Organizing Team

Sua Myong obtained both B.S and Ph.D at University of California, Berkeley. Her thesis work was studying one-carbon metabolism measured by mass spectrometry gas chromatography. She received her postdoctorate training at University of Illinois at Urbana Champaign, in the Biophysics laboratory of Dr. Taekjip Ha. She used single molecule fluorescence detection to study DNA and RNA motor protein mechanisms. She started her independent position in the bioengineering department at University of Illinois in 2009, then moved to Biophysics Department at Johns Hopkins University in 2015. Her lab develops and applies single molecule and single cell technique to study biological pathways involved in human diseases including cancer and neurodegeneration. Recent effort has focused on understanding the mechanisms and biological role of liquid-liquid phase separation mediated by disordered RNA binding proteins which are associated with incurable neurodegenerative diseases including Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Lobal Dementia (FTLD).

Dr. Yumi Kim is an Assistant Professor in the Department of Biology at Johns Hopkins University. Her research focuses on the mechanisms governing genetic inheritance from parent to offspring. Her lab studies the behavior of chromosomes during meiosis, a specialized cell division that produces sex cells such as sperm and eggs. Dr. Kim earned a B.S. in Biology from Seoul National University and a Ph.D. in Biological Sciences from UCSD. She did her postdoctoral work at UC Berkeley, investigating how chromosome dynamics are executed and coordinated during meiosis using the nematode Caenorhabditis elegans as a model organism. Her research accomplishment has been recognized by several awards including a Damon Runyon Postdoctoral Fellowship and an NIH Maximizing Investigators’ Research Award (MIRA).

Dr. Seungil Kim is a Research Assistant Professor at the University of Pittsburgh. As an expert in polymer/biomedical engineering, his current research focuses are 1) design, synthesis, characterization, modification, and processing of sustainable polymers, 2) bioresorbable embolization biomaterials for the treatment of intracranial and renal artery aneurysms, 3) medical devices for cardiovascular diseases including artificial grafts, aortic valves, and cardiac patches, and 4) topical target delivery (drug, gene, and cell) using a nanocarrier or medical device. As a principal investigator, he secures the Brain Aneurysm Foundation Grant 2022 and actively leads in developing bioresorbable embolization for treating intracranial vascular malfunctions.

Dr. Hae-Bum “Andrew” Yun is an Associate Professor of Civil, Environmental and Construction Engineering at the University of Central Florida. He earned his MS degree from Carnegie Mellon University and PhD degree from the University of Southern California. Dr. Yun’s research interest is in smart sending, structural health monitoring and non-destructive evaluation for civil infrastructure systems, using various techniques of advanced signal processing, machine learning, computer vision, and smart sensors. His research has been financially supported nationally and internationally, including NSF, USDOT, Florida DOT, Korean government and private companies. Dr. Yun served as the Chair of KSEA SEED East and West in 2015. He also chaired the 8th World Conference on Structural Control and Monitoring (8WCSCM) in 2022 and will chair the 13th International Conference on Bridge Maintenance, Safety and Management in 2026 (IBAMAS 2026). As a structural faculty, Dr. Yun is teaching core civil engineering structural courses, such as reinforced concrete, prestressed concrete and advanced structural mechanics.

Dr. Juhun Lee is an Assistant Professor in the Departments of Radiology and Bioengineering at the University of Pittsburgh. He received his PhD in Electrical and Computer Engineering at The University of Texas at Austin in 2014. Dr. Lee did his postdoctoral training in the Department of Radiology at the University of Pittsburgh for quantitative analysis of breast cancer imaging under the supervision of Dr. Robert M. Nishikawa. His research focuses on quantitative analysis of breast images using artificial intelligence and machine learning approaches. His research on AI/ML research on breast cancer care is currently supported by multiple grants from the National Cancer Institute, NIH. He is also a recipient of a R37 The Method to Extend Research in Time (MERIT) award for his breast cancer risk estimation research.