Anders Johansson

Harvard University — United States

Engineering · Physical Sciences

20h-index2.3kcitations99works6.62yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

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

Research Topics

Railway Engineering and Dynamics(21), Structural Health Monitoring Techniques(18), Probabilistic and Robust Engineering Design(10), Hydraulic and Pneumatic Systems(10), Machine Learning in Materials Science(9)

Publications99 total

In Pursuit of the Optimal City: Evaluation of Procedurally Generated City Layouts
2025Open Access
Multiscale Light-Matter Dynamics in Quantum Materials: From Electrons to Topological Superlattices
2025· 1 citedOpen Access
Nonequilibrium quantum dynamics in SrTiO <sub>3</sub> under impulsive THz radiation with machine learning
Science Advances·2025· 1 citedOpen Access
Multiscale light-matter dynamics in quantum materials: from electrons to topological superlattices
arXiv (Cornell University)·2025Open Access
Experimental-Analytical Dynamic Substructuring of Ampair Testbed: A State-Space Approach
River Publishers eBooks·2025
Improving Test Rig Performance Using Passive Components
River Publishers eBooks·2025
Development of Simplified Models for Wind Turbine Blades with Application to NREL 5 MW Offshore Research Wind Turbine
River Publishers eBooks·2025
Unified differentiable learning of electric response
Nature Communications·2025· 17 citedOpen Access
High-performance training and inference for deep equivariant interatomic potentials
arXiv (Cornell University)·2025· 7 citedOpen Access
Atomistic evolution of active sites in multi-component heterogeneous catalysts
arXiv (Cornell University)·2024· 6 citedOpen Access
Transferability and Accuracy of Ionic Liquid Simulations with Equivariant Machine Learning Interatomic Potentials
The Journal of Physical Chemistry Letters·2024· 26 cited
Low-index mesoscopic surface reconstructions of Au surfaces using Bayesian force fields
Nature Communications·2024· 26 citedOpen Access
Unbiased Atomistic Predictions of Crystal Dislocation Dynamics using Bayesian Force Fields
arXiv (Cornell University)·2024· 1 citedOpen Access
Scaling the Leading Accuracy of Deep Equivariant Models to Biomolecular Simulations of Realistic Size
2023· 40 citedOpen Access
Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC
npj Computational Materials·2023· 64 citedOpen Access
Learning local equivariant representations for large-scale atomistic dynamics
Nature Communications·2023· 545 citedOpen Access
Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations
Journal of Physics Materials·2022· 40 citedOpen Access
Uncertainty-aware molecular dynamics from Bayesian active learning: Phase Transformations and Thermal Transport in SiC
Research Square (Research Square)·2022· 3 citedOpen Access
Phoebe: a collection of Phonon and Electron Boltzmann Equation solvers
arXiv (Cornell University)·2021· 2 citedOpen Access
LAMMPS output from creep simulation of silica sphere caps, symmetric system with tdamp=5
2019Open Access
page 1 of 5Next →

Frequent Co-authors

Boris Kozinsky(11), Thomas Abrahamsson(10), Jens C. O. Nielsen(9), Albert Musaelian(6), Cameron J. Owen(4), Magnus Ekh(4), Andrea Cepellotti(4), Simon Batzner(3), Lixin Sun(3), Björn A. Pålsson(3), Yu Xie(3), Mladen Gibanica(3), Mats Ander(2), Jim Brouzoulis(2), Jonathan Vandermause(2), Senja Ramakers(2), Nakib H. Protik(2), B. L. Josefson(2), Jennifer Coulter(2), Natalya S. Fedorova(2)