Jigyasa Nigam

77 Massachusetts Avenue

Cambridge, MA 02139

I am a postdoc at MIT, funded by the School of Engineering’s Postdoc Fellowship for Excellence in Engineering!
In August 2024 I finished my PhD at the Lab of Computational Science and Modeling at EPFL, which I called home since the summer of 2020.
Before embarking on this adventure, I was working on getting my Masters at the Indian Institute of Space Science and Technology, where I started given my fascination with the stars and mysteries of the giant worlds beyond our world, but ended up falling in love with the dynamics of objects on the opposite end of the length scale. My current research interests include machine learning (ML) enabled simulations at the atomic scale, incorporating symmetries (equivariance) in these frameworks and unifying them with electronic structure.

news

Sep 01, 2024	So excited to begin my postdoc today!
Aug 09, 2024	The day I became Dr. Nigam

latest posts

Sep 29, 2024	Uprooting, challenging, ...
Sep 29, 2024	My world is burning

selected publications

Integrating symmetry and physical constraints into atomic-scale machine learning

Jigyasa Nigam

2024

Bib

@article{thesis2024jn,
  title = {Integrating symmetry and physical constraints into atomic-scale machine learning},
  url = {https://infoscience.epfl.ch/handl
  e/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},
}

Expanding density-correlation machine learning representations for anisotropic coarse-grained particles

Arthur Lin, Kevin K Huguenin-Dumittan, Yong-Cheol Cho, Jigyasa Nigam, and Rose K Cersonsky

The Journal of Chemical Physics, 2024

Bib

@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},
  reps = {true}
}

Electronic Excited States from Physically Constrained Machine Learning

Edoardo Cignoni, Divya Suman, Jigyasa Nigam, Lorenzo Cupellini, Benedetta Mennucci, and Michele Ceriotti

ACS Central Science, 2024

Bib

@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},
  ham = {true}
}

Completeness of atomic structure representations

Jigyasa Nigam, Sergey N Pozdnyakov, Kevin K Huguenin-Dumittan, and Michele Ceriotti

APL Machine Learning, 2024

Bib

@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},
  reps = {true}
}

Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties

Jigyasa Nigam, Michael J Willatt, and Michele Ceriotti

The Journal of Chemical Physics, 2022

Bib

@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},
  ham = {true}
}

Unified theory of atom-centered representations and message-passing machine-learning schemes

Jigyasa Nigam, Sergey Pozdnyakov, Guillaume Fraux, and Michele Ceriotti

The Journal of Chemical Physics, 2022

Bib

@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},
  reps = {true}
}

Multi-scale approach for the prediction of atomic scale properties

Andrea Grisafi, Jigyasa Nigam, and Michele Ceriotti

Chemical Science, 2021

Bib

@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},
}

Recursive evaluation and iterative contraction of N-body equivariant features

Jigyasa Nigam, Sergey Pozdnyakov, and Michele Ceriotti

The Journal of Chemical Physics, 2020

Bib

@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},
}