Kongju National University (KNU) is a university located in Chungcheongnam-do, South Korea with three campuses in Gongju, Cheonan and Yesan. Kongju National University is one of the leading national research universities of South Korea. The College of Engineering of Kongju National University aims to produce capable engineering experts who will lead the industrial society of the future and who are ready to respond to the info-tech driven world. The College operates 10 departments, 26 majors and two courses. The number of students exceeds 5,000, including graduate students, and more than 180 faculty members are dedicated to education and research in this large-scale college.

Prof. Dookie Kim who is a PI of Korea is a licensed professional engineer both in Korea and in the United States. He received his Bachelor degree in Civil and Environmental Engineering from Korea University in 1993, and he earned his Master and Ph.D. degrees in Civil Engineering from Korea Advanced Institute of Science and Technology (KAIST) in 1995 and 1999 respectively. He spent almost three and half years (September 1999 - February 2003) as a post-doctoral researcher and at Korea Atomic Energy Research Institute (KAERI), University of California, Irvine (UCI), and University of California, Berkeley, and as a senior researcher at UNISON Co. Ltd.
Since March 2003, Dr. Kim has been teaching, researching, and consulting at the Department of Civil and Environmental Engineering, Kunsan National University (KSNU, March 2003 - February 2020, Kunsan) and Kongju National University (KNU, March 2020 - Present, Cheoan), Republic of Korea.


He has published several books and more than 140 and SCI(E) and KCI indexed journal papers. Among his books, Structural Dynamics, which includes soil-structure interaction, wave-structure interaction, and vibration control, is a long-time best seller in Korea for about 20 years. His research interests are: a) dynamic interaction such as vibration control, seismic design, and system identification, b) artificial intelligence such as neural network, support vector machine, and c) probability engineering such as reliability design, LCC analysis, etc.