Bingqing Cheng

Berkeley College — United States

Materials Science · Physical Sciences

26h-index3.3kcitations93works7.72yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Machine Learning in Materials Science(26), Phase Equilibria and Thermodynamics(13), Computational Drug Discovery Methods(11), nanoparticles nucleation surface interactions(11), Microstructure and mechanical properties(10)

Publications93 total

Long-range electrostatics for machine learning interatomic potentials is easier than we thought
The Journal of Chemical Physics·2026Open Access
Event-based Motion Deblurring via Multi-Temporal Granularity Fusion
IEEE Transactions on Circuits and Systems for Video Technology·2026
A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials
Journal of Chemical Theory and Computation·2025· 3 citedOpen Access
Cartesian equivariant representations for learning and understanding molecular orbitals
Proceedings of the National Academy of Sciences·2025Open Access
Scalable Multitemperature Free Energy Sampling of Classical Ising Spin States
Journal of Chemical Theory and Computation·2025
Lattice distortion leads to glassy thermal transport in crystalline Cs <sub>3</sub> Bi <sub>2</sub> I <sub>6</sub> Cl <sub>3</sub>
Proceedings of the National Academy of Sciences·2025· 2 citedOpen Access
Machine learning of charges and long-range interactions from energies and forces
Nature Communications·2025· 13 citedOpen Access
Ion-modulated structure, proton transfer, and capacitance in the Pt(111)/water electric double layer
arXiv (Cornell University)·2025Open Access
A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials
ArXiv.org·2025· 1 citedOpen Access
Cartesian Equivariant Representations for Learning and Understanding Molecular Orbitals
2025Open Access
Thermal Transport of Amorphous Hafnia Across the Glass Transition
ACS Materials Letters·2025· 1 citedOpen Access
Cartesian Equivariant Representations for Learning and Understanding Molecular Orbitals
2025· 1 citedOpen Access
Machine learning interatomic potential can infer electrical response
arXiv (Cornell University)·2025· 1 citedOpen Access
Latent Ewald summation for machine learning of long-range interactions
npj Computational Materials·2025· 42 citedOpen Access
Scalable Multitemperature Free Energy Sampling of Classical Ising Spin States
ArXiv.org·2025Open Access
Thermal transport of amorphous hafnia across the glass transition
arXiv (Cornell University)·2025· 1 citedOpen Access
Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance
Nature Communications·2025· 9 citedOpen Access
Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance
arXiv (Cornell University)·2024· 1 citedOpen Access
The seventh blind test of crystal structure prediction: structure generation methods
Acta Crystallographica Section B Structural Science Crystal Engineering and Materials·2024· 65 citedOpen Access
Response Matching for Generating Materials and Molecules
Journal of Chemical Theory and Computation·2024· 2 citedOpen Access
page 1 of 5Next →

Frequent Co-authors

Michele Ceriotti(10), A.H.W. Ngan(7), Tiesheng Dou(7), Chris J. Pickard(6), Aleks Reinhardt(4), Shifa Xia(4), Jinxin Yang(4), Gareth A. Tribello(3), Edgar A. Engel(3), Jan Gerit Brandenburg(3), Mandy Bethkenhagen(3), Sébastien Hamel(3), Felix Wodaczek(3), H.S. Leung(3), Lijun Zhao(3), Xiaonong Dong(3), Alexandre Tkatchenko(2), Jörg Behler(2), Guglielmo Mazzola(2), Christian Künkel(2)