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Nasimul Noman

researcher, ORCID id # 0000-0002-8566-0870
Person human Q58219123

Facts

5 properties
Instance of
human
Sex or gender
male[4]
Occupation
researcher, computer scientist
Employer
University of Newcastle[3]
Educated at
University of Tokyo
🏷️ Also known as
en Nasimul Noman
🔖 Identifiers · 12
ISNI
0000000367181224
ORCID iD
0000-0002-8566-0870
VIAF cluster ID
231793844
Library of Congress authority ID
nb2012004354
GND ID
1018858970
DBLP author ID
06/215
Dimensions author ID
015664561055.46
IdRef ID
166042692
NL CR AUT ID
utb2013748526
National Library of Israel J9U ID
987007389404105171
Scopus author ID
6508099536
Yale LUX ID
person/82d5dc9a-58ad-462e-ba9e-bb62a5da2d5c

Report an error or request removal Lineage (PROV-JSON)

🔗 Connections
Author of 9
A comparative analysis of deep neural network architectures for sentence classification using genetic algorithm, A Metaheuristic Framework for Energy-Intensive Industries With Batch Processing Machines, An adaptive memetic algorithm for feature selection using proximity graphs, An Effective Method for Evolving Reaction Networks in Synthetic Biochemical Systems, Ensuring Fairness and Gradient Privacy in Personalized Heterogeneous Federated Learning, Fast Automatic Optimisation of CNN Architectures for Image Classification Using Genetic Algorithm, Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification, Improved Soft Actor-Critic: Mixing Prioritized Off-Policy Samples With On-Policy Experiences +1 more
← Authored by 9
A comparative analysis of deep neural network architectures for sentence classification using genetic algorithm, A Metaheuristic Framework for Energy-Intensive Industries With Batch Processing Machines, An adaptive memetic algorithm for feature selection using proximity graphs, An Effective Method for Evolving Reaction Networks in Synthetic Biochemical Systems, Ensuring Fairness and Gradient Privacy in Personalized Heterogeneous Federated Learning, Fast Automatic Optimisation of CNN Architectures for Image Classification Using Genetic Algorithm, Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification, Improved Soft Actor-Critic: Mixing Prioritized Off-Policy Samples With On-Policy Experiences +1 more
Affiliated with 2
University of Newcastle, Hunter Medical Research Institute
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Summary

Nasimul Noman has worked as a researcher[1] and computer scientist[2].

FAQs

What did Nasimul Noman do for work?

Nasimul Noman worked as a researcher[1] and computer scientist[2].

Related Entities

Hunter Medical Research Institute

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [4] ↑ . IdRef. Retrieved . wikidata.org.
  2. [1] ↑ . wikidata.org.
  3. [2] ↑ . Integrated Authority File. Retrieved . wikidata.org.
  4. [3] ↑ . ORCID Public Data File 2023. Retrieved . pub.orcid.org. Provenance: wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Nasimul Noman. Retrieved October 30, 2026, from https://4ort.xyz/entity/nasimul-noman
MLA “Nasimul Noman.” 4ort.xyz Knowledge Graph, 4ort.xyz, 30 Oct. 2026, https://4ort.xyz/entity/nasimul-noman.
BibTeX @misc{4ortxyz_nasimul-noman_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Nasimul Noman}}, year = {2026}, url = {https://4ort.xyz/entity/nasimul-noman}, note = {Accessed: 2026-10-30}}
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Edit History

Rolling log of changes to this entity's Wikidata record. Values shown reflect the current state of each edited property — follow the history link to see the precise diff for any edit.

  1. 24w ago · Epìdosis · 2026-05-21 view diff on Wikidata ↗
    National Library of Israel J9U ID → 987007389404105171
    GND ID → 1018858970
    Dimensions author ID → 015664561055.46
    ORCID iD → 0000-0002-8566-0870
    + 15 other properties edited (see Wikidata diff for full list)
    "/* wbeditentity-update:0| */ QuickStatements 3.0 [[:toollabs:qs-dev/batch/32118|batch #32118]]: import P21 and P106 from GND (31)"
Live feed via Wikidata EventStreams. New edits appear within minutes of being made on Wikidata.