Hamed Saidaoui

About Hamed Saidaoui

Hamed Saidaoui, With an exceptional h-index of 6 and a recent h-index of 5 (since 2020), a distinguished researcher at King Abdullah University of Science and Technology, specializes in the field of Theoretical physics, Machine learning, Condensed Matter Physics, Spin Transport.

His recent articles reflect a diverse array of research interests and contributions to the field:

Deep nurbs--admissible neural networks

Band gap tuning in aluminum doped two-dimensional hexagonal boron nitride

Direct scheme calculation of the kinetic energy functional derivative using machine learning

Hamed Saidaoui Information

University

Position

Ph.D (KAUST)

Citations(all)

220

Citations(since 2020)

156

Cited By

132

hIndex(all)

6

hIndex(since 2020)

5

i10Index(all)

6

i10Index(since 2020)

5

Email

University Profile Page

King Abdullah University of Science and Technology

Google Scholar

View Google Scholar Profile

Hamed Saidaoui Skills & Research Interests

Theoretical physics

Machine learning

Condensed Matter Physics

Spin Transport

Top articles of Hamed Saidaoui

Title

Journal

Author(s)

Publication Date

Deep nurbs--admissible neural networks

arXiv preprint arXiv:2210.13900

Hamed Saidaoui

Luis Espath

Rául Tempone

2022/10/25

Band gap tuning in aluminum doped two-dimensional hexagonal boron nitride

Materials Chemistry and Physics

Merid Legesse

Sergey N Rashkeev

Hamed Saidaoui

Fedwa El Mellouhi

Said Ahzi

...

2020/8/1

Direct scheme calculation of the kinetic energy functional derivative using machine learning

arXiv preprint arXiv:2003.00876

H Saidaoui

S Kais

S Rashkeev

FH Alharbi

2020/2/22

See List of Professors in Hamed Saidaoui University(King Abdullah University of Science and Technology)