| 2022 | ICDM | Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning. | Siyan Liu, Dan Lu, Daniel M. Ricciuto, Anthony P. Walker |
| 2020 | ICDM | Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling. | Dan Lu, Daniel M. Ricciuto |
| 2019 | ICCS | Parallel Computing for Module-Based Computational Experiment. | Zhuo Yao, Dali Wang, Daniel M. Ricciuto, Fengming Yuan, Chunsheng Fang |
| 2019 | ICDM | An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science. | Dan Lu, Siyan Liu, Daniel M. Ricciuto |
| 2019 | ICDM | Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction. | Dan Lu, Daniel M. Ricciuto |
| 2014 | ICCS | Stochastic Parameterization to Represent Variability and Extremes in Climate Modeling. | Roisin Langan, Richard Archibald, Matthew Plumlee, Salil Mahajan, Daniel M. Ricciuto, Chengen Yang, Rui Mei, Jiafu Mao, Xiaoying Shi, Joshua S. Fu |
| 2013 | ICCS | ParCAT: Parallel Climate Analysis Toolkit. | Brian E. Smith, Daniel M. Ricciuto, Peter E. Thornton, Galen M. Shipman, Chad A. Steed, Dean N. Williams, Michael F. Wehner |