Jigyasa Nigam

@article{jpcm_editorial_2026,
  title = {Editorial for machine learning for understanding the physics of chemical processes},
  volume = {38},
  issn = {0953-8984},
  url = {https://doi.org/10.1088/1361-648X/ae3415},
  doi = {10.1088/1361-648X/ae3415},
  number = {2},
  urldate = {2026-01-20},
  journal = {Journal of Physics: Condensed Matter},
  author = {Nigam, Jigyasa and Veit, Max},
  year = {2026},
  note = {Publisher: IOP Publishing},
  pages = {020201},
  reps = {true}
}

@article{bioemu,
  title = {Scalable emulation of protein equilibrium ensembles with generative deep learning},
  url = {https://www-science-org.libproxy.mit.edu/doi/10.1126/science.adv9817},
  author = {Lewis, S and Hempel, T and Jimenez-Luna, J and Gastegger, M and Xie, Yu and Foong, A and Satorras, V and others},
  journal = {Science},
  year = {2025},
  publisher = {American Association for the Advancement of Science},
}

@article{suman2025exploring,
  title = {Exploring the design space of machine-learning models for quantum chemistry with a fully differentiable framework},
  url = {https://pubs.acs.org/doi/10.1021/acs.jctc.5c00522},
  author = {Suman, Divya and Nigam, Jigyasa and Saade, Sandra and Pegolo, Paolo and Tuerk, Hanna and Zhang, Xing and Chan, Garnet Kin and Ceriotti, Michele},
  journal = {Journal of Chemical Theory and Computation},
  volume = {21},
  number = {13},
  pages = {6505-6516},
  year = {2025},
  ham = {true}
}

@article{thesis2024jn,
  title = {Integrating symmetry and physical constraints into atomic-scale machine learning},
  url = {https://infoscience.epfl.ch/handle/20.500.14299/240680},
  doi = {10.5075/epfl-thesis-10848},
  author = {Nigam, Jigyasa},
  year = {2024},
  keywords = {atom-centered density correlations (ACDC) | atomistic machine learning | descriptors | N-center representations | equivariance , completeness , physical constraints | electronic Hamiltonians},
}

@article{lin2024expanding,
  title = {Expanding density-correlation machine learning representations for anisotropic coarse-grained particles},
  author = {Lin, Arthur and Huguenin-Dumittan, Kevin K and Cho, Yong-Cheol and Nigam, Jigyasa and Cersonsky, Rose K},
  journal = {The Journal of Chemical Physics},
  volume = {161},
  number = {7},
  year = {2024},
  publisher = {AIP Publishing},
  url = {https://pubs.aip.org/aip/jcp/article-abstract/161/7/074112/3308992/Expanding-density-correlation-machine-learning},
  reps = {true}
}

@article{cignoni2024electronic,
  title = {Electronic Excited States from Physically Constrained Machine Learning},
  author = {Cignoni, Edoardo and Suman, Divya and Nigam, Jigyasa and Cupellini, Lorenzo and Mennucci, Benedetta and Ceriotti, Michele},
  journal = {ACS Central Science},
  volume = {10},
  number = {3},
  pages = {637--648},
  year = {2024},
  publisher = {ACS Publications},
  url = {https://pubs.acs.org/doi/full/10.1021/acscentsci.3c01480},
  ham = {true}
}

@article{nigam2024completeness,
  title = {Completeness of atomic structure representations},
  author = {Nigam, Jigyasa and Pozdnyakov, Sergey N and Huguenin-Dumittan, Kevin K and Ceriotti, Michele},
  journal = {APL Machine Learning},
  volume = {2},
  number = {1},
  year = {2024},
  publisher = {AIP Publishing},
  url = {https://pubs.aip.org/aip/aml/article/2/1/016110/3262493/Completeness-of-atomic-structure-representations},
  reps = {true}
}

@article{nigam2022equivariant,
  title = {Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties},
  author = {Nigam, Jigyasa and Willatt, Michael J and Ceriotti, Michele},
  journal = {The Journal of Chemical Physics},
  volume = {156},
  number = {1},
  pages = {014115},
  year = {2022},
  publisher = {AIP Publishing LLC},
  url = {https://pubs.aip.org/aip/jcp/article-abstract/156/1/014115/2839817/Equivariant-representations-for-molecular},
  ham = {true}
}

@article{nigam2022unified,
  title = {Unified theory of atom-centered representations and message-passing machine-learning schemes},
  author = {Nigam, Jigyasa and Pozdnyakov, Sergey and Fraux, Guillaume and Ceriotti, Michele},
  journal = {The Journal of Chemical Physics},
  volume = {156},
  number = {20},
  pages = {204115},
  year = {2022},
  publisher = {AIP Publishing LLC},
  url = {https://pubs.aip.org/aip/jcp/article/156/20/204115/2841327/Unified-theory-of-atom-centered-representations},
  reps = {true}
}

@article{grisafi2021multi,
  title = {Multi-scale approach for the prediction of atomic scale properties},
  author = {Grisafi, Andrea and Nigam, Jigyasa and Ceriotti, Michele},
  journal = {Chemical Science},
  volume = {12},
  number = {6},
  pages = {2078--2090},
  year = {2021},
  publisher = {Royal Society of Chemistry},
  reps = {true},
  url = {https://pubs.rsc.org/en/content/articlelanding/2021/sc/d0sc04934d},
}

@article{nigam2020recursive,
  title = {Recursive evaluation and iterative contraction of N-body equivariant features},
  author = {Nigam, Jigyasa and Pozdnyakov, Sergey and Ceriotti, Michele},
  journal = {The Journal of Chemical Physics},
  volume = {153},
  number = {12},
  pages = {121101},
  year = {2020},
  publisher = {AIP Publishing LLC},
  reps = {true},
  url = {https://pubs.aip.org/aip/jcp/article/153/12/121101/1023428/Recursive-evaluation-and-iterative-contraction-of},
}