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Hi there 👋

I am Juno Nam, a first year PhD student in MIT DMSE & CCSE, advised by Prof. Rafael Gómez-Bombarelli. I work on dynamics-aware materials design, using molecular dynamics, free energy methods, and machine learning. I am trying to do enhanced sampling with myself on the landscape of computational materials research!

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Recent work highlights

  • Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials
    J. Nam and R. Gómez-Bombarelli, arXiv:2404.10746. [Preprint · Code]
  • Learning Collective Variables with Synthetic Data Augmentation through Physics-inspired Geodesic Interpolation
    S. Yang*, J. Nam*, J. C. B. Dietschreit, and R. Gómez-Bombarelli, arXiv:2402.01542. [Preprint · Code]
  • Enhanced Sampling for Free Energy Profiles with Post-Transition-State Bifurcations
    J. Nam and Y. Jung, J. Chem. Theory Comput. 19, 2735 (2023). [Paper · Preprint]

Juno Nam's Projects

cirpy icon cirpy

Python wrapper for the NCI Chemical Identifier Resolver (CIR)

eqnparse icon eqnparse

4190.306 Automata theory - homework 2 / LL(1) parser

labutil icon labutil

Lab materials for MIT 3.320 and Harvard AP 275

mlcolvar icon mlcolvar

A unified framework for machine learning collective variables for enhanced sampling simulations

openbabel icon openbabel

Open Babel is a chemical toolbox designed to speak the many languages of chemical data.

rdkit icon rdkit

The official sources for the RDKit library

rexp icon rexp

4190.306 Automata theory - homework 1

spectral-workbench icon spectral-workbench

Web-based tools for collecting, analyzing, and sharing data from a DIY spectrometer

wxmacmolplt icon wxmacmolplt

wxMacMolPlt is a graphical user interface principally for the GAMESS program

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