Simone Casolo

Manager and industrial data scientist at Cognite. Ph.D. in theoretical chemistry, University of Milan.

I specialize in applying data science and machine learning to heavy industries such as process, energy, and chemicals, where complex and messy sensor data are the norm. I am especially interested in applying AI and machine learning to industrial processes. Also, I have been applying topological and geometrical methods for signal analysis, condition monitoring, and hybrid modeling.

Below are highlights from applied work on real assets; see the projects page for summaries and the publications page for bibliographic details.

selected publications

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health

Peter Collett, Alexander Stasik, Simone Casolo, and Signe Riemer-Sørensen

(2026)

arXiv Bib HTML

@misc{collett2026fastbayesianequipmentcondition,
  title = {Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health},
  author = {Collett, Peter and Stasik, Alexander and Casolo, Simone and Riemer-S{\o}rensen, Signe},
  year = {2026},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
  url = {https://arxiv.org/abs/2604.20735},
}

Testing Topological Data Analysis for Condition Monitoring of Wind Turbines

Simone Casolo, Alexander Stasik, Zhenyou Zhang, and Signe Riemer-Sørensen

In PHM Society European Conference, 8 (1), 10, (2024)

DOI arXiv Bib HTML

@inproceedings{casolo2024wind,
  title = {Testing Topological Data Analysis for Condition Monitoring of Wind Turbines},
  author = {Casolo, Simone and Stasik, Alexander and Zhang, Zhenyou and Riemer-S{\o}rensen, Signe},
  booktitle = {PHM Society European Conference},
  volume = {8},
  number = {1},
  pages = {10},
  year = {2024},
  doi = {10.36001/phme.2024.v8i1.4117},
}

Cloud-based virtual flow metering system powered by a hybrid physics-data approach for water production monitoring in an offshore gas field

Rafael H. Nemoto, Roberto Ibarra, Gunnar Staff, Anvar Akhiiartdinov, Daniel Brett, Peder Dalby, Simone Casolo, and Andris Piebalgs

Digital Chemical Engineering, 9, 100124, (2023)

DOI Bib HTML

@article{casolo2023vfm,
  title = {Cloud-based virtual flow metering system powered by a hybrid physics-data approach for water production monitoring in an offshore gas field},
  author = {Nemoto, Rafael H. and Ibarra, Roberto and Staff, Gunnar and Akhiiartdinov, Anvar and Brett, Daniel and Dalby, Peder and Casolo, Simone and Piebalgs, Andris},
  journal = {Digital Chemical Engineering},
  volume = {9},
  pages = {100124},
  year = {2023},
  issn = {2772-5081},
  doi = {10.1016/j.dche.2023.100124},
}

Topological data analysis of slug flow in offshore wells

Simone Casolo

Digital Chemical Engineering, 4, 100045, (2022)

DOI Bib HTML PDF

@article{casolo2022slug,
  title = {Topological data analysis of slug flow in offshore wells},
  author = {Casolo, Simone},
  journal = {Digital Chemical Engineering},
  volume = {4},
  pages = {100045},
  year = {2022},
  doi = {10.1016/j.dche.2022.100045},
}