Author

Mafizur Rahman

Observed names: M. Mazibur Rahman, Md-Mafizur Rahman

Institution: Prairie View A&M University

Observed institutions: Prairie View A&M University, Bangladesh Atomic Energy Commission

ORCID: 0009-0007-4870-0232

Observed ORCID: 0009-0007-4870-0232

OpenAlex ID: A5100876112

Evaluating Pretrained Deep Learning Models for Image Classification Against Individual and Ensemble Adversarial Attacks

2025 · Mafizur Rahman, Prosenjit Roy, et al. · IEEE Access · 24

Advanced Retinal Image Segmentation using U-Net Architecture: A Leap Forward in Ophthalmological Diagnostics

2024 · Nobanul Hasan, Md Jahid Alam Riad, et al. · International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) · 9

Validation study of the cell code WIMS-D and a 69 group library based on JENDL-3.2

2004 · Mafizur Rahman, M.A.W Mandal, et al. · Annals of Nuclear Energy · 6

Assessment of radioactive pollution around a fertilizer factory complex in the North-Eastern part of Bangladesh

2013 · S Ghose, M. Akhter, et al. · Radioprotection · 4

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Validation study of the Monte Carlo code MVP for analysis of two-region TCA critical experiments with PWR-type MOX fuels

2006 · Mafizur Rahman, T. Suzaki, et al. · Progress in Nuclear Energy · 2

Generation, Testing, and Validation of a WIMS-D/4 Multigroup Cross-Section Library Based on the JENDL-3.2 Nuclear Data

2001 · Mafizur Rahman, Hideki Takano · Nuclear Technology · 2

Comparative Analysis of Inference Performance of Pre-Trained Convolutional Neural Networks in Analog Accelerators

2025 · Mafizur Rahman, Lijun Qian · IEEE Transactions on Emerging Topics in Computational Intelligence · 1

Attention Under Attack: Analog Noise Effects and Mechanistic Vulnerabilities in Transformer Models

2026 · Mafizur Rahman, Lijun Qian · Proceedings of the conference - Association for Computational Linguistics. Meeting

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Comparative Analysis of Inference Performance of Pre-Trained Deep Neural Networks in Analog Accelerators

2024 · Mafizur Rahman, Lin Li, et al. · International Conference on Machine Learning and Applications

Peer Review Report For: The genome sequence of the Spruce-seed moth, Cydia strobilella (Linnaeus, 1758) [version 1; peer review: 2 approved]

2024 · Md-Mafizur Rahman · Wellcome Open Research

Towards Global River Discharge Assessment Using a Distributed Hydrological Model and Global Data Sets

2010 · Oliver Cristian Saavedra Valeriano, Toshio Koike1, et al. · DOAJ (DOAJ: Directory of Open Access Journals)

Works count: 11

Citation count: 48

H-index: 4

I10-index: 1