The full-day conference featured keynote talks, research poster sessions, industry panels, and networking opportunities aimed at advancing human factors research and practice across the Midwest. Attendees included graduate and undergraduate students, industry professionals, faculty, and practitioners from across the region.

 

Organized with support from the HFES Purdue Chapter and numerous volunteers, the event kicked off with opening remarks from Dr. Young-Jun Son, James J. Solberg Head and Ransburg Professor of Purdue’s Edwardson School of Industrial Engineering. The morning keynote was delivered by Cory Kimball of Johnson & Johnson MedTech, who emphasized the importance of user experience in medical device design.

 

Other morning presenters included William Nelson (Humatec), who offered insights into legal case studies through a human factors lens, and Jared Frantz (Rimkus), who presented a risk assessment on coffee temperatures. Dr. Pallabi Bhowmick (University of Illinois Urbana-Champaign) shared graphics of her work on a soft robotic showerhead for adults with mobility challenges, while Dr. Debra Henneberry (Purdue University) discussed the use of wearable technology in aviation.

 

Lightning talks highlighted emerging research from students and early-career scholars, followed by a midday session that featured virtual programming provided by HFES national leadership, focusing on relationship-building and influence within the profession. A panel discussion on artificial intelligence concluded the segment, while the afternoon panel brought together industry experts from diverse sectors who shared perspectives on careers in user experience research and human factors.

 

A reception and poster session, sponsored by the Edwardson School of Industrial Engineering, capped off the day. Research posters were evaluated by a panel of judges including Dr. Susan Kotowski, Jared Frantz, Dr. Pallabi Bhowmick, and Dr. Rebecca Wiener.

 

Emily Garcia received the Best Poster Award for her research titled “Assessing Algorithmic Bias in Clinical Decision Support Systems for Acute Myocardial Infarction: A MIMIC IV Cohort Study.”