Soo-Young Lee received B.S., M.S., and Ph.D. degrees from Seoul National University in 1975, Korea Advanced Institute of Science in 1977, and Polytechnic Institute of New York in 1984, respectively. From 1977 to 1980 he worked for the Taihan Engineering Co., Seoul, Korea. From 1982 to 1985 he also worked for General Physics Corporation at Columbia, MD, USA. In early 1986 he joined the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, as an Assistant Professor and now is a Full Professor. at the Department of Electrical Engineering and also Department of Bio & Brain Engineering. From June 2008 to June 2009 he also worked for Mathematical Neuroscience Laboratory at RIKEN Brain science Institute for his sabbatical leave.

In 1997 he established Brain Science Research Center, which is the main research organization for the Korean Brain Neuroinformatics Research Program. The research program is one of the Korean Brain Research Promotion Initiatives sponsored by Korean Ministry of Science and Technology from 1998 to 2008, and currently about 35 Ph.D. researchers have joined the research program from many Korean universities.

He is a Past-President of Asia-Pacific Neural Network Assembly, and has contributed to International Conference on Neural Information Processing as Conference Chair (2000), Conference Vice Co-Chair (2003), and Program Co-Chair (1994, 2002). He is on Editorial Boards for Neural Processing Letters and Cognitive Neurodynamics journals. He received Leadership Award and Presidential Award from International Neural Network Society in 1994 and 2001, respectively, and APPNA Service Award and APNNA Outstanding Achievement Award from Asia-Pacific Neural Network Assembly in 2004 and 2009, respectively. From SPIE he also received Biomedical Wellness Award and ICA Unsupervised Learning Pioneer Award in 2008 and 2010, respectively.

His research interests have resided in Artificial Brain, alias Artificial Cognitive Systems, the human-like intelligent systems/robots based on biological information processing mechanism in our brain. He has worked on the auditory models from the cochlea to the auditory cortex for noisy speech processing, information-theoretic binaural processing models for sound localization and speech enhancement/separation, the unsupervised pro-active developmental models of human knowledge and situation awareness capability with multi-modal man-machine interactions, and the top-down selective attention models for superimposed pattern recognitions. Recently he is also working on understanding human implicit intention from multimodal data including fMRI, EEG, GSR, audio and visual data. Especially, he is interested in combining computational neuroscience and information theory, of which examples are Independent Component Analysis for blind signal separation and discriminant feature extraction, and also top-down attention for robust classification. His research scope covers the mathematical models, neuromorphic chips, and real-world applications. Recently, he is also interested in intelligent man-machine interface with EEG, eye-gaze, etc.