Dr. Yeo is a Woodruff Faculty Fellow, Associate Professor in the Mechanical Engineering and Biomedical Engineering, and the Director of the Center for Human-Centric Interfaces and Engineering at Georgia Institute of Technology. His research focuses on the areas of nano-microengineering, soft materials, molecular interactions, and biosystems, with an emphasis on nanomembrane bioelectronics. Dr. Yeo received his Ph.D. in mechanical engineering at the University of Washington, Seattle. Afterward, he was a postdoctoral research fellow at the University of Illinois at Urbana-Champaign. Dr. Yeo has published over 100 peer-reviewed articles, including many in top-quality journals, including Nature Materials, Nature Machine Intelligence, Nature Communications, and Science Advances. In addition, Dr. Yeo is an IEEE Senior Member and a recipient of a number of awards, including the NIH Trailblazer Young Investigator Award, IEEE Outstanding Engineer Award, Imlay Innovation Award, Lucy G. Moses Lectureship Award, Sensors Young Investigator Award, American Heart Association Innovative Project Award, and Outstanding Yonsei Scholar Award. Dr. Kim is an Assistant Professor of Radiology at the BioMedical Engineering and Imaging Institute at the Icahn School of Medicine at Mount Sinai. His research focuses on developing skin-like, stretchable, and wireless electronic systems that can be gently and seamlessly mounted on the skin. Leveraging a wide range of emerging manufacturing technologies, such as MEMS, aerosol-jet and screen printing, laser micromachining, and electronic chip integration, Dr. Kim strives to translate the concepts of smart medicine into practical applications that can be deployed in clinical settings. His most recent research outcomes include fully-printed wearable electronics, multi-functional health monitors with elastomeric properties tailored for specific age groups, and face-wearable electronics for portable ocular therapies. These projects are representative of Dr. Kim’s aim to combine breakthroughs in materials, manufacturing, and AI-driven data analysis toward improving patient outcomes as well as general health care.