A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer. - Francesco Di Natale; Harsh Bhatia; Timothy S. Carpenter; Chris Neale; Sara Kokkila Schumacher; Tomas Oppelstrup; Liam Stanton; Xiaohua Zhang; Shiv Sundram; Thomas R. W. Scogland; Gautham Dharuman; Michael P. Surh; et al. (SC, 2019)

Comparing GPU Power and Frequency Capping: A Case Study with the MuMMI Workflow. - Tapasya Patki; Zachary Frye; Harsh Bhatia; Francesco Di Natale; James N. Glosli; Helgi I. Ingólfsson; Barry Rountree (WORKS@SC, 2019)

Merlin: Enabling Machine Learning-Ready HPC Ensembles. - J. Luc Peterson; Rushil Anirudh; Kevin Athey; Benjamin Bay; Peer-Timo Bremer; Vic Castillo; Francesco Di Natale; David Fox; Jim A. Gaffney; David Hysom; Sam Ade Jacobs; Bhavya Kailkhura; et al. (CoRR, 2019)

Emulating I/O Behavior in Scientific Workflows on High Performance Computing Systems. - Fahim Chowdhury; Yue Zhu 002; Francesco Di Natale; Adam Moody; Elsa Gonsiorowski; Kathryn M. Mohror; Weikuan Yu (PDSW@SC, 2020)

Generalizable coordination of large multiscale workflows: challenges and learnings at scale. - Harsh Bhatia; Francesco Di Natale; Joseph Y. Moon; Xiaohua Zhang; Joseph R. Chavez; Fikret Aydin; Christopher B. Stanley; Tomas Oppelstrup; Chris Neale; Sara Kokkila Schumacher; Dong H. Ahn; Stephen Herbein; et al. (SC, 2021)

Scalable Composition and Analysis Techniques for Massive Scientific Workflows. - Dong H. Ahn; Xiaohua Zhang; Jeffrey Mast; Stephen Herbein; Francesco Di Natale; Dan Kirshner 001; Sam Ade Jacobs; Ian Karlin; Daniel J. Milroy; Bronis R. de Supinski; Brian Van Essen; Jonathan E. Allen; et al. (e-Science, 2022)

DFMan: A Graph-based Optimization of Dataflow Scheduling on High-Performance Computing Systems. - Fahim Chowdhury; Francesco Di Natale; Adam Moody; Kathryn M. Mohror; Weikuan Yu (IPDPS, 2022)

Enabling machine learning-ready HPC ensembles with Merlin. - J. Luc Peterson; Benjamin Bay; Joe Koning; Peter B. Robinson; Jessica Semler; Jeremy White; Rushil Anirudh; Kevin Athey; Peer-Timo Bremer; Francesco Di Natale; David Fox; Jim A. Gaffney; et al. (Future Gener. Comput. Syst., 2022)

Prediction Of Chemical Plants Operating Performances: A Machine Learning Approach. - Lelio Campanile; Luigi Piero Di Bonito; Mauro Iacono; Francesco Di Natale (ECMS, 2023)

Ensemble Models For Predicting CO Concentrations: Application And Explainability In Environmental Monitoring In Campania, Italy. - Lelio Campanile; Luigi Piero Di Bonito; Francesco Di Natale; Mauro Iacono (ECMS, 2024)

An eXplainable Artificial Intelligence framework to predict marine scrubbers performances. - Luigi Piero Di Bonito; Lelio Campanile; Mauro Iacono; Francesco Di Natale (Eng. Appl. Artif. Intell., 2025)