Youzhi Luo

Materials Science · Physical Sciences

8h-index400citations31works1.12yr avg
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Research Topics

Machine Learning in Materials Science(17), Computational Drug Discovery Methods(12), Advanced Graph Neural Networks(6), Topic Modeling(5), Protein Structure and Dynamics(4)

Publications31 total

PRISM: A Unified Framework for Post-Training LLMs Without Verifiable Rewards
ArXiv.org·2026Open Access
PRISM: A Unified Framework for Post-Training LLMs Without Verifiable Rewards
arXiv (Cornell University)·2026Open Access
Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation
Proceedings of the AAAI Conference on Artificial Intelligence·2025Open Access
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Foundations and Trends® in Machine Learning·2025· 6 cited
Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation
arXiv (Cornell University)·2024Open Access
Geometry Informed Tokenization of Molecules for Language Model Generation
arXiv (Cornell University)·2024· 1 citedOpen Access
3D Molecular Geometry Analysis with 2D Graphs
Society for Industrial and Applied Mathematics eBooks·2024· 1 cited
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
arXiv (Cornell University)·2023· 53 citedOpen Access
Towards Symmetry-Aware Generation of Periodic Materials
arXiv (Cornell University)·2023· 8 citedOpen Access
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
arXiv (Cornell University)·2023· 3 citedOpen Access
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization
arXiv (Cornell University)·2023· 3 citedOpen Access
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
arXiv (Cornell University)·2023· 10 citedOpen Access
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization
arXiv (Cornell University)·2023· 8 citedOpen Access
3D Molecular Geometry Analysis with 2D Graphs
arXiv (Cornell University)·2023Open Access
Frontiers of Graph Neural Networks with DIG
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining·2022
Generating 3D Molecules for Target Protein Binding
arXiv (Cornell University)·2022· 43 citedOpen Access
Automated Data Augmentations for Graph Classification
arXiv (Cornell University)·2022· 7 citedOpen Access
Advanced graph and sequence neural networks for molecular property prediction and drug discovery
Bioinformatics·2022· 105 cited
Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs
arXiv (Cornell University)·2021· 6 citedOpen Access
Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks
arXiv (Cornell University)·2021· 3 citedOpen Access
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Frequent Co-authors

Shuiwang Ji(23), Xu Zhao(11), Yaochen Xie(11), Meng Liu(7), Limei Wang(7), Shurui Gui(6), Haiyang Yu(5), Keqiang Yan(4), Cong Fu(4), Xuan Zhang(4), Yuchao Lin(4), Xiner Li(4), Xiaoning Qian(4), Tianbao Yang(4), Qi Qi(3), Xuan Zhang(3), Alex Strasser(3), Shenglong Xu(3), Carl N. Edwards(3), Heng Ji(3)