Author

Z.-D. Deng

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioengineering· 2 Physiology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:drug response / drug discovery· 3 Assay:electrophysiology· 3 Organism:human· 3 Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Approach:optimal transport· 1

Frequent Co-Authors

A. V. Peterchev· 1 shared C. Lu· 1 shared D. Wang· 1 shared F.-S. Choa· 1 shared L. J. Gomez· 1 shared M. Dannhauer· 1 shared N. I. Hasan· 1 shared S. M. Goetz· 1 shared

Activity by Year

2018-2023 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 10 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperPhysiology

A. V. Peterchev

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

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

N. I. Hasan, M. Dannhauer, D. Wang, Z.-D. Deng, L. J. Gomez

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

bioRxiv · Oct 25, 2023 · PreprintBioengineering

Augmenting Transcranial Magnetic Stimulation Coil with Magnetic Material: An Optimization Approach

C. Lu, Z.-D. Deng, F.-S. Choa

This paper proposes a novel TMS coil design using magnetic materials to improve the depth-focality tradeoff, achieving better penetration depth and focality than existing commercial coils.

bioRxiv · Jan 21, 2022 · PreprintBioengineering

Statistical Model of Motor Evoked Potentials for Simulation of Transcranial Magnetic and Electric Stimulation

S. M. Goetz, S. M. Mahdi Alavi, Z.-D. Deng, A. V. Peterchev

This paper develops a statistical model of motor evoked potentials (MEPs) to simulate individualized and population-level data for transcranial stimulation applications.

bioRxiv · Dec 17, 2018 · PreprintPhysiology