Sung-Eui Yoon

Sung-Eui Yoon is a Professor at the Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), where he leads the Scalable Graphics, Vision, & Robotics Lab (SGVR Lab). He also holds affiliations with KAIST AI, KAIST Robotics Program, and CS Robotics. His academic career spans over 15 years at KAIST, where he has established himself as a leading researcher in graphics, vision, and robotics.

Dr. Yoon received his Ph.D. from the Department of Computer Science at the University of North Carolina at Chapel Hill under the advisory of Dr. Dinesh Manocha, completed a postdoc at Lawrence Livermore National Lab, and earned his B.S. and M.S. from the Department of Computer Science at Seoul National University. His academic lineage traces back to Carl Friedrich Gauss through a distinguished line of mathematicians and computer scientists.

His research spans scalable graphics, vision, robotics, and AI problems, with a particular focus on real-time rendering, collision detection, motion planning, and image retrieval. Dr. Yoon's work bridges theoretical foundations with practical applications, resulting in numerous publications, tutorials, and workshops at major conferences including SIGGRAPH, ICRA, and CVPR.

His publications demonstrate a consistent focus on scalability and efficiency in graphics and robotics systems, with recent work emphasizing deep learning applications in image search and advanced motion planning algorithms for robotics. His research has evolved from foundational work in massive model rendering to cutting-edge applications in robotics and AI.

Among his notable recognitions are the Outstanding Paper Award at ICRA 2023, Outstanding Navigation Award Finalist at ICRA 2022, Next-Generation Scientist Award (IT category) in 2019, and Technical Innovation Award from KAIST in 2018.

Dr. Yoon has advised 4 Ph.D. students at KAIST between 2007-2014 and has secured numerous research grants supporting his lab's work. He has also authored influential books including "Rendering" (2018) and "Real-Time Massive Model Rendering" (2008). His teaching portfolio includes graduate courses on Web-Scale Image Retrieval, Motion Planning, and Graduate-level Computer Graphics, as well as undergraduate courses in Computer Graphics and Data Structures.