Mohammad Sadegh Taskhiri | Data Science | Most Cited Researcher Award

Most Cited Researcher Award

Mohammad Sadegh Taskhiri
Affiliation La Trobe University
Country Australia
Scopus ID 36683248800
Documents 34
Citations 776
h-index 15
Subject Area Data Science
Event The Scientist Global Awards
ORCID 0000-0002-9871-361X

Mohammad Sadegh Taskhiri
La Trobe University

The Most Cited Researcher Award recognizes researchers whose scholarly publications have demonstrated sustained academic influence through citation performance, research quality, interdisciplinary collaboration, and contributions to advancing scientific knowledge. Mohammad Sadegh Taskhiri of La Trobe University has established an active research profile in the field of Data Science, contributing to computational methodologies, intelligent data analysis, and applied research with measurable scholarly impact. His publication record, citation metrics, and international visibility collectively reflect continued engagement with globally relevant scientific challenges.[1]

Abstract

Citation performance represents one of the internationally recognized indicators of scholarly influence and research dissemination. The Most Cited Researcher Award highlights sustained scientific contributions that have achieved broad visibility within the academic community. Mohammad Sadegh Taskhiri’s research portfolio demonstrates engagement in Data Science through computational intelligence, machine learning applications, data analytics, and interdisciplinary research collaborations. His publication metrics, including 34 indexed documents, 776 citations, and an h-index of 15, indicate consistent academic recognition across the scientific literature.[1]

Keywords

Data Science, Machine Learning, Artificial Intelligence,Computational Intelligence,Data Analytics, Scientific Impact, Research Metrics, Citation Analysis

Introduction

Modern Data Science combines statistics, artificial intelligence, optimization, computational modeling, and domain expertise to address complex scientific and industrial problems. Researchers working in this field contribute to evidence-based decision making, predictive analytics, intelligent automation, and digital transformation. Recognition through citation-based awards acknowledges research that has achieved measurable academic visibility while supporting continued scientific advancement.[2]

Research Profile

Mohammad Sadegh Taskhiri is affiliated with La Trobe University, Australia. His scholarly activities encompass Data Science, intelligent computational systems, analytical modeling, and interdisciplinary applications of machine learning. Through peer-reviewed publications and collaborative research, his work contributes to expanding scientific understanding while supporting practical applications across multiple sectors. Bibliometric indicators available through Scopus demonstrate an established international research presence.[1]

Research Contributions

Development of computational approaches for data-driven scientific investigations. Application of machine learning methodologies to complex analytical problems. Promotion of interdisciplinary collaboration integrating data analytics with applied sciences. Contribution to peer-reviewed literature supporting reproducible and evidence-based research. Advancement of intelligent data processing techniques for practical research applications.

Publications

The researcher’s scholarly portfolio includes 34 Scopus-indexed publications covering topics within Data Science and related computational disciplines. The published work has accumulated significant citation activity, reflecting continued utilization by researchers across multiple scientific domains. Representative publications are indexed through major academic databases and include articles with DOI registration supporting long-term scholarly accessibility.[3]

Research Impact

Research impact is evaluated through publication quality, citation performance, scholarly visibility, and influence on subsequent investigations. Citation metrics associated with Mohammad Sadegh Taskhiri indicate sustained engagement by the international research community. These quantitative indicators complement qualitative contributions including interdisciplinary collaboration, scientific dissemination, and advancement of analytical methodologies within Data Science.[1]

Award Suitability

The Most Cited Researcher Award recognizes measurable scholarly influence supported by objective bibliometric evidence. Based on the documented publication record, citation count, h-index, and active contribution to Data Science research, Mohammad Sadegh Taskhiri demonstrates characteristics aligned with citation-based academic recognition. Evaluation for this award may additionally consider research quality, scientific integrity, international collaboration, and continuing impact on the broader research community.[1]

Conclusion

The scholarly profile presented here summarizes the documented academic achievements of Mohammad Sadegh Taskhiri within the field of Data Science. Bibliometric indicators, peer-reviewed publications, and research visibility collectively illustrate continued participation in international scientific research. Recognition through the Most Cited Researcher Award reflects objective academic performance while encouraging ongoing excellence in research, innovation, and knowledge dissemination.[2]

References

  1. Elsevier (2026). Scopus author details: Mohammad Sadegh Taskhiri, Author ID 36683248800. Scopus.
    https://www.scopus.com/pages/authors/36683248800
  2. The role of agricultural biomass in supply chain decarbonization.
    https://doi.org/10.1007/s10479-024-05979-6
  3. Crossref (2026). Economic impact of recycled and bioplastic packaging production in Australia – A Monte Carlo simulation model.
    https://doi.org/10.1016/j.procs.2021.01.001

Imtiaz Ahmad | Mathematical Sciences | Research Excellence Award

Prof. Dr. Imtiaz Ahmad | Mathematical Sciences | Research Excellence Award

Professor | University of Malakand | Pakistan

Dr. Imtiaz Ahmad is a distinguished researcher in the field of mathematics, with a strong focus on algebraic structures, graph theory, and mathematical modeling. His scholarly contributions encompass Abel-Grassmann’s groupoids, semigroups, fuzzy algebra, and the application of mathematical models to epidemiological dynamics. He has demonstrated consistent research productivity with 39 documents, accumulating over 380 citations and achieving an h-index of 10, reflecting the academic impact and relevance of his work within the global research community. His publications span reputable international journals, covering both theoretical advancements and applied mathematical modeling, particularly in infectious disease dynamics such as COVID-19, Ebola, and hepatitis. His research integrates abstract algebra with real-world problem-solving, contributing to interdisciplinary knowledge. Prof. Ahmad’s work continues to support the advancement of mathematical sciences through analytical rigor, innovation, and sustained scholarly engagement.

Citation Metrics (Scopus)

 

400

300

200

100

0

 

380
 
Citations

39
 
Documents

10
 
h-index

 

Citations

 

Documents

 

h-index

Featured Publications

 

 

 

Ideals in CA-AG-Groupoids

Indian Journal of Pure and Applied Mathematics, 2018

 

Normal Bipolar Soft Subgroups

Fuzzy Information and Engineering, 2021

Julio Chagas | Computational Chemistry | Best Scholar Award

Dr. Julio Chagas | Computational Chemistry | Best Scholar Award 

Postdoctoral Scholar | Northwestern University | United States

Dr. Julio Cesar Verli Chagas is an emerging scholar in theoretical and computational chemistry whose research advances the understanding of molecular electronic structure, excited-state dynamics, and frontier spectroscopic phenomena. His academic influence continues to grow, with 8 peer-reviewed journal publications, 7 completed or ongoing research projects, and a citation impact reflected by 26 citations, an h-index of 3, and additional Scopus metrics indicating 19 citations across 14 documents. His work centers on multireference quantum chemistry methods, enabling accurate modeling of electronically complex systems and contributing to improved predictive capabilities in chemical physics. Chagas has notably elucidated excited-state manifolds in conjugated and photoactive molecules, providing insights that support the development of advanced optical materials and next-generation photonic applications. His research portfolio integrates high-level theory with cutting-edge experimentation, particularly through investigations of molecular optical responses and entangled-photon spectroscopy—an emerging direction that strengthens the interface between quantum chemistry and quantum optics. International collaborations have been central to his scientific contributions, including work with Prof. Hans Lischka on excited-state computational methodologies and Prof. George Schatz on optical and nonlinear spectroscopic modeling, enhancing the interdisciplinary reach and global relevance of his research. He has presented at over 25 scientific conferences and actively contributes to collaborative scientific initiatives in the United States, Brazil, and Europe. Through rigorous modeling, innovative methodological development, and cross-disciplinary research, Chagas’ work provides foundational insights with potential societal impact in areas such as photonic materials, spectroscopy-driven chemical sensing, and quantum-enhanced measurement technologies. His growing scholarly footprint reflects a trajectory of continued excellence and expanding international recognition.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Milanez, B. D., Chagas, J. C. V., Pinheiro Jr, M., Aquino, A. J. A., & Lischka, H. (2020). Effects on the aromaticity and on the biradicaloid nature of acenes by the inclusion of a cyclobutadiene linkage. Theoretical Chemistry Accounts, 139(7), 113. Citations: 7

  2. Dos Santos, L. G. F., Chagas, J. C. V., Ferrão, L. F. A., Aquino, A. J. A., Nieman, R., & Lischka, H. (2025). Tuning aromaticity, stability and radicaloid character of periacenes by chemical BN doping. Journal of Computational Chemistry, 46(3), e70039. Citations: 5

  3. Chagas, J. C. V., Milanez, B. D., Oliveira, V. P., Pinheiro Jr, M., Ferrão, L. F. A., & Aquino, A. J. A. (2024). A multi-descriptor analysis of substituent effects on the structure and aromaticity of benzene derivatives: π-conjugation versus charge effects. Journal of Computational Chemistry, 45(12), 863–877. Citations: 4

  4. Plasser, F., Lischka, H., Shepard, R., Szalay, P. G., Pitzer, R. M., Alves, R. L. R., Chagas, J. C. V., … (2025). COLUMBUS─An efficient and general program package for ground and excited state computations including spin–orbit couplings and dynamics. The Journal of Physical Chemistry A, 129(28), 6482–6517. Citations: 2

  5. Pimentel, J. V. M., Chagas, J. C. V., Pinheiro Jr, M., Aquino, A. J. A., & Lischka, H. (2025). Thermally activated delayed fluorescence in B, N-substituted tetracene derivatives: A theoretical pathway to enhanced OLED materials. The Journal of Physical Chemistry A, 129(2), 470–480. Citations: 2