2026-08-03: REU Renewal Proposal Awarded by NSF

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I am excited to share that our proposal, "REU Site: Human-AI Interaction and Evaluation in Web and Information Systems," has been funded by the National Science Foundation. This is a renewal of our previous NSF REU grant, "Disinformation Detection and Analytics." The renewal provides $372,000 to support at least eight undergraduate students each year in conducting on-site research at Old Dominion University and the Virginia Modeling, Analytics, and Simulation Center (VMASC) during the summers of 2027–2029. 

As AI technologies proliferate across web platforms and information systems, the nature of human-computer interaction is fundamentally changing: users increasingly engage with and rely on adaptive, generative, and often opaque AI agents such as chatbots. This shift makes human-AI interaction (HAI) a critical research topic, as researchers must now understand and shape how humans and AI systems communicate, collaborate, build trust, and share decision-making responsibilities.

Recognizing the growing importance of HAI research, this project renews an REU Site focused on Human-AI Interaction and Evaluation in Web and Information Systems at ODU, led by the Department of Computer Science in collaboration with VMASC and the Department of Communication Disorders & Special Education. The goal of our REU Site is to provide inquiry-based, experiential research training that enables undergraduate students to become independent, contributing researchers. To achieve this goal, we will involve undergraduate students from a wide spectrum of backgrounds as colleagues in ongoing research projects and encourage them to pursue graduate study in STEM disciplines.

The REU Site includes 8 mentors, of which 4 are in the Web Science Digital Library (WS-DL) research group. 

In this REU program, students will learn human-AI interaction concepts, methods, and interfaces; tools and skills for accessing, cleaning, preprocessing, and visualizing diverse datasets, including human-generated, AI-generated, and other web-related data; state-of-the-art computational methods — including multimodal large language models and machine learning algorithms — for building analytical and predictive model prototypes with open-source programming tools to address research challenges in HAI; and key metrics for evaluating research tasks, comparing baseline models, and producing publication-quality results. Students will also develop essential research skills, including critical thinking, technical writing, and research presentation. This program strengthens the nation's research capacity by training a new generation of diverse, well-prepared researchers in the rapidly growing field of human-AI interaction.

Student recruiting will begin in January 2027 and continue for the following three years. For more information, please visit our website: https://oducsreu.github.io/ and see our final presentation blog posts for years 3, 2, and 1.

We express our gratitude to NSF for their support of undergraduate research! 

-- Jian Wu

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