UROP Project

Using Artificial Intelligence to Support Social Connection and Healthy Aging

Health Informatics, Data Science, Machine Learning, AI

Research Mentor: Dr. Zhe He,
Department, College, Affiliation: School of Information, Communication and Information
Contact Email: zhe@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Balu Bhasuran He, Him, His
Research Assistant Supervisor Email: bb23u@fsu.edu
Faculty Collaborators: Dr. Mia Lustria She, her, hers
Faculty Collaborators Email: mlustria@fsu.edu

Looking for Research Assistants: Yes
Number of Research Assistants: 4
Relevant Majors: Computer Science; Information Technology; Information, Communication and Technology (ICT); Public Health; Psychology; Behavioral Neuroscience; Biological Science; Statistics; Data Science; Nursing; Social Work; Sociology; and related majors.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Yes
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:

• Day: Friday, September 4
  Start Time: 12:00
  End Time: 12:30
  Zoom Link: https://fsu.zoom.us/j/92169841983

Project Description

This research opportunity focuses on the development and evaluation of human-centered artificial intelligence (AI) technologies to improve health communication, patient engagement, and healthy aging. Undergraduate research assistants will have opportunities to contribute to two ongoing projects in the FSU eHealth Lab and Institute for Successful Longevity.

LabGenie is an AI-based educational tool designed to help patients better understand their laboratory test results. The project uses large language models and a multi-agent AI framework to generate personalized, easy-to-understand explanations of lab results and support patients in preparing for conversations with their healthcare providers. Undergraduate researchers will support an upcoming study evaluating how different AI-generated explanations affect users' understanding, trust, and ability to identify appropriate next steps.

ALCOVE explores how AI can help older adults identify and engage with meaningful social, recreational, educational, and wellness opportunities in their communities. The project aims to develop an AI-powered social concierge that provides personalized recommendations based on an individual's interests, needs, and preferences, with the broader goal of promoting social connection and healthy aging.

Students may contribute to activities such as literature reviews, preparation of study materials, evaluation of AI-generated content, participant recruitment and research coordination, data collection and management, qualitative and quantitative data analysis, and dissemination of research findings. Students will gain hands-on experience with interdisciplinary research at the intersection of AI, health informatics, human-centered design, and aging research. No prior AI research experience is required; training and mentorship will be provided.

Research Tasks: Evaluating and annotating large language model (LLM) outputs for accuracy, relevance, readability, and appropriateness; conducting literature searches and reviews related to AI, health communication, and healthy aging; assisting with preparation of study materials and research protocols; recruiting and communicating with research participants; supporting participant screening, scheduling, and data collection; assisting with interviews, focus groups, and usability studies; organizing and managing research data; coding qualitative data; assisting with basic quantitative and qualitative data analysis; and contributing to research presentations, reports, and manuscripts.

Skills that research assistant(s) may need: Strong communication and interpersonal skills; attention to detail and ability to follow research protocols; good organizational and time-management skills; basic computer skills (e.g., Microsoft Office/Google Workspace); ability to conduct literature searches and summarize scientific information; willingness to learn research methods and data analysis; and an interest in AI, health, aging, or human-centered technology. Experience with data analysis, qualitative research, programming (e.g., Python or R), or AI/LLMs is helpful but not required. Training will be provided.