Research output per year
Research output per year
Personal profile
Education
2002 – 2009 Ph.D. in Chemistry, University of Pennsylvania, USA (Prof. Jeffery G. Saven)
1996 – 1998 M.S. in Chemistry, Yonsei University, Korea (Prof. Yong-Rok Kim)
1992 – 1996 B.S. in Chemistry, Yonsei University, Korea
Professional Experience
2024.3 – Present Associate Professor, SKKU Advanced Institute of Nano Technology (SAINT) & Department of Nano Engineering, Sungkyunkwan University (SKKU), Korea
2014.4 – 2024.2 Research Staff Member, Computational Biology Center, IBM T.J. Watson Research Center, USA
2011.3 – 2014.4 Postdoctoral Research Fellow, Computational Biology Center, IBM T.J. Watson Research Center, USA (Prof. Ruhong Zhou)
2010.2 – 2011.3 Postdoctoral Research Fellow, Department of Chemistry, University of Pennsylvania, USA (Prof. Jeffery G. Saven)
1998.10 – 2002.1 Full-time Instructor, Department of Chemistry, Republic of Korea Air Force Academy, Korea
1997.10 – 1998.10 Research Assistant, Quantum Optics Group, Korea Research Institute of Standards and Science (KRISS), Korea
Awards
Outstanding Accomplishments, “Pioneering Foundation Models and Generative AI for Accelerated Discovery”, IBM, 2023.
Outstanding Technical Achievement Award (the highest technical achievement award of the Global IBM), “Molecular Modeling for Alzheimer’s Disease”, IBM, 2019.
Outstanding Technical Achievement Award, “Novel Nanostructures from small-peptide self-assembly”, IBM, 2018.
Outstanding Technical Achievement Award, “Linear Response Method for Drug Discovery”, IBM, 2018.
Outstanding Technical Achievement Award, “Advances in Protein Science Powered by Blue Gene”, IBM, 2016.
Outstanding Technical Achievement Award, “De novo Design of Nanomedicine: Implications from Nanotoxicity”, IBM, 2014.
Fingerprint
Dive into the research topics where Seunggu Kang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
Intersection-Free Fractal-Like Structuring of Recombinant Adhesive Proteins for Surface Functionalization
Kim, S., Sa, D. H., Jung, W., Khaleel, Z. H., Lee, J. K., Choi, D., Kim, N. H., Kang, S. G., An, S., Kim, J. H. & Kim, Y. H., 20 Aug 2025, In: Nano Letters. 25, 33, p. 12738-12746 9 p.Research output: Contribution to journal › Article › peer-review
-
The lipid bilayer strengthens the cooperative network of membrane proteins
MuhammedNazaar, S., Yao, J., Necelis, M. R., Park, Y. C., Shen, Z., Bridges, M. D., Guo, R., Swope, N., Rhee, M. S., Kim, M., Kim, K. H., Hubbell, W. L., Fleming, K. G., Columbus, L., Kang, S. G. & Hong, H., 4 Jul 2025, In: Science Advances. 11, 27, eadv9568.Research output: Contribution to journal › Article › peer-review
Open Access -
SPARK: Harnessing Human-Centered Workflows with Biomedical Foundation Models for Drug Discovery
Kwon, B. C., Rabinovici-Cohen, S., Moturi, B., Mwaura, R., Wahome, K., Njeru, O., Shinyenyi, M., Wanjiru, C., Remy, S., Ogallo, W., Guez, I., Suryanarayanan, P., Morrone, J., Sethi, S., Kang, S. G., Huynh, T., Ng, K., Mahajan, D., Li, H. & Ninio, M. & 3 others, , 2024, Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024. Larson, K. (ed.). International Joint Conferences on Artificial Intelligence, p. 8713-8716 4 p. (IJCAI International Joint Conference on Artificial Intelligence).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
-
Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity
Weber, J. K., Morrone, J. A., Kang, S. G., Zhang, L., Lang, L., Chowell, D., Krishna, C., Huynh, T., Parthasarathy, P., Luan, B., Alban, T. J., Cornell, W. D. & Chan, T. A., 1 Jan 2024, In: Briefings in Bioinformatics. 25, 1, bbad504.Research output: Contribution to journal › Article › peer-review
Open Access5 Scopus citations -
Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation
Kang, S. G., Morrone, J. A., Weber, J. K. & Cornell, W. D., 28 Feb 2022, In: Journal of Chemical Information and Modeling. 62, 4, p. 801-816 16 p.Research output: Contribution to journal › Article › peer-review
Open Access9 Scopus citations