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🧪[19] Foster, A.^*; Schatzle, Z.^*; Szabo, P. B.^*; Cheng, L.^*; Kohler, J.; Cassella, G.; Gao, N.; Li, J. ; Noe, F.; Hermann, J. A Wavefunction Foundation Model that Accurately Describes Bond Breaking. arXiv:2506.19960. (2025). Link

🧪[18] Sun, J.; Cheng, L.; Zhang, S.-X. Stabilizer Ground State: Theory, Algorithms and Applications, Quantum, 2025.Link

🔮[17] Jacobson, G.^*; Cheng, L.^*; Sun, J; Bhethanabotla, V; McCoy, A. B., Machine Learning Approaches for Developing Potential Surfaces: Applications to OH-(H2O)n (n=1-3) Complexes. J. Phys. Chem. A, 2025. Link

🧪[16] Cheng, L.^*; Szabó, P.B.^*; Schätzle, Z.^*; Kooi, D.; Köhler, J.; Noé, F.; Gori-Giorgi, P.; Foster, A. Highly Accurate Real-space Electron Densities with Neural Networks, J. Chem. Phys., 2025.Link

🧪[15] Cheng, L.^*; Chen, Y.-Q.^*; Zhang, S.-X.; Zhang, S. Error-Mitigated Quantum Approximate Optimization via Learning-Based Adaptive Optimization. (*co-first author) Commun. Phys., 2024.Link, "Top 25 downloaded papers of 2024" on Communications Physics

🧪[14] Sun, J.; Cheng, L.; Li, W. Towards Chemical Accuracy with Shallow Quantum Circuits: A Clifford-Based Hamiltonian Engineering Approach. J. Chem. Theory Comput., 2024.Link

🤖[13] MR AI4Science^, MA Quantum. The Impact of Large Language Models on Scientific Discovery: A Preliminary Study Using GPT-4. arXiv:2311.07361 (2023).Link (^Main contributor to Chapter 4, see Authorship and contribution list)

🧪[12] Li, W; Allcock, J.; Cheng, L.; Zhang, S.-X.; Chen, Y.-Q.; Mailoa, J.P.; Zhang, S. TenCirChem: An Efficient Quantum Computational Chemistry Package for the NISQ Era. J. Chem. Theory Comput., 2023.Link

⚙️[11] Cheng, L.; Sun, J.; Deustua, J. E.; Bhethanabotla, V. C.; Miller III, T. F. Molecular-Orbital-Based Machine Learning for Open-Shell and Multi-Reference Systems with Kernel Addition Gaussian Process Regression. J. Chem. Phys., 2022. Link

⚙️[10] Sun, J.; Cheng, L.; Miller III, T. F. Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-Orbital-Based Machine Learning. J. Chem. Phys., 2022. Link

📝[9] Cheng, L.^*; Yang, Z.^*; Liao, B.; Hsieh, C.; Zhang, S. ODBO: Bayesian Optimization with Prescreening for Directed Protein Evolution. arXiv:2205.09548 (2022). (*co-first author) Link

⚙️[8] Cheng, L., Sun, J. & Miller III, T. F. Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space. J. Chem. Theory Comput., 2022. Link

🔮[7] Lu, F.^*; Cheng, L.^*; DiRisio, R. J.^*; Finney, J. M.; Boyer, M. A.; Moonkaen, P.; Sun, J.; Lee, S. J. R.; Deustua, J. E.; Miller III, T. F.; McCoy, A. B. Fast Near Ab Initio Potential Energy Surfaces Using Machine Learning. J. Phys. Chem. A, 2022. (*co-first author) Link

⚙️[6] Sun, J.; Cheng, L.; Miller III, T. F. Molecular Energy Learning Using Alternative Blackbox Matrix-Matrix Multiplication (AltBBMM) Algorithm for Exact Gaussian Process. arXiv:2109.09817 (2021). (Accepted for presentation at the NeurIPS 2021 AI for Science Workshop) Link

⚙️[5] Husch, T.; Sun, J.; Cheng, L.; Lee, S. J. R.; Miller III, T. F. Improved Accuracy and Transferability of Molecular-Orbital-Based Machine Learning: Organics, Transition-Metal Complexes, Non-Covalent Interactions, and Transition States. J. Chem. Phys., 2021. Link

⚙️[4] Cheng, L.; Kovachki, N; Welborn, M.; Miller III, T. F. Regression Clustering for Improved Accuracy and Training Costs with Molecular-Orbital-Based Machine Learning. J. Chem. Theory Comput., 2019. Link

⚙️[3] Cheng, L.; Welborn, M.; Miller III, T. F. A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules. J. Chem. Phys., 2019. Link

⚙️[2] Welborn, M.; Cheng, L.; Miller III, T. F. Transferability in Machine Learning for Electronic Structure via the Molecular Orbital Basis. J. Chem. Theory Comput., 2018. Link (Highlighted with commentary in C&EN and Caltech News; #5 of 6595 JCTC papers in Altmetric attention score)

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Patent:

• Miller III, T. F.; Welborn, M.; Cheng, L.; Husch, T.; Song, J.; Kovachiki, N.; Burov, D.; Teh, Y.S.; Anandkumar, A.; Ding, F.; Lee, S.J.R.; Qiao, Z.; Lale, A.S. Systems and methods for determining molecular structures with molecular-orbital-based features. U.S. Patent 16817489, 2020 Link

• 程立雪; 杨子翊; 廖奔犇; 张胜誉 ; 对象确定方法、装置、计算机设备和存储介质, 2022-05-09, 中 国, 2022104986847

• 程立雪; 赖炫尧; 张胜誉 ; 分子能量的预测方法、装置、设备及存储介质, 2022-10-18, 中国, 2022112749576