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Tsz Wai Ko

Observed names: Ko, Tsz Wai, Tsz Wai Ko
ORCID: 0000-0002-0802-9559
Observed ORCID: 0000-0002-0802-9559
OpenAlex ID: A5063684599
A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer
2021 · Tsz Wai Ko, Jonas A. Finkler, et al. · Nature Communications · 511
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Neural Network Potentials: A Concise Overview of Methods
2022 · Emir Kocer, Tsz Wai Ko, et al. · Annual Review of Physical Chemistry · 310
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Recent advances and outstanding challenges for machine learning interatomic potentials
2023 · Tsz Wai Ko, Shyue Ping Ong · Nature Computational Science · 134
General-Purpose Machine Learning Potentials Capturing Nonlocal Charge Transfer
2021 · Tsz Wai Ko, Jonas A. Finkler, et al. · Accounts of Chemical Research · 130
Robust training of machine learning interatomic potentials with dimensionality reduction and stratified sampling
2024 · Ji Qi, Tsz Wai Ko, et al. · npj Computational Materials · 120
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Roadmap for the development of machine learning-based interatomic potentials
2024 · Yong-Wei Zhang, Viacheslav Sorkin, et al. · Modelling and Simulation in Materials Science and Engineering · 53
Accurate Fourth-Generation Machine Learning Potentials by Electrostatic Embedding
2023 · Tsz Wai Ko, Jonas A. Finkler, et al. · Journal of Chemical Theory and Computation · 50
Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry
2025 · Tsz Wai Ko, Bowen Deng, et al. · npj Computational Materials · 28
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Crash testing machine learning force fields for molecules, materials, and interfaces: molecular dynamics in the TEA challenge 2023
2025 · Igor Poltavsky, Mirela Puleva, et al. · Chemical Science · 28
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Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023
2025 · Igor Poltavsky, Anton Charkin-Gorbulin, et al. · Chemical Science · 25
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A Foundational Potential Energy Surface Dataset for Materials
2025 · Kaplan, Aaron D., Liu, Runze, et al. · arXiv (Cornell University) · 21
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Data-efficient construction of high-fidelity graph deep learning interatomic potentials
2025 · Tsz Wai Ko, Shyue Ping Ong · npj Computational Materials · 20
Iterative charge equilibration for fourth-generation high-dimensional neural network potentials
2025 · Emir Kocer, Andreas Singraber, et al. · The Journal of Chemical Physics · 11
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Superionic Surface Li-Ion Transport in Carbonaceous Materials
2025 · Jianbin Zhou, Shen Wang, et al. · Nano Letters · 9
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Exploring the Compositional Ternary Diagram of Ge/S/Cu Glasses for Resistance Switching Memories
2019 · Nicolas Onofrio, Tsz Wai Ko · The Journal of Physical Chemistry C · 6
El Agente Gráfico: A Semantic Execution Runtime for Scientific Agents
2026 · Bai, Jiaru, Aldossary, Abdulrahman, et al. · arXiv (Cornell University) · 4
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A Linear-Scaling, Charge-Aware Foundation Potential for Atomistic Simulations
2025 · Ko, Tsz Wai, Liu, Runze, et al. · arXiv (Cornell University) · 3
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El Agente Quntur: A research collaborator agent for quantum chemistry
2026 · Juan B. Pérez-Sánchez, Yunheng Zou, et al. · Chem · 2
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El Agente Sólido: A New Age(nt) for Solid State Simulations
2026 · Sai Govind Hari Kumar, Yunheng Zou, et al. · SSRN Electronic Journal · 2
Accurate Fourth-Generation Machine Learning Potentials by Electrostatic Embedding
2023 · Ko, Tsz Wai, Finkler, Jonas A., et al. · arXiv (Cornell University) · 2
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El Agente Potente: High-Throughput Agentic Atomistic Simulations
2026 · Ko, Tsz Wai, Bai, Jiaru, et al. · arXiv (Cornell University)
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Charge-Equilibrated TensorNet (QET) Source Code
2026 · Ko, Tsz Wai, Ong, Shyue Ping · Zenodo (CERN European Organization for Nuclear Research)
MatPES-R2SCAN-2025.2
2026 · Kaplan, Aaron D., Runze Liu, et al. · ColabFit Exchange
MatPES-PBE-2025.2
2026 · Kaplan, Aaron D., Runze Liu, et al. · ColabFit Exchange
Rightsizing AI Models and Datasets for Materials Design
2025 · Shyue Ping Ong, Aaron D. Kaplan, et al. · ECS Meeting Abstracts
Works count: 39
Citation count: 1,473
H-index: 12
I10-index: 13
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