Author

Nahian I. Hasan

Purdue University West LafayetteORCID 0000-0003-1725-4683Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioengineering· 2 Neuroscience· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Assay:electrophysiology· 1 Approach:experimental assay· 1 Organism:rat· 1

Frequent Co-Authors

Luis J. GomeziD· 3 shared Dezhi WangiD· 2 shared Amanda Jeanne WalenciakiD· 1 shared Moritz DannhaueriD· 1 shared Vanine SabinoiD· 1 shared Yang LiuiD· 1 shared Zhi‐De DengiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 12 mutual co-author links

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3 shared papersBioengineering

Luis J. GomezORCID

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3 papers

Recent·Most cited

BioengineeringIEEE Journal of Electromagnetics RF and Microwaves in Medicine and BiologyPeer-reviewedJun 5, 2026

Modeling Pyramidal Neurons Using Bidomain BEM and Hierarchical Matrix Approximation

Nahian I. Hasan, Vanine Sabino, Amanda Jeanne Walenciak…·Luis J. Gomez

The paper introduces a bidomain boundary element method for modeling electric fields in neurons and demonstrates its application to rat pyramidal neurons.

1 citation

ratexperimental assay

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BioengineeringImaging NeurosciencePeer-reviewedDec 9, 2024

Real-Time Computation of Brain E-Field for Enhanced Transcranial Magnetic Stimulation Neuronavigation and Optimization

Nahian I. Hasan, Moritz Dannhauer, Dezhi Wang…·Luis J. Gomez

The paper introduces a real-time method and software for computing brain electric field distributions to improve TMS neuronavigation and optimization.

11 citations

humanelectrophysiology

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NeurosciencebioRxivPreprintFeb 8, 2023

Fast And Accurate Population Level Transcranial Magnetic Stimulation via Low-Rank Probabilistic Matrix Decomposition (PMD)

Nahian I. Hasan, Dezhi Wang, Luis J. Gomez

The paper develops a fast method to predict transcranial magnetic stimulation (TMS) electric field (E-field) across many coil placements using probabilistic matrix decomposition, achieving rapid and accurate predictions for population-level TMS applications.

1 citation

humanstatistical model

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