Publications

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2026

Inverse design of bespoke interatomic potentials via active learning by information-matching

Yonatan Kurniawan, Logan D. Williams, Amit Samanta, Ilia Nikiforov, Daniel Schwalbe-Koda, Mark K. Transtrum, Ellad B. Tadmor, Vincenzo Lordi, Vasily V. Bulatov

Journal of Materials Science: Materials Theory · DOI

Accelerating Electrochemical Impedance Spectroscopy Measurements by Reducing Reliance on Noisy Low-Frequency Data

Qiuyu Shi, Naohiro Fujinuma, Yonatan Kurniawan, Runze Zhang, Ali Jaberi, Ashley Dale, Jason Hattrick-Simpers

Preprint · arXiv

Building informative materials datasets beyond targeted objectives

Rafael Espinosa Castañeda, Ashley Dale, Hongchen Wang, Yonatan Kurniawan, Hao Wan, Runze Zhang, Adji Bousso Dieng, Kangming Li, Jason Hattrick-Simpers

Preprint · arXiv

AutoREC: A software platform for developing reinforcement learning agents for equivalent circuit model generation from electrochemical impedance spectroscopy data

Ali Jaberi, Yonatan Kurniawan, Robert Black, Shayan Mousavi M., Kabir Verma, Zoya Sadighi, Santiago Miret, Jason Hattrick-Simpers

Preprint · arXiv

An information-matching approach to optimal experimental design and active learning

Yonatan Kurniawan, Tracianne B. Neilsen, Benjamin L. Francis, Alex M. Stankovic, Mingjian Wen, Ilia Nikiforov, Ellad B. Tadmor, Vasily V. Bulatov, Vincenzo Lordi, Mark K. Transtrum

Applied Physics Letters · DOI

Comparative study of ensemble-based uncertainty quantification methods for neural network interatomic potentials

Yonatan Kurniawan, Mingjian Wen, Ellad Tadmor, Mark K Transtrum

Machine Learning: Science and Technology · DOI

2025

Embracing Uncertainty in ΓÇ£Small DataΓÇ¥ Problems: Estimating Earthquakes From Historical Anecdotes

N. E. Glatt-Holtz, R. A. Harris, A. J. Holbrook, J. Krometis, Y. Kurniawan, H. Ringer, J. P. Whitehead

Journal of Geophysical Research: Machine Learning and Computation · DOI

2022

Extending OpenKIM with an Uncertainty Quantification Toolkit for Molecular Modeling

Yonatan Kurniawan, Cody L. Petrie, Mark K. Transtrum, Ellad B. Tadmor, Ryan S. Elliott, Daniel S. Karls, Mingjian Wen

2022 IEEE 18th International Conference on e-Science (e-Science) · DOI

Bayesian, frequentist, and information geometric approaches to parametric uncertainty quantification of classical empirical interatomic potentials

Yonatan Kurniawan, Cody L. Petrie, Kinamo J. Williams, Jr., Mark K. Transtrum, Ellad B. Tadmor, Ryan S. Elliott, Daniel S. Karls, Mingjian Wen

The Journal of Chemical Physics · DOI