Seungwoo Hwang

Seoul National University — South Korea

Materials Science · Physical Sciences

10h-index786citations20works29.92yr avg
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Research Topics

Machine Learning in Materials Science(8), RNA and protein synthesis mechanisms(3), Protein Structure and Dynamics(2), EEG and Brain-Computer Interfaces(2), Chalcogenide Semiconductor Thin Films(2)

Publications20 total

Are diffusion models ready for materials discovery in unexplored chemical space?
arXiv (Cornell University)·2025Open Access
Unveiling Defect Motifs in Amorphous GeSe Using Machine Learning Interatomic Potentials
ACS Applied Materials & Interfaces·2025· 1 cited
Discovery of oxide Li-conducting electrolytes in uncharted chemical space via topology-constrained crystal structure prediction
arXiv (Cornell University)·2025Open Access
An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials
arXiv (Cornell University)·2025Open Access
Roadmap for the development of machine learning-based interatomic potentials
Modelling and Simulation in Materials Science and Engineering·2024· 35 citedOpen Access
Disorder-Dependent Li Diffusion in Li<sub>6</sub>PS<sub>5</sub>Cl Investigated by Machine-Learning Potential
ACS Applied Materials & Interfaces·2024· 24 cited
Scalable Parallel Algorithm for Graph Neural Network Interatomic Potentials in Molecular Dynamics Simulations
Journal of Chemical Theory and Computation·2024· 149 citedOpen Access
Stability and Equilibrium Structures of Unknown Ternary Metal Oxides Explored by Machine-Learned Potentials
Journal of the American Chemical Society·2023· 24 cited
Development of Reflow Fill of CGeSbTe Films for Sub‐20 nm Cells in 3D Cross‐Point Memory
Advanced Materials Technologies·2022· 1 cited
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials
npj Computational Materials·2022· 34 citedOpen Access
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials
Figshare·2021· 1 citedOpen Access
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials
Figshare·2021Open Access
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials
Figshare·2021Open Access
Microarray analysis of <i>Drosophila dicer‐2</i> mutants reveals potential regulation of mitochondrial metabolism by endogenous siRNAs
Journal of Cellular Biochemistry·2012· 11 cited
The endogenous siRNA pathway in<i>Drosophila</i>impacts stress resistance and lifespan by regulating metabolic homeostasis
FEBS Letters·2011· 54 citedOpen Access
Lim DH, Oh CT, Lee L, Hong JS, Noh SH, Hwang S, Kim S, Han SJ, Lee YS. The endogenous siRNA pathway in Drosophila impacts stress resistance and lifespan by regulating metabolic homeostasis. FEBS Letters
2011· 1 cited
DP-Bind: a web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins
Bioinformatics·2007· 262 citedOpen Access
Using evolutionary and structural information to predict DNA‐binding sites on DNA‐binding proteins
Proteins Structure Function and Bioinformatics·2006· 166 cited
A novel sensitive method for the detection of user-defined compositional bias in biological sequences
Bioinformatics·2006· 21 citedOpen Access
Molecular Cloning and Characterization of S-adenosylmethionine Synthetase Isolated fromSuspension Culture Cdna Library of Oil Palm (Elaeis guineensis Jacq.)
Pakistan Journal of Biological Sciences·2003· 2 cited

Frequent Co-authors

Seungwu Han(13), Sungwoo Kang(7), Chang‐Ho Hong(6), Wonseok Jeong(5), Yutack Park(4), Youngchae Yoon(4), Igor B. Kuznetsov(3), Jaesun Kim(3), Do‐Hwan Lim(3), Langho Lee(3), Jisu Jung(3), Youngho Kang(3), Zhenkun Gou(2), Sungchan Kim(2), Sung‐Jun Han(2), Young Sik Lee(2), Jiho Lee(2), Run Li(1), Chun-Taek Oh(1), Jae-Sang Hong(1)