computer Vision, Robotics, Computer Science | This project aims to leverage the integration of unmanned aerial vehicles (UAVs, aka. drones) and on-ground robots (say, lawn mower robot) to automate residential lawn care. It aims to develop two collaborative loops: drone-robot and drone-robot-human. In the first drone-robot loop, we focus on autonomous lawn care using high-altitude perception to guide on-ground operation so that the ground robot can handle spot-based lawn care issues in a more efficient manner. In the second drone-robot-human loop, we target at human-enhanced AI and AI-enhanced human, where UAV and robots help to greatly reduce human labor efforts and humans (more precisely, lawn care professionals) help to improve lawn care quality done by drones and robots. | The undergraduate scholar will participate an ongoing project led by Prof. Peng and her PhD student team. The type of work includes but not limited to attending project meetings and brainstorming, conducting field experiments, performing computer vision and AI technologies to enable robot-drone cooperation, conducting a user study to get feedcback from humans, working on the reports and/or paper submissions as well as demos/presentations. | Apply Automating Residential Lawn Care in a Drone-Robot-Human Loop (1818) |
| Academic Year 2026 | Yes | Science | West Lafayette | AI-enabled Personalized Metabolic Digital Twin | Guang Lin | AI | This position is for summer stay. This undergraduate research project, part of the NSF-funded NOURISH initiative, focuses on the development of an AI-enabled "Metabolic Digital Twin" to revolutionize personalized nutrition. Students participating in this interdisciplinary collaboration between Purdue’s College of Engineering and College of Science will assist in bridging the gap between wearable hardware and computational modeling. The project involves integrating data from advanced nanoscale biosensors—which track real-time biomarkers like glucose, lactate, and amino acids—into physics-informed AI algorithms that simulate a "virtual you." By analyzing how an individual’s metabolism responds to specific meals, physical activity, and sleep patterns, the research aims to replace generic dietary advice with precise, real-time health recommendations. This work provides students with hands-on experience in nanomanufacturing, probabilistic AI, and digital health, contributing to a system that predicts metabolic outcomes as accurately as a weather app predicts the climate. | Develop Python code, produce figures, and write research report | Apply AI-enabled Personalized Metabolic Digital Twin (1819) |
| Academic Year 2026 | Yes | Polytechnic Institute | Indianapolis | Lean Construction and Sustainability in Construction Management Education | Esra Tepeli | Construction Management; Lean Construction; Sustainability; Project Management; Engineering Education | This undergraduate research project explores how Lean Construction methods can help improve sustainability learning in construction management education. In many courses, students learn about topics such as waste reduction, safety, materials, scheduling, or project impacts, but they may not always see how these ideas connect in real project decision-making. This project will help study that connection and develop practical course materials that make sustainability more understandable and more applicable to industry practice. The student will work with the faculty mentor to examine how Lean tools such as value stream mapping, pull planning, Last Planner concepts, and A3 problem solving can be used to support lower waste, less rework, better workflow, improved safety, and more responsible project outcomes. The student may help review course materials, summarize relevant literature and industry examples, compare how sustainability currently appears across selected construction courses, and help develop a pilot learning module or toolkit for future classes. This is a good project for students interested in construction, project management, sustainability, and improving how future professionals are trained. The project also offers a strong opportunity to prepare an abstract and poster for undergraduate research presentation, which is a key expectation in Purdue’s undergraduate research programs. | Literature review; educational research; case/example analysis; curriculum module development; qualitative analysis; poster preparation. Expected contributions to the research group: The student will contribute by helping gather and organize background sources, summarizing Lean Construction and sustainability concepts for an undergraduate audience, identifying examples from construction management education and practice, and assisting with the development of a pilot teaching/research module. The student will also help prepare a conference-style abstract and a professional research poster. | Apply Lean Construction and Sustainability in Construction Management Education (1821) |
| Academic Year 2026 | Yes | Science | West Lafayette | Designer-Guided Behavior Alignment for Generative Agents | Jason Wu | Computer Science, Human-Computer Interaction, Artificial Intelligence | Generative agents are increasingly used in interactive systems such as games, simulations, and virtual assistants, where they must produce behaviors that are not only believable and useful, but also aligned with designer goals and constraints. However, evaluating and controlling agent behavior remains difficult because these systems are often non-deterministic, context-dependent, and shaped by requirements such as personality, safety, and functional role. Our project studies how to build computational methods and tools for designers and non-ML experts to perform behavior alignment of generative agents. We are interested in several directions, including: i) developing methods to evaluate whether agent behavior matches intended design goals, ii) building tools that help designers test, compare, and refine agent behaviors, and iii) designing training or inference-time techniques to better align generative agents with desired behavior specifications. As a test case, we will focus on AI-driven non-player characters (NPCs) in games and develop tools and methodologies that help game designers steer and validate NPC behavior. | Students will learn and apply skills in the scientific research process, including project ideation, literature review, project discussions, experimental design and implementation (e.g., user studies), data analysis, and results presentation. Depending on project direction, useful technologies may include Python, game engine experience (e.g., Unity), ML libraries (e.g., PyTorch), and game modding experience (e.g., Minecraft API). Prior experience with these is appreciated but not required, and students will develop their technical implementation skills throughout the project. Students should have experience or interest in human-computer interaction and artificial intelligence. | Apply Designer-Guided Behavior Alignment for Generative Agents (1822) |
| Academic Year 2026 | Yes | Science | West Lafayette | A Foundational Approach Towards Robust AI | Bowei Xi | Statistical Understanding for AI Safety | AI is a very important tool implemented in many systems to handle complex tasks such as image classification, object recognition, natural language processing etc. The current wave of AI increasingly penetrates different areas of our daily lives. Consequently AI's structural vulnerabilities become part of the security vulnerabilities in any system that heavily relies on AI to perform critical tasks. This project will study the root cause of AI structural vulnerabilities, which is a much more serious problem than what was reported in the literature and the existing adversarial attacks. The project will focus on understanding AI adversarial sub-spaces. The project will also examine whether strategically increasing training sample size will be able to reduce the total size of adversarial sub-spaces. The project could potentially extend to AI fairness and more explainable AI. | Research activities leading to submission of research papers | Apply A Foundational Approach Towards Robust AI (1833) |
| Academic Year 2026 | Yes | Health & Human Sciences | West Lafayette | Studying how the brain learns movements using a robot | Kwang Seob Kim | Neuroscience | We are looking for a highly motivated undergraduate student who is interested in studying human movements. In this project, we will be using an innovative robot to study arm reaching movement learning. We will train you to use the robot and run experiments with human participants. Our laboratory is located in Lyles-Porter. If you are interested, please send me your resume/CV and transcript. | You will be trained with recruiting participants, and run the experiments. You will also learn how to use a MATLAB program to extract and analyze movement data. | Apply Studying how the brain learns movements using a robot (1839) |
| Academic Year 2026 | Yes | Science | West Lafayette | Investigating the Effects of Magnetic Fields on Human Physiology in the Context of Space Exploration | Caue Sciascia Borlina | Magnetism, Space Exploration, Engineering | Investigating the Effects of Magnetic Fields on Human Physiology in the Context of Space Exploration Identifying factors affecting humans during travel and living in space is vital as we establish a presence away from Earth. It is well-known that spaceflight can affect the human physiology in many different ways including the nervous system, immune system, vision, vestibular, cardiovascular, and musculoskeletal systems, among others. The exposure to low gravity and radiation have been the main focus of past studies on how spaceflight affects these systems; however, growing evidence suggests that weak and/or absent magnetic fields (<20,000 nT) known as hypomagnetic fields, when compared to Earth’s magnetic field of 50,000 nT, could affect the human physiology during spaceflight and presence in hypomagnetic environments such as the Moon and Mars. However, we still lack information key information about how hypomagnetism affects humans, including, for example, at magnetic field strength this might become important. In this project, the student will help develop a experimental setup that will enable conducting a set of experiments relevant to this question. | The student will primarily work on the development of a Helmholtz coil that will be integrated into the biological experiments that we plan on conducting. We are excited for this to be an opportunity to get an undergraduate that might participate in the long term project. | Apply Investigating the Effects of Magnetic Fields on Human Physiology in the Context of Space Exploration (1840) |
| Academic Year 2026 | Yes | Health & Human Sciences | West Lafayette | Emotion and Impulsive Choices: Evidence Accumulation, Inhibition, and Vulnerability | Yu-Chin Chiu | Cognitive Neuroscience | This project will examine how emotion influences impulsive decisions, especially when people need to act quickly or hold back an action. Using two behavioral tasks, EEG, and individual-difference measures of impulsivity, we will test whether emotional context makes people more likely to act before enough evidence is available, or whether it mainly weakens inhibitory control. The goal is to better understand the mechanisms that drive emotion-related impulsive behavior and why some individuals may be more vulnerable than others. | Brainstorm and refine existing behavioral task paradigms, collect behavioral and EEG data, and analyze and interpret the results. | Apply Emotion and Impulsive Choices: Evidence Accumulation, Inhibition, and Vulnerability (1841) |
| Academic Year 2026 | Yes | Health & Human Sciences | West Lafayette | Sleep and School Start Times | A. J. Schwichtenberg | Sleep, policy, and education | This project is led by graduate student, Amy Janis. As part of a policy brief project in the lab, we are collecting the school start times of high schools in Indiana to understand how we as a state compare to the rest of the country. School start times for each year will be used to inform a state focused policy brief around teen sleep health. In 2026, data from the last three years will be turned into a publication. | Data collection, reading, writing, research presentations | Apply Sleep and School Start Times (1842) |
| Academic Year 2026 | Yes | Science | West Lafayette | High-Performance Vector Search for PostgreSQL | Jianguo Wang | Infrastructure for AI | Description: This project investigates techniques for integrating high-performance approximate nearest neighbor (ANN) search into PostgreSQL to support emerging AI and retrieval-augmented generation (RAG) workloads. The student will contribute to the design, implementation, and evaluation of vector indexing extensions for PostgreSQL, including GPU-accelerated index backends (e.g., NVIDIA cuVS) and storage-optimized architectures for cloud-native environments such as object storage (S3). Research activities include implementing and benchmarking index integration with PostgreSQL internals, analyzing query latency and recall tradeoffs across index types and storage tiers, and contributing to systems targeting production deployment. This work builds on the lab's recent publication at CIDR 2026 on decoupled vector search in PostgreSQL. | Research work. Expected to publish a paper. | Apply High-Performance Vector Search for PostgreSQL (1843) |
| Academic Year 2026 | Yes | Science | Indianapolis | Data-driven collaboration leveraging wearable technology for athlete performance optimization | Atinuke Olusola Adebanji | Statistics and Sports Analytics | This independent study engages the student in an applied data analytics project in the Department of Statistics, conducted in collaboration with the Department of Applied Sport Science. The project is explicitly designed to operate at the intersection of academic research and high-performance sport practice, recognising that: • Data visualisation, interactive dashboards, and applied data analysis represent the primary currency of strength & conditioning and performance staff. • Manuscripts and peer-reviewed research publications represent the primary scholarly currency of academia. Using athlete monitoring and performance datasets (e.g., wearable technology, training load, competition demands), the student will (working under the supervision of Statistics Faculty): • Conduct rigorous data cleaning and analysis • Produce dual-track deliverables: o Practitioner-facing tools to inform training and decision-making, and o Scholarly outputs that would form the basis for academic dissemination The overarching goal is to generate actionable insights that enhance athlete performance and health. | Primary Responsibilities: • Perform data wrangling, cleaning, and quality control. • Conduct exploratory and inferential analyses using appropriate statistical or analytical methods. • Develop data visualisations and/or dashboards for applied use. • Maintain regular communication with the statistics mentor and participate in periodic meetings. | Apply Data-driven collaboration leveraging wearable technology for athlete performance optimization (1844) |
| Academic Year 2026 | Yes | Science | West Lafayette | Machine-learning based searching and categorization of atomically thin materials | Yihang Zeng | Physics, computer science | Identification and categorization of atomically-thin materials is one of the bottom neck of the fast-growing field of two-dimensional quantum material research. This crucial step is currently fulfilled by human operator which is labor intensive. Machine-learning algorithm and image identification is an advanced alternative to a manual process. Furthermore, it serves as a cornerstone to fully automated two-dimensional device assembly and fabrication. | Develop machine learning algorithm to categorize two-dimensional materials based on a microscope image. The motorized scanning and searching part which is present in the lab will be used for automation. | Apply Machine-learning based searching and categorization of atomically thin materials (1847) |
| Academic Year 2026 | Yes | Health & Human Sciences | West Lafayette | Speech learning with VR | Kwang Seob Kim | Neuroscience | We are looking for a highly motivated undergraduate student who is interested in studying speech learning using VR. In this project, we will be creating an innovative VR environment and conduct experiments with human participants. Our laboratory is located in Lyles-Porter. If you are interested, please send me your resume/CV and transcript. | You will be using Unreal engine or Unity to create a VR and create a hardware setup so that the VR can communicate with Matlab. You will also communicate with me and graduate students to potentially debug and improve our software. | Apply Speech learning with VR (1848) |
| Academic Year 2026 | Yes | Science | West Lafayette | Fabricating atomic-clean vdW heterostructures for scanning tunneling microscopy | Tiancong Zhu | Condensed Matter Physics, Nanoscience | This project focuses on developing a clean and reproducible method to fabricate graphene trenches using local anodic oxidation (LAO) and integrating them into van der Waals heterostructures. The first objective is to implement LAO trench fabrication inside a glovebox to enable the use of air-sensitive materials such as transition metal dichalcogenides (TMDs). The second objective is to assemble monolayer graphene/hBN heterostructures incorporating LAO-defined trenches that act as electrostatic gates. These structures will be used to study quantum Hall edge states with minimal contamination compared to conventional fabrication methods. | Perform AFM-based local anodic oxidation to fabricate graphene trenches Integrate fabrication into a glovebox environment Assemble van der Waals heterostructures using PVC stacking and hBN pulling Characterize devices using EFM to probe electric field distribution and gate sharpness Analyze device behavior and compare with expected quantum Hall edge state physics. | Apply Fabricating atomic-clean vdW heterostructures for scanning tunneling microscopy (1850) |
| Academic Year 2026 | Yes | Science | West Lafayette | Geographic and Temporal Distribution of Genetic Risk of Chronic Diseases in United States | Geyu Zhou | Human Genetics; Statistical Genetics; Computational Biology | This project will examine genetic risk factors for chronic diseases across different geographic regions and time periods in the United States, with the goal of understanding the drivers behind the rising prevalence of these conditions. | The work deals with data analysis of large scale datasets. | Apply Geographic and Temporal Distribution of Genetic Risk of Chronic Diseases in United States (1852) |
| Academic Year 2026 | Yes | Science | West Lafayette | Programmable atom array-integrated photonic circuits | Chen-Lung Hung | AMO physics and quantum information science | Student working on this project will help develop instrument to realize atom array trapping on a photonic circuit for studying collective atom-light interactions and quantum communications. | The student will explore techniques in radio frequency arbitrary waveform generation and learn optoelectronics for controlling light arrays. | Apply Programmable atom array-integrated photonic circuits (1853) |
| Academic Year 2026 | Yes | Health & Human Sciences | West Lafayette | Qualitative Research Training Using Interviews with Rural Latino/a Youth and Their Families | Yumary Ruiz | Public Health, Human Development and Family Sciences | The Purdue Puentes Project (PPP) is a multi-disciplinary research study focused on Latino/a youth (ages 10-15) in rural, farm worker or agricultural families, and is led by Dr. Zoe Taylor (HDFS) and Dr. Yumary Ruiz (Public Health). This longitudinal project examines youth's mental and physical health, stressors, challenges, and resilience. | Students will work with qualitative data, which includes identifying and interpreting patterns or themes from youth and/or parent interviews using NVivo software. Students may also transcribe one-hour interviews with youth (ages 14-17) and their parents using software such as Otter AI and Sonix AI. All students will be trained prior to initiating work. | Apply Qualitative Research Training Using Interviews with Rural Latino/a Youth and Their Families (1855) |
| Academic Year 2026 | Yes | Science | West Lafayette | Air Quality Modeling | Greg M Michalski | computer progamming, chemistry | Air quality is important to understand because of its impact on human health, climate, and the environment. Computer models are used to predict air quality episodes but are not as accurate as they could be. Stable isotope analysis is a new tool that can be used to refine their accuracy, This is an ongoing project that is incorporating stable isotopes into the EPS's CMAQ model | Computer coding such as python, R, command line scripting (bash, csh) and cluster computing. | Apply Air Quality Modeling (1856) |
| Academic Year 2026 | Yes | Science | West Lafayette | OUR Scholars: US Election Forecasting | Alexandria Volkening | Applied mathematics, data science | This project uses mathematical modeling to forecast the 2026 US midterm elections. It involves website development, data analysis, public science communication, and mathematical modeling. | I am looking for students interested in being part of a multidisciplinary team. Past research experience is not necessary. Research will involve mathematical modeling, programming, sharing forecasts, and website development. | Apply OUR Scholars: US Election Forecasting (1857) |
| Academic Year 2026 | Yes | Health & Human Sciences | West Lafayette | Dietary Fat Absorption | Kimberly K Buhman | Nutrition Science | An elevated blood triglyceride response after a meal containing dietary fat is an independent risk factor for cardiovascular and metabolic diseases. Blood triglyceride levels during this time initially increase and then decrease over time reflecting both input and clearance of triglycerides from blood. The main input of triglycerides is determined by the amount and rate of dietary fat absorption by absorptive cells of the intestine, enterocytes. We hypothesize that dietary fat types differentially contribute to the blood triglyceride response after a meal through differential enterocyte lipid metabolism. This study will investigate the differential enterocyte lipid metabolism in response to a variety of types of dietary fat. | To determine the impact of dietary fat type on blood triglycerides and enterocyte lipid metabolism after a meal, we will conduct triglyceride tolerance tests in C57BL/6J mice using olive oil, corn oil, coconut oil, palm olein, and butter fat. To determine the contribution of dietary fat type on dynamics in enterocyte metabolism, we will conduct a triglyceride tolerance test with the addition of a lipase inhibitor, tyloxapol, to inhibit triglyceride clearance from blood. In addition, we will image enterocytes using electron microscopy and analyze changes in gene and protein expression in enterocytes in response to different types of dietary fat. The undergraduate student on this project will support the triglyceride tolerance tests and will play a significant role in the analysis of the enterocytes by imaging, gene expression and protein expression analysis. | Apply Dietary Fat Absorption (1858) |
| Academic Year 2026 | Yes | Science | West Lafayette | Spatially Resolved Spectroscopy of Supernova Remnants: Connecting Optical Emission-Line Diagnostics to JWST Mid-Infrared Observations | Danny Milisavljevic | Astrophysics | This project involves the analysis of spatially resolved spectral data from the Canada-France-Hawaii Telescope (CFHT), obtained with SITELLE, an imaging Fourier transform spectrometer. The data cover a supernova remnant and allow detailed mapping of optical emission lines including [S II], [N II], and H?. By analyzing these diagnostics, the student will help constrain shock velocities, ionization conditions, and chemical abundances within the remnant. This work directly supports interpretation of mid-infrared observations from the James Webb Space Telescope (JWST), contributing to an ongoing observational campaign led by the supervising faculty member. | The student will contribute to the reduction and analysis of terabyte-scale hyperspectral data cubes. Specific tasks include running data reduction pipelines, performing wavelength calibration, applying continuum subtraction to isolate faint emission features, generating velocity maps, and constructing emission-line ratio diagrams. Results will be compared against radiative shock models to infer properties of the supernova progenitor and explosion energetics. The student's work is expected to contribute to peer-reviewed publications arising from this research program. | Apply Spatially Resolved Spectroscopy of Supernova Remnants: Connecting Optical Emission-Line Diagnostics to JWST Mid-Infrared Observations (1859) |
| Academic Year 2026 | Yes | Polytechnic Institute | West Lafayette | Automation and Intelligent Construction | Jiansong Zhang | Construction Automation, Robotics | We are investigating the use of different robotic systems to help with construction automation, and developing new robotic systems that overcome the limitations of the existing ones in this context. These patents show example outcomes from our project. Zhang, J., Lacny, C., Reardon, N. (2024). Autonomous Robotic System for Placing and Fastening Paneling Material for Building Construction Operations. (Continuation Patent). U.S. Patent Number: 12090628. Date of Patent: Sep 17, 2024. https://patentimages.storage.googleapis.com/55/46/50/022ad70cfaa6ec/US12090628.pdf Zhang, J., Lacny, C., and Reardon, N. (2023). Autonomous Robotic System for Placing and Fastening Paneling Material for Building Construction Operations. Patent Number: 11745356. Date of Patent: Sep 5, 2023. Current U.S. Class: Apparatus for Moving Material to a Position in the Erection or Repair of a Building (414/11) International Classification: B25J 9/16 (2006.01); B25J 11/00 (2006.01); B25J 15/00 (2006.01); B25J 15/06 (2006.01); B25J 13/08 (2006.01); B25J 9/12 (2006.01). | Robotic Planning Robotic Control Robot Design Sensor Data Analysis Hardware Manufacturing Analysis | Apply Automation and Intelligent Construction (1861) |
| Academic Year 2026 | Yes | Libraries | West Lafayette | Generative AI Use in Undergraduate Research | Jerilyn Pia Tinio | Information Studies | With the explosion of generative AI tools available just in the past two years, the traditional term paper assignment has been disrupted. Students can generate text that, unlike prior plagiaristic and/or academically dishonest behaviors, cannot be easily tracked and identified. To move away from disruption and towards effective and appropriate use of AI in student learning, our project seeks to design scaffolded research project assignments, to be integrated into information studies courses. To create appropriate learning activities to achieve our project goals, the team aims to gather data through a needs assessment based on what students are currently thinking concerning the use of AI for academic research. Backward design principles and data gathered from focus group and think-aloud activities will be used to draft learning outcomes and learning activities aimed to help students achieve these outcomes. | OUR scholars will be tasked with recruiting for and conducting think aloud assessments with undergraduate students. Scholars will also be tasked with cleaning the transcripts for these recordings and assisting with data analysis. | Apply Generative AI Use in Undergraduate Research (1862) |
| Academic Year 2026 | Yes | Libraries | West Lafayette | Warhammer Paratext Information as Community: A Games Workshop Business Strategy | Neal Allen Baker | qualitative data analysis, marketing, business primary sources, periodical studies, information monetization, game studies | This project connects information studies to marketing. It does so via Games Workshop (GW), a top 100 British company and their Warhammer brand. Powered by an $8+ billion market cap and $5+ billion annual revenue, GW produces tabletop games involving miniature model combat in trademarked SF/fantasy settings. GW games are at the center of a global “miniaturing pastime” that spans collecting, building, painting, gameplay, and other customer touchpoints including licensed media spin-offs and annual conventions that attract tens of thousands of participants. The pastime is also an information-saturated affinity space within a wider “informational capitalism” – where brands like Warhammer can become a broad and generative lifestyle. This project uses reflexive thematic analysis to highlight paratext information themes across thousands of articles at Warhammer Community, the web locus of GW’s marketing mix. Paratext is understood as information surrounding a central text (e.g. a game like Warhammer 40,000). By examining GW’s deployment of website serial paratext across several years, we build on a 2025-2026 OUR Scholar project that led to a journal article co-written with an undergraduate (Baker & Mosier, 2026). While the article was published in a journal accepting less than 6% of submissions, we also extend a Routledge book chapter about GW wayfinding information as a business asset (Baker, 2025). | This year’s OUR Scholar would handle scraping or other data gathering, data management and coding, and visualizations of GW paratext. The project outcome would be another peer-reviewed article co-written with contributions by an OUR Scholar. | Apply Warhammer Paratext Information as Community: A Games Workshop Business Strategy (1863) |