“Instead of responding when it happens, why don’t we prevent it by taking action now!”
ABOUT ME
PhD Student in Human-Centered Computing | Computing for Social Good Lab | University of Florida
My name is Alaina Smith. My research interests center on the design and development of AI-driven health education technologies that address health disparities in underserved and urban communities. I focus on creating theory-based, human-centered interventions that promote healthy aging, wellness across the lifespan, and sustainable behavior change. By integrating artificial intelligence, digital health tools, and thoughtful technical design, my work aims to improve accessibility, enhance user engagement, and advance equity in health outcomes.
Research Interest
Artificial Intelligence (AI), Digital Health, Health Disparities, Healthy Eating, CS Education, Underserved Communities, Behavior Change
Research Experience
July 2025-Present
January 2026 - Present
April 2024 - December 2024
August 2023 - May 2024
January 2023 - May 2023
August 2021 - August 2022
January 2020 – April 2021
Evidence-Based Embodied Conversational Chatbot for Food Security Awareness at HBCUs
Developing an interactive theory-based chatbot using AI grounded in the Theory of Planned Behavior to educate students about campus food‑security resources, aiming to shift behavioral, normative, and control beliefs.
Beyond Code Generation: Student Perceptions of Generative AI during Programming Tasks
Understanding how students' mental models and role framing of generative AI affect self-efficacy when completing programming tasks.
Optimizing Interactive Machine Learning Tools to Support Plant Scientists using Human Centered Design
Contributed to the design and development of research instruments for evaluating interactive machine learning tools, applying human-centered design to support plant scientists.
Understanding the effectiveness of mobile applications that promote healthy eating
This survey paper aims to analyze current applications used in mobile applications to promote healthy eating and understand effectiveness.
A Disease tailored grocery list application using positive reinforcement to measure self-efficacy
The purpose of this study is to explore the use of technology to provide health education for people with Type 2 diabetes. Tools: Xcode
Evaluating New Technology for equitable and secure voter verification
The purpose of this study is to investigate the utility of using facial verification technology to verify voters. Tools: Amazon Rekognition, Python
IDENTIFYING THE RISK OF ALZHEIMER’S IN OLDER ADULTS USING AN INTERACTIVE SIMULATOR
The purpose of this study is to build decision trees to identify the risks of Alzheimer’s Disease and build a simulator to predict outcomes. Tools: Excel, JavaScript, CSS, HTML
May 2020 – August 2020
MOBILE APPLICATION DEVELOPMENT TO PROMOTE PHYSICAL HEALTH AND ACTIVITY IN THE AGING COMMUNITY
The purpose of this study was to promote and motivate the aging community to participate in physical activity while providing a safe way to do so and enhance technology skills using a mobile game. Role: undergraduate student; Tools: Unity Software, C#
May 2019 – August 2019
DETECT SMOKING EVENTS USING AI IN SMARTWATCH TECHNOLOGY
This research was aimed to study the habits of cigarette and vape smokers using smartwatches and use the data to find ways to intervene when the person attempts to smoke. Tools: Android Studio, Octave, Excel
Publications
1. Gilbert, J.E., McKenzie, J., Smith, A., & Thompson, L. (2023) Evaluating New Technology for Equitable and Secure Voter Verification, Tech Policy Press, Technology and Democracy, April 7, 2023, https://techpolicy.press/evaluating-new-technology-for-equitable-and-secure-voter-verification/
2. Alaina Smith and Juan E. Gilbert. 2024. Computing for Social Good: University of Florida.
XRDS 30, 2 (Winter 2023), 38–39. https://doi.org/10.1145/3637464
3. Gilbert, J.E., McKenzie, J., Smith, A., Jennings, J., & Hart, A. (2024). Two-Step Ballot Verification: Mitigating the Impact of the Hawthorne Effect on Vote-Flipping Studies. In Proceedings of the Human Factors and Ergonomics Society (HFES)Annual Meeting, Phoenix, AZ, USA, pp. 1–5. DOI: https://journals.sagepub.com/doi/full/10.1177/10711813241279792
4. Moon Rembert, D., Smith, A., Thompson, L., Jennings, D., Solomon, A. & Gilbert, J. (2025). InterestMe Math: A Math Word Problem Rewrite System Integrating Career Interests to Enhance Learning Outcomes. In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 698-718). Barcelona, Spain: Association for the Advancement of Computing in Education (AACE). Retrieved May 28, 2025 from https://www.learntechlib.org/primary/p/225974/.
5. Thomas, S.V., McKenzie, J., Smith, A., Gilbert, J.E. (2025). User-Centered Design for Career and Academic Motivation in Student-Athletes. In: Smith, B.K., Borge, M. (eds) Learning and Collaboration Technologies. HCII 2025. Lecture Notes in Computer Science, vol 15806. Springer, Cham. https://doi.org/10.1007/978-3-031-93564-0_11
6. Nadia S. J. Morrow, Atayliya Irving, Jasmine McKenzie, Alaina Smith, and Juan E. Gilbert. 2025. The Invisible Participants: How Computing Education Research Fails Students with Disabilities. In Proceedings of the 2025 Conference on Research on Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT 2025). Association for Computing Machinery, New York, NY, USA, 115–121. https://doi.org/10.1145/3704637.3734739
7. Smith, A. (2025) Computing with Purpose: Building CS Learning Pathways Rooted in Real-World Change, In: BICE, IEEE (Accepted)
8. Atkinson, A., & Myrthil, T., & Stofer, K. A., & McKenzie, J., & Smith, A., & Ojo, D., & Naikodi, M. A., & Bista, D., & CHEN, Y., & Obajemu, O., & Regmi, N., & Broaddus, B. A., & Zare, A., & Anthony, L., & Waisome, J. A. M. (2026, March), Research Participants who Helped Design AI/ML Data Training Interface Trend toward Increased Interest in Research Career Paper presented at 2026 ASEE Southeastern Section Conference , University of Memphis, Tennessee. 10.18260/1-2--58004
