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Rukhmini Bandyopadhyay

3 papers hereh-index 362 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • q-bio.QM2
  • eess.IV1

identity via Semantic Scholar / OpenAlex

most citedFrom Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research

16 citations · 17 across the 3 of their papers we have counts for

collaborators

3 papers

eess.IV2026★ 1 cited

Projection Guided Personalized Federated Learning for Low Dose CT Denoising

Anas Zafar, Muhammad Waqas, Amgad Muneer +2

Low-dose CT (LDCT) reduces radiation exposure but introduces protocol-dependent noise and artifacts that vary across institutions. While federated learning enables collaborative tr…

q-bio.QM2025

The Next Layer: Augmenting Foundation Models with Structure-Preserving and Attention-Guided Learning for Local Patches to Global Context Awareness in Computational Pathology

Muhammad Waqas, Rukhmini Bandyopadhyay, Eman Showkatian +12

Foundation models have recently emerged as powerful feature extractors in computational pathology, yet they typically omit mechanisms for leveraging the global spatial structure of…

q-bio.QM2025★ 16 cited

From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research

Amgad Muneer, Muhammad Waqas, Maliazurina B Saad +16

Cancer research is increasingly driven by the integration of diverse data modalities, spanning from genomics and proteomics to imaging and clinical factors. However, extracting act…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.