Dr. Schwalbe-Koda's research seeks to accelerate materials design by integrating high-performance computing, machine learning (ML), literature data, and atomistic simulations. In particular, his group develops models to bridge the gap between computational predictions and experiments using data-driven synthesis recipes. His interests also include designing new materials for energy applications, creating complex workflows in high-throughput materials simulations, and developing new ML approaches for atomistic simulation.

• Schwalbe-Koda. “mkite: A distributed computing platform for high-throughput materials simulations.”arXiv:2301.08841 (2023). https://doi.org/10.48550/arXiv.2301.08841
• Peng,D., Schwalbe-Koda, et al. “Human- and Machine-Centered Designs of Molecules and Materials for Sustainability and Decarbonization.” Nat. Rev. Mater. 7, 991 (2022). https://doi.org/10.1038/s41578-022-00466-5
• Bello-Jurado, D.Schwalbe-Koda, et al. “Controlling enrichment and DeNOx performance of CHA/AEI zeolite intergrowths with ‘a priori’ bi-selective OSDAs.” Angew. Chemie Int. Ed. 61 (28), e202201837 (2022). https://doi.org/10.1002/anie.202201837
• Schwalbe-Koda, et al. “A priori control of zeolite phase competition and intergrowth with high-throughput simulations.” Science 374 (6565), 308 (2021). https://doi.org/10.1126/science.abh3350
• Schwalbe-Koda, A. R. Tan et al. “Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks.”Nat. Commun. 12, 5104 (2021). https://doi.org/10.1038/s41467-021-25342-8
• Schwalbe-Koda, et al. “Generative Models for Automatic Chemical Design.” In: K.T. Schütt, S. Chmiela, A. von Lilienfeld, A. Tkatchenko, K. Tsuda, K.-R. Müller (eds.) Machine Learning for Quantum Simulations of Molecules and Materials. Springer, Cham, 445-467 (2020). https://doi.org/10.1007/978-3-030-40245-7_21
• Schwalbe-Koda, et al. “Graph similarity drives zeolite diffusionless transformations and intergrowth.” Nat. Mater. 18, 1177 (2019). https://doi.org/10.1038/s41563-019-0486-1

Forbes 30 Under 30: Science (2023)

• B.S., Electronic Engineering, Aeronautics Institute of Technology - Brazil, 2017
• M.S., Physics, Aeronautics Institute of Technology - Brazil, 2018
• Ph.D., Materials Science and Engineering, Massachusetts Institute of Technology, 2022

• Forbes 30 Under 30: Science (2023)
• LLNL Lawrence Postdoctoral Fellowship (2022)
• MRS Graduate Student Gold Award (2021)
• MIT Energy Fellowship (2020)
• MIT Robert M. Rose Presidential Fellowship (2018)
• Brazilian Ministry of Defense Honor Award (2018)
• Summa cum Laude, Aeronautics Institute of Technology, Brazil (2017)
• Best undergraduate research in Brazil on Exact, Earth Sciences and Mathematics, CNPq (2017)