Riasat Ali | Particle physics and cosmology | Editorial Board Member | 3098

Editorial Board Member

Riasat Ali
Riasat Ali
Affiliation Shanghai University
Country China
Scopus ID 57212863194
Documents 76
Citations 1,159
h-index 20
Subject Area Particle Physics and Cosmology
Event Global Particle Physics Excellence Awards
ORCID Connected via Scopus

Riasat Ali is a researcher affiliated with Shanghai University, China, whose academic work focuses on particle physics, cosmology, black hole physics, gravitation, and related theoretical investigations. His research profile demonstrates continuous scholarly engagement in contemporary astrophysical and gravitational studies, particularly in modified gravity models, plasma effects on black hole shadows, and quantum gravity-inspired thermodynamics.[1]

Abstract

This article presents an overview of the academic profile and scholarly contributions of Riasat Ali in the fields of particle physics and cosmology. His research portfolio includes investigations into black hole thermodynamics, plasma-induced gravitational lensing, Hawking radiation, and modified gravity theories. Through publications in recognized international journals, his work contributes to ongoing discussions in theoretical astrophysics and gravitational physics.[1][2]

Keywords

Particle physics, cosmology, black hole physics, Horndeski gravity, Hawking radiation, plasma physics, gravitational lensing, modified gravity, astrophysics, quantum gravity.

Introduction

Theoretical particle physics and cosmology continue to provide important frameworks for understanding gravitational phenomena, spacetime geometry, and high-energy astrophysical systems. Researchers working in these areas frequently examine black hole behavior, quantum corrections, and observational signatures associated with relativistic environments. Riasat Ali has contributed to these themes through studies involving black hole shadows, photon deflection, and thermodynamic properties within alternative gravity frameworks.[2]

Research Profile

According to Scopus author records, Riasat Ali has authored or co-authored 76 indexed documents and accumulated more than 1,159 citations with an h-index of 20. His publications primarily focus on gravitational physics, black hole thermodynamics, plasma effects in astrophysical systems, and modified theories of gravity.[1]

His recent works examine topics such as charged hairy black holes in Horndeski gravity, photon deflection in dispersive media, and generalized uncertainty principle corrections in black hole systems. These investigations contribute to the broader understanding of relativistic astrophysical environments and quantum-inspired gravitational models.[2]

Research Contributions

  • Investigated unstable equilibrium and chaos-bound violations in charged hairy black holes within Horndeski gravity frameworks.
  • Studied photon deflection and black hole shadow formation under the influence of plasma and dispersive media.
  • Explored Hawking temperature corrections and thermodynamic properties associated with generalized uncertainty principles.
  • Published research associated with modified gravity theories including Rastall gravity and f(Q,BQ) gravity models.

Publications

  1. “Unstable equilibrium and chaos-bound violation for a charged hairy black hole in Horndeski gravity,” New Astronomy, 2026.
  2. “Deflection of photon and shadow cast for black hole spacetime under the impact of a dispersive medium,” Indian Journal of Physics, 2026.
  3. “Greybody Factor and Hawking Temperature of ModMax-AdS Black Holes Surrounded by Perfect Fluid Dark Matter,” Fortschritte Der Physik, 2025.
  4. “Exploring plasma and dark matter on photon deflection by Reissner–Nordström black hole with scalar hair and its shadow,” Annals of Physics, 2025.

Research Impact

The research contributions of Riasat Ali demonstrate interdisciplinary engagement between cosmology, astrophysics, and gravitational theory. His publication metrics and citation record indicate continued academic visibility within theoretical physics communities. The integration of plasma physics, dark matter models, and quantum corrections into black hole studies reflects current directions in modern gravitational research.[1]

Award Suitability

Riasat Ali’s research profile aligns with the objectives of the Global Particle Physics Excellence Awards, particularly in the recognition of emerging contributions to theoretical particle physics and cosmology. His sustained publication activity, citation impact, and involvement in advanced gravitational studies support his suitability for editorial and scholarly recognition within the international academic community.

Conclusion

Riasat Ali has established a notable academic presence in the domains of particle physics and cosmology through research on black hole dynamics, modified gravity, and relativistic astrophysics. His scholarly activities, publication output, and citation performance indicate active participation in contemporary theoretical physics research and continued contribution to advancing cosmological understanding.

References

  1. Elsevier. (2026). Scopus author details: Riasat Ali, Author ID 57212863194. Scopus.
    http://scopus.com/authid/detail.uri?authorId=57212863194
  2. Ali, R. H. (2026). Unstable equilibrium and chaos-bound violation for a charged hairy black hole in Horndeski gravity. New Astronomy.
    10.1016/j.newast.2026.102564
  3. Ali, R. H. (2025). Exploring plasma and dark matter on photon deflection by Reissner–Nordström black hole with scalar hair and its shadow. Annals of Physics.
    https://doi.org/10.1016/j.aop.2025.170201
  4. Google Scholar. (2026). Riasat Ali citation profile.
    https://scholar.google.com/citations?user=Stp2lpMAAAAJ&hl=en

Praveen Kumar Dhankar | Particle physics and cosmology | Research Excellence Award

Dr. Praveen Kumar Dhankar | Particle physics and cosmology | Research Excellence Award

Symbiosis Institute of Technology, India

Dr. Praveen Kumar Dhankar is an emerging researcher recognized for his valuable academic and scientific contributions in cosmology, modified gravity theories, and applied machine learning. Affiliated with Symbiosis Institute of Technology, he has demonstrated consistent research productivity through publications in reputed international journals. His scholarly profile reflects 40 documents, 78 citations, and an h-index of 5, highlighting growing academic influence within interdisciplinary scientific domains. His recent investigations in Gauss–Bonnet gravity, f(G) cosmology, and observational astrophysics showcase analytical expertise and strong computational understanding. In addition, his work connecting machine learning with precision agriculture illustrates research versatility and practical innovation. Through continuous engagement in advanced theoretical studies and collaborative scientific publications, Dr. Dhankar has established himself as a dedicated researcher contributing to modern developments in physics, cosmology, and data-driven applications with promising future research potential.

Professional Profile

Education

Dr. Praveen Kumar Dhankar has developed a strong academic foundation through dedicated study in physics, computational sciences, and interdisciplinary technological applications. His educational journey reflects a deep commitment to understanding theoretical cosmology, modified gravity theories, and modern data-driven scientific methodologies. Through advanced academic training, he acquired expertise in analytical modeling, observational data interpretation, statistical techniques, and machine learning applications in scientific research. His educational background has enabled him to work effectively across diverse scientific domains, combining theoretical understanding with computational innovation. Continuous engagement with emerging scientific developments has strengthened his academic profile and expanded his technical competencies in cosmological simulations and predictive analysis. His educational preparation demonstrates intellectual curiosity, scientific discipline, and the capacity to contribute meaningfully to modern research challenges. This strong academic grounding has become the basis for his growing influence in theoretical physics and interdisciplinary computational investigations.

Professional Experience

Dr. Praveen Kumar Dhankar possesses valuable professional and research experience through his academic association with Symbiosis Institute of Technology and collaborative scientific projects. His experience spans theoretical cosmology, modified gravity investigations, computational data analysis, and interdisciplinary technological applications. Over the years, he has actively participated in scholarly collaborations, contributing to scientific discussions involving cosmological constraints, observational datasets, and astrophysical modeling. His research activities demonstrate proficiency in statistical tools, including MCMC methods, which are widely applied in modern cosmological investigations. Furthermore, Dr. Dhankar has explored practical technological implementations through machine learning-based agricultural prediction systems, showcasing multidimensional professional capabilities. His academic profile includes 40 published documents and collaborations with numerous co-authors, reflecting strong engagement within the research community. Through consistent publication efforts, conference participation, and interdisciplinary contributions, he has developed an impressive professional portfolio that combines theoretical expertise, computational proficiency, and innovative research thinking in both physical sciences and applied technological domains.

Research Interest

Dr. Praveen Kumar Dhankar focuses his research on modern cosmology, modified gravity theories, observational astrophysics, and computational modeling. His scientific interests particularly emphasize f(G) gravity, Gauss–Bonnet gravity, dark energy models, and cosmological parameter estimation using advanced statistical techniques. He actively investigates the compatibility of theoretical cosmological models with observational datasets such as DESI BAO measurements and multi-fluid cosmological systems. His research demonstrates a strong commitment to understanding the accelerated expansion of the universe and alternative explanations beyond conventional cosmological frameworks. Additionally, Dr. Dhankar explores interdisciplinary applications involving machine learning and predictive analytics, especially within precision agriculture and intelligent recommendation systems. His work combines theoretical formulation, numerical simulation, and data-driven interpretation to address complex scientific challenges. With 40 research documents, 78 citations, and an h-index of 5, his evolving research profile reflects growing influence in cosmology and computational science while highlighting his dedication to advancing innovative, interdisciplinary, and evidence-based scientific investigations.

Award and Honor

Dr. Praveen Kumar Dhankar has earned growing academic recognition through his impactful scientific publications, collaborative research contributions, and consistent scholarly productivity. His Scopus-indexed profile demonstrates notable research visibility with 40 published documents, 78 citations received from 55 documents, and an h-index of 5, reflecting meaningful influence within the scientific community. His publications in reputed journals such as Physics of the Dark Universe and European Physical Journal C signify professional acknowledgment of his research quality and scientific relevance. Dr. Dhankar’s contributions to modified gravity theories, cosmological modeling, and machine learning applications have strengthened his academic reputation among interdisciplinary researchers. His collaborations with numerous co-authors and participation in contemporary research initiatives further highlight his professional credibility. Although his career continues to evolve, the measurable impact of his publications and research activities positions him as a promising scholar deserving recognition for scientific excellence, innovative thinking, and dedication toward advancing modern theoretical and computational research methodologies.

Conclusion

Dr. Praveen Kumar Dhankar represents a promising and dedicated researcher whose academic journey reflects strong commitment to scientific advancement, interdisciplinary innovation, and scholarly excellence. His educational background, professional experience, and focused research contributions have enabled him to build a meaningful presence within cosmology, theoretical physics, and computational applications. With 40 research documents, 78 citations, and an h-index of 5, he has demonstrated measurable research impact and growing recognition within international scientific communities. His investigations in modified gravity theories, observational cosmology, and machine learning applications illustrate both analytical depth and practical research versatility. Through continuous publication efforts, collaborative engagements, and innovative scientific exploration, Dr. Dhankar continues to strengthen his academic reputation and future research potential. His dedication to advancing knowledge, solving complex scientific challenges, and integrating computational methodologies into interdisciplinary studies establishes him as a valuable contributor to contemporary scientific research and an emerging leader in modern theoretical and applied sciences.

Publications Top Notes

Title: Interaction of divergence-free deceleration parameter in Weyl-type f (Q, T) gravity
Authors: GN Gadbail, S Arora, P Kumar, PK Sahoo
Year: 2022
Citation: 25

Title: Modified Chaplygin gas with bulk viscous cosmology in FRW (2+ 1)-dimensional spacetime
Authors: GS Khadekar, P Kumar, S Islam
Year: 2019
Citation: 12

Title: Quantum-enhanced AI robotics for sustainable agriculture: Pioneering autonomous systems in precision farming
Authors: P Khobragade, PK Dhankar, A Titarmare, M Dhone, S Thakur, P Saraf
Year: 2024
Citation: 10

Title: Advancing Oncology Outcomes: Deploying Advanced Machine Learning Models for Early Detection and Optimized Treatment
Authors: P Khobragade, PK Dhankar, M Motghare, A Golghate, N Rakesh
Year: 2024
Citation: 10

Title: (2+ 1) dimensional cosmological models in f (R, T) gravity with (R, T)
Authors: S Islam, P Kumar, GS Khadekar, TK Das
Year: 2019
Citation: 10

Bernard Twarog | Interactions and Fields | Research Excellence Award

Dr. Bernard Twarog | Interactions and Fields | Research Excellence Award

Associate Professor | Cracow University of Technology | Poland

Dr. Bernard Twarog is a researcher contributing to applied science and engineering fields through analytical and collaborative studies. His research interests focus on problem-solving methodologies and scientific investigation. He possesses skills in data analysis, technical writing, and interdisciplinary research. According to Scopus, he has 7 documents, 15 citations, and an h-index of 2. While no specific awards are listed, his steady publication record reflects growing academic impact. Overall, his profile shows consistent contributions and promising potential for future research advancement.

 

Citation Metrics (Scopus)

15
12
8
4
0

Citations

15

Documents

7

h-index

2

Citations

Documents

h-index

View Scopus Profile View ORCID Profile View Google Scholar Profile

Featured Publications

 

Askhat Diveev | Computational Methods | Excellence in Research

Prof. Askhat Diveev | Computational Methods | Excellence in Research 

Prof. Askhat Diveev, Federal research center Computer Science and Control of RAS,  Russia

Prof. Askhat Diveev is a renowned computational scientist and expert in control systems and machine learning methods. Based at the Federal Research Center for Computer Science and Control of RAS, he has authored over 400 scientific publications and mentored multiple scholars in their academic journeys. His innovative contributions to numerical methods, genetic programming, and traffic flow modeling have earned him international recognition. His dedication to advancing computational sciences continues to inspire the global research community.

PROFILE

Orcid  Profile

Educational Detail

Prof. Askhat Diveev has a distinguished academic foundation in computational science and numerical methods. He has mentored numerous scholars, successfully guiding eight candidates of sciences and one doctor of sciences.

Professional Experience

Prof. Diveev is a leading researcher at the Federal Research Center for Computer Science and Control, Russian Academy of Sciences (RAS). With over 400 published scientific papers and 148 indexed in Scopus, he holds a Hirsch index of 14 in Scopus and 9 in WoS. His expertise lies in the development of advanced numerical methods and machine learning techniques, which have been applied to various fields, including traffic flow modeling and control systems. Additionally, he has authored a book (ISBN: 978-3-030-83213-1) and holds significant contributions to applied mathematics and computer science.

Research Interests

Prof. Diveev’s research focuses on numerical methods for control problems, symbolic regression, genetic programming, and mathematical modeling. His groundbreaking work includes:

Developing a numerical method for general control synthesis using symbolic regression in machine learning.

Innovating the principle of small variations of the basis solution for mathematical expressions in non-numerical spaces.

Advancing variation genetic programming methodologies, including Cartesian and binary genetic programming.

Creating a recurrent, finite-difference mathematical model for urban traffic light control systems.

Top Notable Publications

1. Solving the Control Synthesis Problem Through Supervised Machine Learning of Symbolic Regression

Authors: A. Diveev et al.

Year: 2024 (November)

DOI: 10.3390/math12223595

Citations: Citation details currently unavailable; updates depend on indexing databases like Scopus or WoS.

2. Advanced Model with a Trajectory Tracking Stabilisation System and Feasible Solution of the Optimal Control Problem

Authors: A. Diveev et al.

Year: 2024 (October)

DOI: 10.3390/math12203193

Citations: Citation details currently unavailable.

3. A Stabilisation System Synthesis for Motion along a Preset Trajectory and Its Solution by Symbolic Regression

Authors: A. Diveev et al.

Year: 2024 (February)

DOI: 10.3390/math12050706

Citations: Citation details currently unavailable.

4. Adaptive Synthesized Control for Solving the Optimal Control Problem

Authors: A. Diveev et al.

Year: 2023 (September)

DOI: 10.3390/math11194035

Citations: Citation details currently unavailable.

5. Universal Stabilisation System for Control Object Motion along the Optimal Trajectory

Authors: A. Diveev et al.

Year: 2023 (August)

DOI: 10.3390/math11163556

Citations: Citation details currently unavailable.

6. Reinforcement Learning for Solving Control Problems in Robotics

Authors: A. Diveev et al.

Year: 2023 (June)

DOI: 10.3390/engproc2023033029

Citations: Citation details currently unavailable.

7. Stabilization of Movement along an Optimal Trajectory and Its Solution

Authors: A. Diveev et al.

Year: 2023 (June)

DOI: 10.3390/engproc2023033012

Citations: Citation details currently unavailable.

8. Additional Requirement in the Formulation of the Optimal Control Problem for Applied Technical Systems

Authors: A. Diveev et al.

Year: 2023 (May)

DOI: 10.3390/engproc2023033007

Citations: Citation details currently unavailable.

Conclusion 

Based on his extensive academic and professional background, impactful research innovations, high citation metrics, and substantial contributions to theoretical and applied sciences, Prof. Askhat Diveev is highly suitable for the Excellence in Research recognition. His work exemplifies the qualities of a leader in the research community, combining innovation, mentorship, and practical applications.