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About CEO


 Prof. Jooyoung Lee, Good Intelligence CEO, received his PhD in Physics (1990) under the supervision of Prof. JM Kosterlitz (2016 Nobel laureate in Physics).

 Since 1994, his research focused on solving the protein folding problem, and he led a KIAS (Korea Institute for Advanced Study) team in the CASP (protein structure modeling) competition for CASP5-CASP12 (2002-2016).

 His CASP experience can be highlighted by the top performance in the area of template based modeling (TBM) at CASP11 (2014) and CASP12 (2016) along with his six consecutive invited talks at CASP7-CASP12. Accurate protein structure modeling in the TBM category is considered to be most relevant for successful new drug discovery.

 Motivated by the superhuman performance of AlphaGo, with an ultimate eye towards improvements in protein folding prediction, Prof. Lee’s research interest temporarily turned to deep learning.

 He started with its application to the game of Go, and implemented a unique deep learning method to compete in world Go AI competitions (2nd place in the 2019 Fuzhou Go AI competition; 3rd place in the 11th Computer Go UEC Cup).

 Prof. Lee, a professor in the school of computational sciences at KIAS, has published more than 120 peer-reviewed papers in various SCI journals. Many of these papers are well cited [(over 4700 citations from SCI journals and over 3900 citations to his first/corresponding-authored papers (as of Sept. 2018)]. His publication H-Index is 34.

Prof. Jooyoung Lee, Good Intelligence CEO, received his PhD in Physics (1990) under the supervision of Prof. JM Kosterlitz (2016 Nobel laureate in Physics).

Since 1994, his research focused on solving the protein folding problem, and he led a KIAS (Korea Institute for Advanced Study) team in the CASP (protein structure modeling) competition for CASP5-CASP12 (2002-2016).


 His CASP experience can be highlighted by the top performance in the area of template based modeling (TBM) at CASP11 (2014) and CASP12 (2016) along with his six consecutive invited talks at CASP7-CASP12. Accurate protein structure modeling in the TBM category is considered to be most relevant for successful new drug discovery.

Motivated by the superhuman performance of AlphaGo, with an ultimate eye towards improvements in protein folding prediction, Prof. Lee’s research interest temporarily turned to deep learning.


 He started with its application to the game of Go, and implemented a unique deep learning method to compete in world Go AI competitions (2nd place in the 2019 Fuzhou Go AI competition; 3rd place in the 11th Computer Go UEC Cup).


 Prof. Lee, a professor in the school of computational sciences at KIAS, has published more than 120 peer-reviewed papers in various SCI journals. Many of these papers are well cited [(over 4700 citations from SCI journals and over 3900 citations to his first/corresponding-authored papers (as of Sept. 2018)]. His publication H-Index is 34.