2025-2026 IAIER Seed Grant Funding Awardees

Principal Investigator: Erezi Ogbo-Gebhardt
Co-principal Investigator: Agnes Pearcy

The rapid rise of artificial intelligence (AI) in everyday life has heightened the need for accessible public education on AI tools, ethics, and use. While public libraries have historically played a critical role in bridging the digital divide and promoting digital literacy, their emerging role in supporting AI literacy remains underexplored. This seed grant will support a first-stage, mixed-methods study to examine how public libraries in North Carolina are responding to this need. The project will begin with a literature review to establish the current state of research, followed by a statewide survey of public libraries to document AI-related programs, training opportunities, and community engagement strategies. Semi-structured interviews with library staff will provide deeper insight into perceived training needs and the evolving role of libraries as informal educators in the age of AI. Findings will lay the groundwork for a larger-scale study focused on co-designing and evaluating AI education tools in public library settings, aligning with broader digital equity goals in North Carolina.

Principal Investigator: Yang Liu
Co-principal Investigator: Siobahn Day Grady

The Institute for Artificial Intelligence and Emerging Research (IAIER) is a cutting-edge center for Artificial Intelligence (AI) education, research, and innovation. Through this institute, North Carolina Central University (NCCU) aims to foster a dynamic environment that promotes interdisciplinary collaboration and leverages AI to address critical societal challenges. AI and data science have become transformative tools for real-time monitoring and predictive analytics across various domains, including public health, economics, and technology. This proposal presents the establishment of an undergraduate study and research group within the School of Business. The group will focus on AI and data science education, workforce development, computational methods in AI research, and the application of AI technologies for data analysis.

By integrating AI methodologies with large-scale data analysis, this project seeks to foster interdisciplinary collaboration and equip students with the skills necessary for careers in AI-driven analytics. Additionally, this initiative will play a vital role in workforce development by preparing students to meet the growing demand for AI and data science expertise across industries. This proposal outlines the development of an AI and data science education and research program at NCCU. This initiative aims to engage undergraduate students, ignite their interest in AI and data science, and establish sustainable teaching and research initiatives that will drive long-term innovation and academic excellence. By expanding research efforts at NCCU, we support the university’s goal of becoming a High Research Activity (R2) institution.

Principal Investigator: Manna Duah
Co-principal Investigator: Brian Robinson

Drs. Duah and Robinson will oversee a project aimed at leveraging AI tools to develop Collaborative Online International Learning (COIL) between the history departments at North Carolina Central University and the University of Ghana. Students involved in the project will use AI tools to digitize and make archival records accessible online. The seed grant from the Institute of Artificial Intelligence and Equity Research will enable the researchers to initiate a pilot phase of this long-term project.  

Principal Investigator: Tracie Locklear
Co-principal Investigator: Weifan Zheng

The cost of developing and gaining marketing approval for a new drug can range anywhere from $19 million to $2.4 billion. The most time-consuming and costly aspect of a clinical trial is the recruitment of study participants. Studies are becoming more complex, requiring researchers to spend more time explaining studies to participants, answering questions and checking for understanding. This extended consent process is accompanied by long and indecipherable consent documents.

AI and chatbot tools can summarize large amounts of text from clinic notes, patient observations, and relevant research, allowing clinicians to quickly identify key information and derive insight from large literature sources. Chatbots are showing up increasingly in higher education as teaching tools to support student learning, providing a controlled simulation environment to practice and enhance skills, for example. These tools have the potential to transform healthcare education and boost student engagement in the clinical research education space. 

The investigators propose to create a chatbot/agent as a teaching tool to support participant consent for clinical trials in cardiovascular disease, specifically hypertension, one of the top 10 therapeutic areas of research for 2025, and therefore a highly relevant area of focus for our graduates.

Principal Investigator: Penny Carroll

The landscape of social work education is rapidly evolving as technological innovations, such as artificial intelligence (AI) and virtual reality (VR) integrations, become essential technological tools in preparing students for the challenges of contemporary social work practice. For instance, cutting-edge learning methods offer a unique opportunity to enhance competency-based training and provide social work students with real-world experience in a controlled and safe learning environment.

Because of this, AI integration and VR simulation-based interactive tools help students build essential skills in biopsychosocial assessments, interventions, and ethical decision-making while preparing for their field internships. AI-driven learning systems are especially beneficial in increasing student motivation and dedication and help with ethical decision making in complex social work scenarios. These technologies allow for a more personalized learning experience, where students can practice and refine their skills before engaging with actual clients and marginalized community populations. In addition, integrating AI technology in social work education helps students become adept at using digital tools and data-driven methods, which are essential in today’s social work research and practice.

The integration of AI learning systems, VR, and simulation-based technology not only enhances students’ ability to perform in micro, mezzo and macro social work practice but also fosters interdisciplinary collaboration. These technologies prepare students to navigate the complexities of social work with confidence, ensuring they are ready to face the challenges of working with individuals, families and marginalized communities and addressing cultural competence, empathy and systemic issues.

In all, incorporating AI-driven learning systems, VR and simulation-based technology into social work education represents a transformative step forward, equipping future social workers with the skills, knowledge, and technological expertise they need to serve various marginalized populations and communities effectively. This approach will enhance the training and professional development of social work students, ultimately benefiting both the students and the communities they will serve.

Principal Investigator: Selena Judon-Monk

Rapid technological developments provide an opportunity to rethink educational practices that align technology, pedagogy, and disciplinary components. Specifically, for higher education instructors who are less competent with using technological tools in the learning environment, it is imperative to strengthen their digital capabilities. This proposal seeks to better understand knowledge, skills, and use of technological tools with a focus on artificial intelligence (AI) among instructors at North Carolina Central University (NCCU) by leveraging the Digital Competence of Educators framework, the Technology Acceptance Model, and the Transtheoretical Model. Then, the investigator will explore the acceptability and feasibility of AI-guided personal learning plans that address each instructor’s specific strengths and improvement needs as part of the adapted integrative model of digital tools.

Principal Investigator: Jim C. Harper II

This documentary project proposes the production of a high-impact documentary trailer based on the newly released historical book "With Faith in God and Heart and Mind: A History of Omega Psi Phi Fraternity." This documentary trailer will blend oral histories, archival footage, drone video footage, and AI-driven technologies to visually capture and archive the fraternity's historical contributions to social justice, education, and African American leadership over the past century.

This project covers aspects of African American, United States and public history. The documentary will be both a scholarly and public-facing tool for promoting Black history and civic leadership and will serve as a prelude to a larger film project. With funding support from the Faculty Research Award Program (FRAP), this phase will include interviews, B-roll filming using drone technology, and AI-enhanced media curation. The project also seeks to experiment with avatar-based educational content tailored for younger students. The $10,000 FRAP award will be used for travel, drone equipment, and professional editing services. Results will be shared via social digital platforms and selected local educational events.

Principal Investigator: Scott Singeisen

North Carolina Central University’s nascent architecture concentration program is uniquely positioned to leap ahead by integrating artificial intelligence (AI) into its core pedagogy. This proposal requests funding to develop and implement a pilot project that weaves AI-focused methods, studios, and ethical frameworks throughout undergraduate architecture courses. Drawing on recent advances at leading institutions (Ivy League schools, SCI-Arc, the Architectural Association, and the Bartlett), this initiative will harness AI for rapid design iteration, performance simulations, and creative exploration, all while emphasizing cultural and ethical considerations relevant to NCCU’s mission.

Over the course of one academic year, the project team will (1) conduct a focused review of AI-based pedagogical models, (2) develop an AI-integrated design studio and supporting modules for the broader curriculum, (3) establish partnerships with industry professionals and sister universities, and (4) disseminate findings through workshops, conference presentations, and an open-source AI curriculum guide. By bridging hands-on technical training with critical reflection on bias, equity, and societal impact, this project will position NCCU at the forefront of AI-driven architectural education. Our students will become research-minded, critically engaged “AI-native” designers, differentiating our program and enhancing our university’s impact in the state and beyond.

Principal Investigator: Ufana Riaz

Co-principal Investigator: TinChung Leung

Beverage packaging plays a crucial role in the modern beverage industry by preserving product quality and ensuring safety throughout its shelf life. Traditionally, beverage packaging serves four key functions: protection and preservation, containment, communication and marketing, and convenience. It shields beverages from spoilage and deterioration caused by environmental factors such as microbes, light, heat, oxygen, moisture, odors, and physical damage. Packaging is designed in various shapes and sizes to optimize logistical efficiency and handling. Additionally, it serves as a communication tool, conveying essential information to consumers through labeling, including ingredient lists, nutritional facts, and branding.

Beyond conventional packaging, sensors are increasingly being integrated to enhance beverage monitoring via VOC sensing. These sensors are not limited to electronic devices but can also include indicators that change color in response to variations in beverage conditions. They enable real-time monitoring, ensuring better quality control and streamlined supply chain tracking. By improving supply chain efficiency, these sensors help in distinguishing high-quality products from compromised ones. This proposal focuses on developing three machine learning statistical models for smart beverage sensing using conducting polymers, specifically evaluating their effectiveness in detecting oxygen levels, humidity, time-temperature variations, and microbial indicators using multiple linear regression (MLR), multiple non-linear regression (MLNR) and artificial neural networks (ANN). The models will be evaluated by K-fold cross-validation in machine learning.

Principal Investigator: Ping-an Li

Co-principal Investigator: Xialan Dong

Diabetes significantly exacerbates ischemic brain damage, and there is no efficacious drug to reduce the enhanced damage. Ferroptosis is an iron-dependent form of regulated cell death marked by lipid peroxidation and oxidative damage, linked to diseases like cancer and neurological injuries. In stroke, especially among diabetic patients, ferroptosis may worsen outcomes beyond the effects of hyperglycemia alone.

The researchers hypothesize that diabetes increases oxidative stress and disrupts iron metabolism, triggering ferroptosis. This is supported by the finding that, in diabetic stroke models, elevated neutrophil-derived lipocalin-2 raises neuronal iron and lipid peroxides, intensifying ferroptotic damage. These insights suggest that targeting ferroptosis could be a promising therapeutic strategy for diabetic stroke.

This proposal aims to use artificial intelligence (AI) to identify existing drugs that can be repurposed to inhibit ferroptosis and protect the brain in diabetic stroke. We will combine large language models (LLMs) with biomedical text mining and knowledge graph techniques to extract ferroptosis-related targets, pathways, and compounds from PubMed. The information will be structured into a knowledge graph of key entities and relationships, enabling link prediction using models like Rotate. Additionally, we will apply BioWordVec embeddings to find drugs treating conditions like ferroptosis. In Aim 1, we will use this AI pipeline to identify candidate drugs. In Aim 2, these drug candidates will be evaluated in vitro using neuronal models of ferroptosis induced by erastin and in vitro diabetic ischemia. This integrated approach will reveal promising repurposing opportunities and support future external grant proposals.

Principal Investigator: TinChung Leung
Co-principal Investigator: Xialan Dong

On behalf of the NCCU AI Working Group Research sub-committee:

• Qing Cheng
• Siobhan Day Grady
• Carol Huynh
• Kevin Lee
• TinChung Leung
• Sean Tikkun
• Gabriel Peterson
• Subcommittee Co-chair: Karen Webb
• Subcommittee Chair: Nicole S Velmeshev

With the first NCCU AI Symposium, a campus-wide event exploring the theme “Responsible Education in the Age of AI,” the NCCU AI working groups’ research subcommittee successfully promoted a campus-wide educational event that shared NCCU AI talent and expertise within our local community. This setting provided an interdisciplinary forum for research advances, methods, and outcomes centered on the use of AI and engaged students, faculty, and staff at NCCU in opportunities to disseminate their AI-related work.

Based on the momentum of that symposium, with this proposal, the researchers aim to bring continuity and strength to this symposium project. The project's overall goal is to continue advancing AI research dissemination, AI tools used, and AI-related collaborative opportunities at North Carolina Central University, through AI interdisciplinary collaboration, with two specific aims. The first aim is to generate quantitative and qualitative outcome evaluations based on findings from the symposium year 1, via a peer-reviewed publication of learnings about AI taking place at NCCU and in particular within our committee areas of expertise (education, law, ethics, and STEM fields). The second aim is to continue the NCCU AI Symposium, which incorporates learnings from year one to continue advancing AI initiatives at NCCU and beyond.