RESEARCH CENTER
Multimodal AI eXperience (MaX) Lab
Fast Facts
The Multimodal AI eXperience (MaX) Lab advances research at the intersection of artificial intelligence, human behavior, and learning. By combining eye tracking, facial expression analysis, and voice-based affect analysis within a synchronized research environment, MaX enables researchers to better understand how people interact with digital technologies and AI systems. The lab supports interdisciplinary collaboration and innovative research that improves learning, user experience, and human-centered AI design.
Overview
The Multimodal AI eXperience (MaX) Lab at the University of Memphis is a collaborative research facility dedicated to studying biometrics. The lab focuses on understanding visual attention, emotional responses, and human experiences during learning, as well as interactions between humans and AI. It utilizes an iMotions-enabled research ecosystem that integrates synchronized eye tracking, facial expression analysis, and voice-based affect analysis. This infrastructure enables researchers to explore not only participants' self-reported experiences but also how attention, emotion, engagement, and information-processing patterns evolve during interactions with digital content and AI systems.
MaX supports both controlled studies conducted in the lab and scalable data collection remotely. This hybrid approach expands participant access beyond the local area, facilitates larger and more diverse sample sizes, and allows for research in more naturalistic environments. The lab is intended to complement the existing research capabilities at the University of Memphis by focusing on learning sciences, educational technology, human-AI interaction, and multimodal evaluation, rather than consumer neuroscience applications.
Research Areas
- Human-AI interaction and human-centered evaluation of generative AI systems.
- Multimodal learning, multimedia design, and educational technology.
- Visual attention and information processing using screen-based and web-based eye tracking.
- Affective computing through facial expression and voice-based affect analysis.
- Remote, hybrid, and cross-site biometric research methods for larger and more diverse participant samples.
Research Projects
The following areas represent MaX's current research and service priorities. Specific funded projects, publications, collaborators, and reports can be added and updated as the lab's portfolio develops.
- The Sound of Reasoning: Acoustic Profiling of Explainable AI Feedback in ChatGPT Voice Mode. Jeya Amantha Kumar & Jasbir Dhaliwal, Venue: Applied AI Research Conference, Ai4 (Las Vegas, NV — Aug 3–6, 2026). Category: Poster Presentation
Faculty & Researchers
Jeya Amantha David Pandya Kumar
Directior & Principal Investigator
Multimodal AI eXperience (MaX) Lab
Jeya.Amantha.D@memphis.edu
Research expertise includes multimodal learning, human-AI interaction, educational technology, generative AI evaluation, biometric research methods, and the study of attention and affect during technology-supported learning.
Partnerships & Collaborations
MaX is structured as a shared research resource for interdisciplinary collaboration within the University of Memphis and with external academic, industry, and community partners. Formal partnerships are listed and updated as they are confirmed.
Get Involved
Faculty, students, academic collaborators, and external organizations can engage with MAX in several ways:
- Faculty may collaborate on study design, pilot projects, grant proposals, and shared use of the lab infrastructure.
- Graduate and undergraduate students may participate through research assistantships, thesis or dissertation work, independent studies, and methods training.
- Industry and community partners may propose applied evaluation projects involving digital platforms, AI systems, learning technologies, or user experience.
- External academic partners may collaborate on distributed studies that use remote or hybrid multimodal data collection.