Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science. - Ziyu Xiang; Mingzhou Fan; Guillermo Vázquez Tovar; William Trehern; Byung-Jun Yoon; Xiaofeng Qian; Raymundo Arróyave; Xiaoning Qian (AAAI, 2021)

Graph neural network for Hamiltonian-based material property prediction. - Hexin Bai; Peng Chu; Jeng-Yuan Tsai; Nathan Wilson; Xiaofeng Qian; Qimin Yan; Haibin Ling (Neural Comput. Appl., 2022)

Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. - Haiyang Yu 005; Zhao Xu 005; Xiaofeng Qian; Xiaoning Qian; Shuiwang Ji (ICML, 2023)

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. - Haiyang Yu 005; Meng Liu 015; Youzhi Luo; Alex Strasser; Xiaofeng Qian; Xiaoning Qian; Shuiwang Ji (NeurIPS, 2023)

Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery. - Xiaoning Qian; Byung-Jun Yoon; Raymundo Arróyave; Xiaofeng Qian; Edward R. Dougherty (Patterns, 2023)

Complete and Efficient Graph Transformers for Crystal Material Property Prediction. - Keqiang Yan; Cong Fu 003; Xiaofeng Qian; Xiaoning Qian; Shuiwang Ji (ICLR, 2024)

A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction. - Keqiang Yan; Alexandra Saxton; Xiaofeng Qian; Xiaoning Qian; Shuiwang Ji (ICML, 2024)

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation. - Keqiang Yan; Xiner Li; Hongyi Ling; Kenna Ashen; Carl Edwards; Raymundo Arróyave; Marinka Zitnik; Heng Ji 001; Xiaofeng Qian; Xiaoning Qian; Shuiwang Ji (NeurIPS, 2024)

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures. - Keqiang Yan; Montgomery Bohde; Andrii Kryvenko; Ziyu Xiang; Kaiji Zhao; Siya Zhu; Saagar Kolachina; Doguhan Saritürk; Jianwen Xie; Raymundo Arróyave; Xiaoning Qian; Xiaofeng Qian; et al. (CoRR, 2025)

Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists. - Lianhao Zhou; Hongyi Ling; Keqiang Yan; Kaiji Zhao; Xiaoning Qian; Raymundo Arróyave; Xiaofeng Qian; Shuiwang Ji (CoRR, 2025)

Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames. - Haiyang Yu 005; Yuchao Lin; Xuan Zhang; Xiaofeng Qian; Shuiwang Ji (CoRR, 2025)

Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials. - Cong Fu 003; Yuchao Lin; Zachary Krueger; Haiyang Yu 005; Maho Nakata; Jianwen Xie; Emine Küçükbenli; Xiaofeng Qian; Shuiwang Ji (CoRR, 2025)

Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations. - Yuchao Lin; Cong Fu 003; Zachary Krueger; Haiyang Yu 005; Maho Nakata; Jianwen Xie; Emine Küçükbenli; Xiaofeng Qian; Shuiwang Ji (CoRR, 2025)