Prof Shyue Ping Ong is the Provost’s Chair Professor in Materials Science and Engineering at the National University of Singapore. He leads the Materialyze.AI lab, a materials informatics research group focused on the integration of materials science with data science and artificial intelligence to accelerate the discovery and design of materials. He is widely recognized as one of the pioneers of foundation potentials, i.e., machine learning interatomic potentials with near-complete coverage of the periodic table that has broad applications in materials discovery and design. Prof Ong is also the founder and lead developer of pymatgen, one of the most popular open-source libraries for materials analysis, and a core contributor to the Materials Project, a public platform that provides computed properties of tens of thousands of inorganic compounds. Ong earned his PhD in Materials Science and Engineering from the Massachusetts Institute of Technology in 2011, and an MEng and BA in Electrical and Information Science from the University of Cambridge in 1999. He has authored more than 150 peer-reviewed publications, and has been recognized as a Clarivate Highly Cited Researcher since 2021. He is also a recipient of the prestigious US Department of Energy Early Career Research Program and the Office of Naval Research Young Investigator Program awards.
Research interests
- AI for materials science
- Rechargeable lithium-ion and sodium-ion batteries
- High-entropy alloys and ceramics
- Advanced semiconductors
Selected publications
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Chen, C.; Ong, S. P. A Universal Graph Deep Learning Interatomic Potential for the Periodic Table. Nat Comput Sci 2022, 2 (11), 718–728. https://doi.org/10.1038/s43588-022-00349-3.
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Chen, C.; Ye, W.; Zuo, Y.; Zheng, C.; Ong, S. P. Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals. Chem. Mater. 2019, 31 (9), 3564–3572. https://doi.org/10.1021/acs.chemmater.9b01294.
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Horton, M. K.; Huck, P.; Yang, R. X.; Munro, J. M.; Dwaraknath, S.; Ganose, A. M.; Kingsbury, R. S.; Wen, M.; Shen, J. X.; Mathis, T. S.; Kaplan, A. D.; Berket, K.; Riebesell, J.; George, J.; Rosen, A. S.; Spotte-Smith, E. W. C.; McDermott, M. J.; Cohen, O. A.; Dunn, A.; Kuner, M. C.; Rignanese, G.-M.; Petretto, G.; Waroquiers, D.; Griffin, S. M.; Neaton, J. B.; Chrzan, D. C.; Asta, M.; Hautier, G.; Cholia, S.; Ceder, G.; Ong, S. P.; Jain, A.; Persson, K. A. Accelerated Data-Driven Materials Science with the Materials Project. Nat. Mater. 2025. https://doi.org/10.1038/s41563-025-02272-0.
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Liu, H.; Zhu, Z.; Yan, Q.; Yu, S.; He, X.; Chen, Y.; Zhang, R.; Ma, L.; Liu, T.; Li, M.; Lin, R.; Chen, Y.; Li, Y.; Xing, X.; Choi, Y.; Gao, L.; Cho, H. S.; An, K.; Feng, J.; Kostecki, R.; Amine, K.; Wu, T.; Lu, J.; Xin, H. L.; Ong, S. P.; Liu, P. A Disordered Rock Salt Anode for Fast-Charging Lithium-Ion Batteries. Nature 2020, 585, 63–67. https://doi.org/10.1038/s41586-020-2637-6.
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Li, X.-G.; Chen, C.; Zheng, H.; Zuo, Y.; Ong, S. P. Complex Strengthening Mechanisms in the NbMoTaW Multi-Principal Element Alloy. npj Comput Mater 2020, 6 (1), 70. https://doi.org/10.1038/s41524-020-0339-0.
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Wang, Z.; Ha, J.; Kim, Y. H.; Im, W. B.; McKittrick, J.; Ong, S. P. Mining Unexplored Chemistries for Phosphors for High-Color-Quality White-Light-Emitting Diodes. Joule 2018, 2 (5), 914–926. https://doi.org/10.1016/j.joule.2018.01.015.
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Ong, S. P.; Richards, W. D.; Jain, A.; Hautier, G.; Kocher, M.; Cholia, S.; Gunter, D.; Chevrier, V. L.; Persson, K. A.; Ceder, G. Python Materials Genomics (Pymatgen): A Robust, Open-Source Python Library for Materials Analysis. Computational Materials Science 2013, 68, 314–319. https://doi.org/10.1016/j.commatsci.2012.10.028.
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Qi, J.; Ko, T. W.; Wood, B. C.; Pham, T. A.; Ong, S. P. Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling. npj Computational Materials 2024, 10 (43), 1–11. https://doi.org/10.1038/s41524-024-01227-4.
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Zheng, H.; Fey, L. T. W.; Li, X.-G.; Hu, Y.-J.; Qi, L.; Beyerlein, I. J.; Ong, S. P. Multi-Scale Investigation of Short-Range Order and Dislocation Glide in MoNbTi and TaNbTi Multi-Principal Element Alloys. npj Computational Materials 2023, 9, 89. https://doi.org/10.1038/s41524-023-01046-z.
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Oh, J. A. S.; Yu, Z.; Huang, C.-J.; Ridley, P.; Liu, A.; Zhang, T.; Hwang, B. J.; Griffith, K. J.; Ong, S. P.; Meng, Y. S. Metastable Sodium Closo-Hydridoborates for All-Solid-State Batteries with Thick Cathodes. Joule 2025, 102130. https://doi.org/10.1016/j.joule.2025.102130.