Research Interests

• Machine learning and interpretable data-driven parameterizations
• Satellite remote sensing of clouds
• Cloud microphysics
• High fidelity atmospheric simulations

Ph.D. Mechanical Engineering, California Institute of Technology, 2024

M.S. Mechanical Engineering, California Institute of Technology, 2021

B.S.E. Chemical and Biological Engineering, Princeton University, 2019

Google Scholar | ORCID

Selected Publications

de Jong, E., Gunawardena, N., Katona, J., Beydoun, H., Ghosh, D., Caldwell, P. (2026) Data-driven reduced ordering modeling for warm rain microphysics, Journal of Geophysical Research: Machine Learning & Computation 3 (3), e2025JH001103, https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2025JH001103 

de Jong, E., Smalley, K., Gunawardena, N., Beydoun, H., Caldwell, P. (2026) CERBERUS: A Three-Headed Decoder for Vertical Cloud Profiles, 2026 ICLR Workshop on ML for Remote Sensing, https://arxiv.org/abs/2604.08772 

Beydoun, H., Ghosh, D., de Jong, E. K., McGuffin, D., Kendrick, C., Lee, J., Gardner, D. J., and Lundquist, K. A. (2026, preprint) Super Droplet Cloud Microphysics in the Energy Research and Forecasting Model, ESS Open Archive, doi: 10.22541/essoar.176858434.43447149/v1

de Jong, E., Quon, E., and Zalkind, D. (2026) Idealized Offshore Low-Level Jets for Turbine Structural Impact Considerations, Wind Energy 29 (1), doi: 10.1002/we.70097.

Katona, J., de Jong, E., and Gunawardena, N. (2025) Uncertainty Quantification for Reduced-Order Surrogate Models Applied to Cloud Microphysics, NeurIPS Workshop on Machine Learning and the Physical Sciences, https://arxiv.org/abs/2511.04534

de Jong, E., Quon, E., and Yellapantula, S. (2024) Mechanisms of Low-Level Jet Formation in the US Mid-Atlantic Offshore, Journal of Atmospheric Sciences 81 (1), 31-52, doi: 10.1175/JAS-D-23-0079.1

Azimi, S., Jaruga, A., de Jong, E., Arabas, S. and Schneider, T. (2023) Training warm-rain bulk microphysics schemes using super-droplet simulations, Journal of Advances in Modeling Earth Systems 16 (7), doi: 10.1029/2023MS004028.

de Jong, E., Mackay, J. B., Bulenok, O., Jaurga, A., and Arabas, S. (2023) Breakups are Complicated: An Efficient Representation of Collisional Breakup in the Superdroplet Method, Geoscientific Model Development 4193-4211, doi: 10.5194/gmd-16-4193-2023.

de Jong, E., Bischoff, T., Nadim, A., and Schneider, T. (2022) Spanning the Gap from Bulk to Bin: A Novel Spectral Microphysics Method, Journal of Advances in Modeling Earth Systems 14 (11), doi: 10.1029/2022MS003186.

Bieli, M., Dunbar, O.R.A., de Jong, E. K., Jaruga, A., Schneider, T., and Bischoff, T. (2022) An Efficient Bayesian Approach to Learning Droplet Collision Kernels: Proof of Concept Using “Cloudy”, a new n-Moment Bulk Microphysics Scheme, Journal of Advances in Modeling Earth Systems 14 (8), doi: 10.1029/2022MS002994.

2026 Lindau Nobel Laureate Meeting Young Scientist (sponsored by University of California)

2026 EOS Research Spotlight: https://eos.org/research-spotlights/comparing-machine-learning-models-of-raindrop-formation