Dr. Yunmei Liu is a co-author of “Cognitive Workload Assessment in Procedural Tasks,” published online in Human Factors on September 2, 2026. The collaborative paper is first-authored by Niosh Basnet.

Understanding Workload as Tasks Unfold

The study examined 30 participants completing cooking tasks under routine conditions and conditions involving disruptions and time pressure. Researchers combined self-reported workload with eye and skin-conductance measures to examine how demands changed during the tasks.

Individual disruptions could produce brief increases in workload, while accumulating anomalies could sustain higher demands. The physiological measures differed in their sensitivity, with blink rate providing a useful indicator in this task setting. These findings can inform assistance that responds to both immediate difficulties and the cumulative demands of procedural work.

Read the publication in Human Factors

Recognizing Support for Student Success

Based on university-wide student nominations, the Student Champion recognition honors exceptional support of student success. Dr. Liu is grateful to the students who shared their experiences and to the University of Louisville community for recognizing the importance of mentorship and sustained support in students’ academic and professional development.

The MINDxAI Lab is excited to welcome two new Ph.D. students, Qunli Liu and Udit Kumar Das, as they begin the next stage of their academic journeys with our lab.

Welcoming Qunli Liu

Qunli holds an M.S. in Data Science from the University of California, Irvine and a B.A. in Data Science from the University of California, Berkeley. His research interests include physiological signal analysis, behavioral data analysis, and statistical modeling. At MINDxAI, his work examines human operator performance in surveillance tasks and how environmental factors shape human activity and mobility behavior in urban environments. He also supports the lab’s smart manufacturing and rehabilitation robotics projects.

Welcoming Udit Kumar Das

Udit holds an M.S. in Industrial and Systems Engineering from the University of Louisville, an M.S. in Applied Statistics and Data Science from Jahangirnagar University, and a B.S. in Petroleum and Mining Engineering from the Military Institute of Science and Technology in Bangladesh. His research focuses on human factors, driver behavior, cognitive workload, and human–AI interaction in transportation. His current work investigates how aggressive driving behaviors affect novice drivers’ visual attention, workload, and driving behavior in simulated driving environments. He leads the lab’s Human-Autonomy/AI Teaming project and supports the Aggressive Driving in Mixed Traffic project.

We hope Qunli and Udit will quickly settle into the new rhythm of Ph.D. life and feel at home in our lab community during the coming semester. We are excited to support their growth, learn from their perspectives, and see the ideas and contributions they will bring to MINDxAI Lab! We look forward to everything they will accomplish in the years ahead!

The MINDxAI Lab congratulates Udit Kumar Das on successfully defending his master's thesis in Industrial and Systems Engineering at the University of Louisville.

A Milestone for the MINDxAI Lab

Udit joined the lab in Fall 2025 and conducted thesis research on the physiological patterns of novice drivers when they encounter aggressive driving conditions. His work was supported by a University of Louisville Graduate Student Council research grant and contributed to the lab’s broader research on driver safety and human-centered transportation systems.

Udit is the first master's student advised by Dr. Yunmei Liu to complete and defend a thesis through the MINDxAI Lab. He will remain with the lab to continue his research as a Ph.D. student.

Led by MINDxAI Lab PhD student Moajjem Hossain Chowdhury with Dr. Yunmei Liu, “Communication Barriers in Patient-Provider Interactions in Health Care: Scoping Review” is now available open access in the Journal of Medical Internet Research.

Beyond a List of Communication Barriers

Following PRISMA-ScR, the review searched four databases, screened 6,233 records, and synthesized 253 empirical studies. It integrates linguistic, cultural, psychological, and patient–provider mental-model barriers into one framework, showing how they overlap and relate to patient experience, healthcare access, clinical decision-making, and health outcomes.

The synthesis identifies important gaps, including limited research on psychological and mental-model barriers and a lack of real-time behavioral, nonverbal, and physiological indicators. These findings provide a foundation for future interventions and technology development: adaptive support requires understanding which barriers are present, how they interact, and how they can be recognized during clinical encounters.

The lab’s next phase will move from evidence synthesis to empirical data analysis, examining how these barriers, individually and jointly, are associated with healthcare experiences and outcomes.

Read the publication in JMIR