Author

Shiraz S Kaderuppan

Newcastle UniversityORCID 0000-0002-0317-8272Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:dimensionality reduction· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1

Frequent Co-Authors

Wai Lok WooiD· 2 shared Anurag SharmaiD· 1 shared Anurag SharmaiD· 1 shared Eugene· 1 shared Eugene Wai Leong WongiD· 1 shared Muhammad Ramadan SaifuddiniD· 1 shared Wong Wai Leong· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 13 mutual co-author links

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2 shared papersBioinformatics

Wai Lok WooORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 14, 2025

In silico prediction of cellular organelles from computationally super-resolved (SR) phase-modulated optical micrographs

Shiraz S Kaderuppan, Anurag Sharma, Muhammad Ramadan Saifuddin…·Wai Lok Woo

The paper develops deep neural networks to predict cellular organelles from super-resolved DIC and PCM micrographs, showing good correlation with ground truth images.

DOI 10.1101/2025.09.14.675997

imagingdeep learning

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJan 24, 2023

{Theta}-Net: Achieving Enhanced Phase-Modulated Optical Nanoscopy in silico through a computational 'string of beads' architecture

Shiraz S Kaderuppan, Eugene Wai Leong Wong, Anurag Sharma, Wai Lok Woo

This paper introduces {Theta}-Net, a computational architecture that improves super-resolved optical microscopy images in silico, outperforming existing frameworks and demonstrating effectiveness under poor signal-to-noise ratios.

DOI 10.1101/2023.01.24.525271

imagingdeep learning

𝕏 PostBluesky