Alessandro Parente
researcher, ORCID id # 0000-0002-7260-7026
Facts
8 properties- Instance of
- human
- Occupation
- researcher
- Doctoral student
- Kamila Zdybał[5]
- Given name
- Alessandro[7]
- Imported from
- wholeness_audit_2026-05-02
🏷️ Also known as
en Alessandro Parente
🔖 Identifiers · 12
- ORCID iD
- 0000-0002-7260-7026
- VIAF cluster ID
- 13152561533515442134
- GND ID
- 1157023355
- OpenAlex ID
- A5031008443, A5091431096, A5124896948, A5126614083, A5135320550, A5135582157, A5137198471, A5137834025as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
- DDB person (GND) ID
- 1157023355
- Google Knowledge Graph ID
- /g/11fyyvbpyx
- Google Scholar author ID
- jP4eB7YAAAAJ
- IdRef ID
- 23763144X
- Loop ID
- 222920
- MR Author ID
- 1435324
- ResearcherID
- B-1115-2019
- Scopus author ID
- 22981074500
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 27
Adaptive chemistry via pre-partitioning of composition space and mechanism reduction,
Advanced regression methods for combustion modelling using principal components,
An evolutionary, data-driven approach for mechanism optimization: theory and application to ammonia combustion,
Application of Bound-to-Bound Data Collaboration approach for development and uncertainty quantification of a reduced char combustion model,
Application of machine learning for filtered density function closure in MILD combustion,
Application of reduced-order models based on PCA & Kriging for the development of digital twins of reacting flow applications,
Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches,
Combination of polynomial chaos and Kriging for reduced-order model of reacting flow applications
+19 more
← Authored by 27
Adaptive chemistry via pre-partitioning of composition space and mechanism reduction,
Advanced regression methods for combustion modelling using principal components,
An evolutionary, data-driven approach for mechanism optimization: theory and application to ammonia combustion,
Application of Bound-to-Bound Data Collaboration approach for development and uncertainty quantification of a reduced char combustion model,
Application of machine learning for filtered density function closure in MILD combustion,
Application of reduced-order models based on PCA & Kriging for the development of digital twins of reacting flow applications,
Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches,
Combination of polynomial chaos and Kriging for reduced-order model of reacting flow applications
+19 more
Affiliated with 2
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Summary
Alessandro Parente worked as a researcher[1].
Body
Career and Affiliations
Employers include National Fund for Scientific Research[2], an organization[8], in Belgium[9] and Université libre de Bruxelles[3], a university[10], in Belgium[11], founded in 1969[12], headquartered in Ixelles[13].
FAQs
What did Alessandro Parente do for work?
Alessandro Parente worked as researcher[1].