Publications
Publications:
[24] Wang, C., Huang, L., Wei, X., Qin, T., Jiang, A., Cheng, L., Zhang, J. Scalable Machine Learning Force Fields for Macromolecular Systems Through Long-Range Aware Message Passing. arXiv:2601.03774. (2026). Link
[23] Song, Z., Lu, J., Du, Y., Yu, B., Pruyn, T.M., Huang, Y., Guo, K., Luo, X., Qu, Y., Qu, Y., Wang, Y., Wang, H., Guo, J., Gan, J., Shojaee, P., Luo, D., Bran, A.M., Li, G., Zhao, Q., Luo, S.-X. L., Zhang, Y., Zou, X., Zhao, W., Zhang, Y.F., Zhang, W., Zheng, S., Zhang, S., Khan, S.T., Rajabi-Kochi, M., Paradi-Maropakis, S., Baltoiu, T., Xie, F., Chen, T., Huang, K., Luo, W., Fang, M., Yang, X., Cheng, L., He, J., Hassoun, S., Zhang, X., Wang, W., Reddy, C.K., Zhang, C., Zheng, Z., Wang, M., Cong, L., Gomes, C.P., Hsieh, C.-Y., Nandy, A., Schwaller, P., Kulik, H.J., Jia, H., Sun, H., Moosavi, S.M., Duan, C. Evaluating Large Language Models in Scientific Discovery. arXiv:2512.15567. (2025). Link
[22] Chen, Y., Cheng, L., Jing, Y. and Zhong, P. Benchmarking a Foundation Potential against Quantum Chemistry Methods for Predicting Molecular Redox Potentials. arXiv:2510.24063. (2025). Link
[21] Jacobson, G.M., Webb, A.W., Cheng, L., and McCoy, A.B. Diffusion Monte Carlo Study of the Structure and Spectroscopy of H3O-, J. Phys. Chem. A., 2025 Link
[20] Simm, G.N.C., Helie, J., Schulz, H., Chen,Y., Simeon, G., Kuzina, A., Martinez-Baez, E., Gasparotto, P., Tocci, G., Chen, C., Li, Y., Cheng, L., Wang, Z., Nguyen, B.H., Smith, J.A. and Sun, L. Simpoly: Simulation of Polymers with Machine Learning Force Fields Derived from First Principles. arXiv:2510.13696. (2025). Link
[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). (*co-first author) 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. (*co-first author)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., 2024.(*co-first author)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
[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)
[1] Knowles, D. B.; Shkel, I. A.; Phan, N. M.; Sternke, M.; Lingeman, E.; Cheng, X.; Cheng, L.; O’Connor, K.; Record, M. T. Chemical interactions of polyethylene glycols (PEGs) and glycerol with protein functional groups: Applications to effects of PEG and glycerol on protein processes. Biochemistry, 2015, 54 (22), 3528–3542. Link
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