@article{goswamiEnhancedClimbingImage2026,
mypdf = {https://arxiv.org/abs/2601.12630},
title = {Enhanced Climbing Image Nudged Elastic Band Method with Hessian Eigenmode Alignment},
author = {Goswami, Rohit and Gunde, Miha and J{\'o}nsson, Hannes},
year = {2026},
month = {may},
journal = {Frontiers in Chemistry},
publisher = {Frontiers Media SA},
volume = {14},
doi = {10.3389/fchem.2026.1807063},
langid = {english},
archivePrefix = {arXiv},
eprint = {2601.12630},
eprinttype = {arxiv},
keywords = {journal, selected},
}
Rohit Goswami
Postdoctoral Researcher · EPFL labCOSMO
Better computational representations unlock better science. I develop surrogate models, cross-language interfaces, and ML infrastructure that make chemical kinetics simulations practical at scale.
My work connects transition state theory, machine learning interoperability, and scientific software engineering through a common principle: the right computational representation unlocks science that was previously out of reach. From relativistic atomic structure to lava flow prediction, I develop the abstractions, implement them in open-source software, and validate them on real chemical systems.
Research Threads
transition-state
Transition State Methods
NEB, dimer methods, and path visualization for reaction pathways
bayesian-stats
Bayesian Statistical Methods
Hierarchical models and uncertainty quantification for algorithm benchmarking
gp-acceleration
GP-Accelerated Saddle Point Searches
Surrogate energy surfaces via Gaussian process regression for 10x fewer force evaluations
sci-sw-interop
Scientific Software Interoperability
Cross-language bindings, build systems, and packaging for computational science codes
ml-atomistic
Machine Learning Interoperability for Molecular Science
Foundational libraries enabling ML models and simulation engines to communicate
molecular-sim
Molecular Simulation and Structural Analysis
Ice nucleation, self-propelled particles, lava flows, and tools for trajectory analysis
reproducible-hpc
Reproducible Scientific Computing
Nix, pixi, spack, and workflow tools for HPC environments
ultrafast
Ultrafast Spectroscopy and Pulse Shaping
Femtosecond lasers for spectroscopy, quantum gates, and machine-learned pulse optimization
Recent Work
@article{goswamiTwodimensionalRMSDProjections2026,
mypdf = {https://arxiv.org/abs/2512.07329},
title = {Two-Dimensional {{RMSD}} Projections for Reaction Path Visualization and Validation},
author = {Goswami, Rohit},
year = {2026},
month = {mar},
journal = {MethodsX},
pages = {103851},
issn = {2215-0161},
doi = {10.1016/j.mex.2026.103851},
eprint = {2512.07329},
eprinttype = {arxiv},
archiveprefix = {arXiv},
urldate = {2026-03-06},
langid = {english},
keywords = {journal, selected},
}@article{bigiMetatensorMetatomicFoundational2025,
mypdf = {https://arxiv.org/abs/2508.15704},
title = {Metatensor and Metatomic: Foundational Libraries for Interoperable Atomistic Machine Learning},
shorttitle = {Metatensor and Metatomic},
author = {Bigi, Filippo and Abbott, Joseph W. and Loche, Philip and Mazitov, Arslan and Tisi, Davide and Langer, Marcel F. and Goscinski, Alexander and Pegolo, Paolo and Chong, Sanggyu and Goswami, Rohit and Febrer, Pol and Chorna, Sofiia and Kellner, Matthias and Ceriotti, Michele and Fraux, Guillaume},
year = {2026},
month = {feb},
journal = {The Journal of Chemical Physics},
volume = {164},
number = {6},
doi = {10.1063/5.0304911},
issn = {1089-7690},
eprint = {2508.15704},
eprinttype = {arxiv},
archiveprefix = {arXiv},
urldate = {2026-02-01},
langid = {english},
keywords = {journal, selected},
}@article{goswamiReproducibleOrchestrationBest2026,
mypdf = {https://doi.org/10.1016/j.mex.2026.103899},
title = {Reproducible Orchestration of Best Practices for Reaction Path Optimization with the Nudged Elastic Band},
author = {Goswami, Rohit},
year = {2026},
journal = {MethodsX},
pages = {103899},
issn = {2215-0161},
doi = {10.1016/j.mex.2026.103899},
keywords = {journal},
}