Salim Shekh | Mathematics | Young Scientist Award

Young Scientist Award

Salim Shekh
Assistant Professor, Department of Mathematics
Affiliation S. P. M. Science and Gilani Arts Commerce College
Country India
Scopus ID 56572682400
Documents 75
Citations 1,294
h-index 23
Subject Area Mathematics
Event International Forensic Scientist Awards
ORCID 0000-0003-4545-1975
Salim Shekh
S. P. M. Science and Gilani Arts Commerce College, India

Salim Shekh is an Indian mathematician and researcher affiliated with S. P. M. Science and Gilani Arts Commerce College, India. His research mainly focuses on cosmology, gravitation, dark energy, and modified gravity theories.[1] He has published several research articles in international journals and gained strong citation impact in mathematical physics and cosmology.[2]

Abstract

This article highlights the academic achievements of Salim Shekh in mathematics and cosmology. His work mainly studies modified gravity, dark energy models, and cosmological analysis. His publications and citation record show steady research contributions in theoretical physics and astrophysics.[3]

Keywords

General Relativity; Gravitation; Dark Energy; Cosmology; f(Q) Gravity; Mathematical Physics; Astrophysics.

Introduction

Modern cosmology studies the evolution and structure of the universe using mathematical and physical theories. Salim Shekh has contributed to this field through research on dark energy and modified gravity theories.[4] His work includes theoretical analysis and observational studies related to cosmic acceleration and cosmological models.[5]

Research Profile

Shekh’s research mainly focuses on modified gravity theories, especially f(Q) gravity and dark energy cosmology. His studies discuss anisotropic cosmological models, holographic dark energy, and observational constraints.[6]

He has published papers in journals such as Physics of the Dark Universe, Journal of High Energy Astrophysics, and Classical and Quantum Gravity.[7]

Research Contributions

One of Shekh’s important works is Anisotropic nature of space–time in fQ gravity, which studied cosmological anisotropy in modified gravity.[8] He also worked on cosmic acceleration and energy conditions in symmetric teleparallel gravity models.[9]

His studies on holographic dark energy and observational cosmology have contributed to discussions on accelerated expansion of the universe and alternative gravity theories.[10]

Publications

  • Anisotropic nature of space–time in fQ gravity, 2022.[8]
  • Models of holographic dark energy in f(Q) gravity, 2021.[10]
  • Observational constraints in accelerated emergent f(Q) gravity model, 2023.[11]
  • Modelling the accelerating universe with f(Q) gravity: observational consistency, 2024.[12]

Research Impact

Shekh has received more than 1,294 citations and has an h-index of 23, showing good academic impact in cosmology and mathematical physics.[2] His research is widely referenced in studies related to modified gravity and dark energy models.[12]

Award Suitability

Salim Shekh’s publication record, citation profile, and international collaborations support his suitability for the Young Scientist Award. His research contributions in cosmology and modified gravity theories demonstrate continuous academic involvement and scientific productivity.[8]

Conclusion

Salim Shekh has contributed significantly to research in cosmology, gravitation, and modified gravity theories. His publications, citation impact, and ongoing academic work reflect his active role in theoretical physics and mathematical cosmology.[10]

References

  1. Scopus Author Profile: Salim Harun Shekh.
    https://www.scopus.com/authid/detail.uri?authorId=56572682400
  2. Scopus citation metrics and h-index profile.
  3. Google Scholar profile of Dr. Salim Shekh.
    https://scholar.google.com/citations?hl=en&user=VOJJ1DgAAAAJ
  4. Shekh, S. H. (2021). Models of holographic dark energy in f(Q) gravity.
    https://doi.org/10.1016/j.dark.2021.100850
  5. Late-time acceleration studies in f(Q) gravity.
  6. Research publications on modified gravity and cosmology.
  7. International journals in cosmology and astrophysics.
  8. Koussour, M., Shekh, S. H., & Bennai, M. (2022). Anisotropic nature of space–time in fQ gravity.
    https://doi.org/10.1016/j.dark.2022.101051
  9. Cosmic acceleration and energy conditions in symmetric teleparallel gravity.
  10. Holographic dark energy studies in modified gravity.
  11. Observational constraints in accelerated emergent f(Q) gravity model.
  12. Modelling the accelerating universe with f(Q) gravity.

Yang Liu | Mathematics | Research Excellence Award

Assist. Prof. Dr. Yang Liu | Mathematics | Research Excellence Award

Great Bay University | China

Dr. Yang Liu is a researcher in numerical optimization and scientific computing, with a focus on scalable algorithms for large-scale nonconvex problems. His work integrates numerical linear algebra, tensor methods, and Krylov subspace techniques to advance efficient optimization frameworks. He has contributed to the development of Newton-MR methods, pseudoinverse solution recovery, and adaptive regularization strategies for higher-order tensor models. His research emphasizes matrix-free and high-performance implementations, with contributions incorporated into advanced solver libraries. Dr. Yang Liu actively engages in international collaborations and contributes to peer-reviewed journals and conferences in optimization and applied mathematics.

                        Citation Metrics (Google Scholar)

300

250

200

150

100

50

0

 

Citations
119
Documents
11
h-index
7

Citations

Documents

h-index

View Google Scholar Profile  View ORCID Profile

Featured Publications


Convergence of Newton-MR under inexact Hessian information

– SIAM Journal on Optimization, 2021 | Cited by: 25

Newton-MR: Inexact Newton method with minimum residual sub-problem solver

– EURO Journal on Computational Optimization, 2022 | Cited by: 22

MINRES: From negative curvature detection to monotonicity properties

– SIAM Journal on Optimization, 2022 | Cited by: 14

Descent properties of an Anderson accelerated gradient method with restarting

– SIAM Journal on Optimization, 2024 | Cited by: 11