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.

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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 

Vyacheslav Abramov | Mathematics | Research Excellence Award

Dr. Vyacheslav Abramov | Mathematics | Research Excellence Award

Retired Academician, Monash University | Australia

Dr. Vyacheslav Abramov is an internationally recognized mathematician whose research centers on probability theory, stochastic processes, and queueing systems, with strong applications to telecommunications, computer networks, and applied stochastic modelling. His scholarly work has made foundational contributions to the theory of Markov chains, random walks, loss systems, Toeplitz and circulant matrices, and asymptotic methods in queueing networks. He is also known for extending classical convergence tests, recurrence criteria, and fixed-point theorems to infinite-dimensional settings. His research bridges rigorous mathematical theory with practical modelling problems in engineering and networked systems.

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Featured Publications


A new criterion for recurrence of Markov chains with an infinitely countable set of states

– Theory of Probability and Mathematical Statistics, 112(5), October 2024


CONDITIONS FOR RECURRENCE AND TRANSIENCE FOR TIME-INHOMOGENEOUS BIRTH-AND-DEATH PROCESSES

– Bulletin of the Australian Mathematical Society, 109(2), May 2023

Malathy N | Computer Science | Best Researcher Award

Dr. Malathy N | Computer Science | Best Researcher Award

Associate Professor | Mepco Schlenk Engineering College | India

Dr. N. Malathy is an esteemed academician and researcher currently serving as an Associate Professor in the Department of Information Technology at Mepco Schlenk Engineering College. With over 12 years of experience in teaching and research, she has made significant contributions to the fields of Mobile Computing, IoT, Networks, Fog Computing, and Machine Learning. She holds a Ph.D. in Fog Computing from Anna University (2024) and has published 24 research papers. Her expertise extends to international certifications in AI, cloud computing, and cybersecurity, and she is an active mentor and reviewer in her domain.

Profile

Google Scholar

ORCID

Scopus

Strengths for the Awards✨

  • Research Excellence 📚

    • 24 research publications, including 5 SCI and 11 Scopus-indexed papers.
    • Notable contributions to Fog Computing, IoT, Machine Learning, and Distributed Computing.
    • Recent high-impact publications, including studies on Federated Learning, Intrusion Detection, and Green Computing.
  • Innovation & Intellectual Property 🏅

    • One granted patent and four published patents demonstrate innovative contributions to applied research.
    • Published two book chapters, contributing to academic literature.
  • Recognized Expertise & Certifications 🎓

    • International certifications from NVIDIA (Deep Learning), Infosys (Generative AI), and Checkpoint (Cybersecurity).
    • Oracle certification in PL/SQL Database Programming and EMC Cloud Infrastructure & Services certification.
    • Top 1%-5% rankings in multiple NPTEL courses, showing a commitment to continuous learning.
  • Professional Engagement & Recognition 🌍

    • Reviewer for 44 research papers, indicating active involvement in the research community.
    • Awarded Best Paper at an International Conference (ICSTA 2022).
    • Guest lectures (9) and faculty development programs (FDPs) conducted, demonstrating leadership in research dissemination.
    • Member of ISTE and CSI, indicating professional affiliation.

🎓 Education

  • Ph.D. in Fog Computing, Anna University, 2024
  • M.E. in Computer & Communication, SSN College of Engineering, Anna University, 2012
  • B.E. in Computer Science & Engineering, Francis Xavier Engineering College, Anna University, 2010

👩‍🏫 Experience

  • Associate Professor, MEPCO Schlenk Engineering College (2024–Present)
  • Assistant Professor (Sl. Grade), MEPCO Schlenk Engineering College (2023–2024)
  • Assistant Professor (Sr. Grade), MEPCO Schlenk Engineering College (2017–2023)
  • Assistant Professor, MEPCO Schlenk Engineering College (2012–2017)

🔬 Research Interests On Computer Science

Dr. Malathy’s research spans multiple cutting-edge areas, including:

  • Distributed Computing: Efficient task scheduling, multi-objective optimization for fog computing
  • IoT: Smart systems development, security research, intrusion detection
  • Fog Computing: Resource allocation, task scheduling, privacy-preserving methodologies
  • Machine Learning: Federated learning for security, optimization algorithms, AI applications

🏆 Awards & Achievements

  • Best Paper Award, ICSTA 2022, Ramco Institute of Technology
  • Top 1% & 5% Ranker in NPTEL Courses on Cloud Computing, Big Data, and HCI
  • International Certifications:
    • NVIDIA Deep Learning (2023)
    • Checkpoint Certified Security Administrator R81 (2024)
    • Generative AI Certifications (Infosys, 2024)
    • Oracle Certification in Database Programming (2019)
  • Top Performing Mentor, NPTEL (2025)

📚 Publications

Dr. Malathy has authored several impactful research papers in reputed journals:

  • Multi‐objective task scheduling in fog computing using improved gaining sharing knowledge based algorithm

    • Authors: M. Navaneetha Krishnan, R. Thiyagarajan
    • Year: 2022
    • Citations: 12
  • VAGR—Void aware in geographic routing for wireless sensor networks

    • Authors: A. Revathi, N. Malathy
    • Year: 2016
    • Citations: 8
  • Entropy‐based complex proportional assessment for efficient task scheduling in fog computing

    • Authors: N. K. Malathy, T. Revathi
    • Year: 2023
    • Citations: 7
  • Opposition‐based improved memetic algorithm for placement of concurrent Internet of Things applications in fog computing

    • Authors: N. Malathy, T. Revathi
    • Year: 2024
    • Citations: 3
  • Pedestrian safety system with crash prediction

    • Authors: M. K. V. S. Ms. N. Malathy, Dr. S. Kavi Priya
    • Year: 2022
    • Citations: 3*
  • Smart trash bin level monitoring system

    • Authors: M. S. A. Ms. N. Malathy, Miss. D. Kaviyaadharshani
    • Year: 2022
    • Citations: 3*
  • Pedwarn-enhancement of pedestrian safety using mobile application

    • Authors: N. Malathy, S. Sabarish Nandha, B. Praveen, K. Pravin Kumar
    • Year: 2020
    • Citations: 2
  • Topology control for depth adjustment using geographic routing in underwater wireless sensor networks

    • Authors: A. Revathi, N. Malathy
    • Year: 2016
    • Citations: 1
  • Energy Efficient Workflow Scheduling for Fog-enhanced IOT Based Healthcare Application

    • Authors: N. Malathy, M. Kartheeswari, M. Yogalakshmi
    • Year: Not mentioned
    • Citations: 1

📌 Conclusion

Dr. N. Malathy continues to make remarkable strides in academia, research, and technological innovation. Her expertise in Distributed Computing, IoT, Fog Computing, and Machine Learning is evident from her numerous publications, patents, and academic contributions. Through mentoring, research, and professional engagements, she actively bridges theoretical advancements with real-world applications, positioning herself as a leader in her field.