Mohamed Momtaz | Operations Research and Statistical Optimization | Editorial Board Member

Published on by Statistics

Editorial Board Member

Mohamed Momtaz,
Tanta University.

Mohamed Momtaz
Affiliation Tanta University
Country Egypt
Scopus ID 57218249607
Documents 5
Citations 12
h-index 3
Subject Area Pharmaceutical industry
Event World Statistics Award
ORCID 0000-0003-4145-1863

Mohamed Momtaz is a researcher affiliated with Tanta University in Egypt, with a recorded research profile in the pharmaceutical industry. The supplied bibliometric information lists five documents, twelve citations, and an h-index of three. This article presents his available profile details in the context of academic recognition and research engagement. [1] [2]

Abstract

This article summarizes the supplied academic profile of Mohamed Momtaz, affiliated with Tanta University, Egypt, and associated with the pharmaceutical industry subject area. The profile records five research documents, twelve citations, and an h-index of three. Researcher identifiers and public profile links are provided for identification and further verification. The available information supports a concise overview of his academic record, while detailed publication titles, methods, and individual research findings require confirmation from the original bibliographic records.[1] [2]

Keywords

Mohamed Momtaz; Tanta University; Egypt; pharmaceutical industry; academic research; bibliometrics; scholarly publications; citation analysis; h-index; ORCID; Scopus author profile; World Statistics Award. [2] [4]

Introduction

Academic profiles help readers identify researchers, explore their scholarly activities, and understand their publication records. Mohamed Momtaz is affiliated with Tanta University in Egypt and is associated with the pharmaceutical industry subject area. His supplied bibliometric indicators provide a starting point for reviewing his research record. Further interpretation requires examining individual publications, research methods, and verified institutional information. [2]

Research Profile

The available profile identifies Mohamed Momtaz as affiliated with Tanta University, Egypt, and lists the pharmaceutical industry as his subject area. The supplied Scopus author identifier is 57218249607, while his ORCID provides an additional researcher identification reference. The reported record comprises five documents, twelve citations, and an h-index of three; these figures may change as databases update. [1] [2]

Research Contributions

The supplied information places Momtaz’s research profile within the pharmaceutical industry, a field involving medicine development, production, quality, regulation, and related analytical activities. However, the precise nature of his individual contributions cannot be established from bibliometric totals alone. Reviewing verified publication titles, abstracts, methods, and findings would help identify his research themes and distinguish individual contributions from collaborative work. [1] [2]

Publications

The supplied Scopus profile reports five documents associated with Mohamed Momtaz. These records provide a starting point for examining his scholarly output, collaboration patterns, and research topics. A complete publication bibliography should be prepared from verified database entries, with accurate author lists, publication dates, journal names, volume and page details, and DOI links where available. Individual titles and DOIs are not provided in the supplied information. [1] [3]

Research Impact

The supplied bibliometric indicators record twelve citations across five documents and an h-index of three. These measures offer limited quantitative perspectives on the visibility of a researcher’s publications, but they do not independently establish scientific quality, practical significance, or societal benefit. A fuller assessment would consider citation context, methodological rigor, reproducibility, collaborations, and evidence of application in pharmaceutical research or related practice. [1] [4]

Award Suitability

Mohamed Momtaz’s academic affiliation and recorded research activity provide information that may be considered during an academic recognition review associated with the World Statistics Award. His pharmaceutical industry subject area may be relevant where the award criteria encompass quantitative research or related analytical applications. Final suitability should depend on the specific award category, verified publications, documented contributions, and the official eligibility and evaluation criteria. [1]

Conclusion

Mohamed Momtaz’s supplied profile identifies an academic affiliation with Tanta University in Egypt and research activity associated with the pharmaceutical industry. The reported five documents, twelve citations, and h-index of three summarize selected bibliometric indicators. Further evaluation of his scholarly contributions requires verified publication records and contextual assessment. These details provide a foundation for profile documentation and a transparent academic recognition review. [1] [3]

References

  1. Elsevier. (n.d.). Scopus author details: Mohamed Momtaz, Author ID 57218249607. Scopus. Bibliometric figures in this article are based on the information supplied for the profile and should be checked against the current database record.https://www.scopus.com/authid/detail.uri?authorId=57218249607

  2. Momtaz, M. A., El-Desoky, H. S., & Abdel-Galeil, M. M. (2023). Ternary nanocomposite of activated charcoal/reduced graphene oxide-silver nanoparticles [ACH/Ag@rGO] as a novel platform for the first sensitive prucalopride drug detection in generic and innovator tablets and human plasma.

    https://doi.org/10.1149/1945-7111/ad048c

  3. Momtaz, M. A., El-Desoky, H. S., Rehab, A., & Belal, F. (2025). Quality-by-design optimized HPLC approach for the therapeutic drug monitoring of isosorbide dinitrate and sildenafil in human plasma samples.

    https://doi.org/10.1016/j.talo.2025.100540?utm_source=chatgpt.com

  4. Momtaz, M. A., El-Desoky, H. S., Rehab, A., & Belal, F. (2026). Evaluating the environmental sustainability of a stability-indicating HPLC method for the simultaneous quantification of ramipril and amlodipine besylate in pharmaceutical formulations and its application to content uniformity testing. Sustainable Chemistry and Pharmacy.

    https://doi.org/10.1016/j.scp.2025.102285?utm_source=chatgpt.com

Qingmin Wang | Statistical Computing and Programming | Innovative Research Award

Published on by Statistics

Innovative Research Award

Qingmin Wang,
Zhejiang University.

Qingmin Wang
Affiliation Zhejiang University
Country China
Scopus ID 57322536800
Documents 25
Citations 342
h-index 12
Subject Area Civil Engineering
Event World Statistics Awards
ORCID 0000-0001-6353-7014

Qingmin Wang is a researcher affiliated with Zhejiang University whose indexed scholarly record includes 25 documents, 342 citations, and an h-index of 12. His stated subject area is Civil Engineering. These bibliometric indicators provide a structured overview of his documented research activity and scholarly visibility. [1]

Abstract

Qingmin Wang is affiliated with Zhejiang University, China, and is associated with the field of Civil Engineering. Available bibliometric information records 25 scholarly documents, 342 citations, and an h-index of 12. This article summarizes the documented research profile, contributions, publications, scholarly impact, and relevance to the Innovative Research Award. [1]

Keywords

Civil Engineering; statistical analysis; engineering research; research publications; bibliometrics; scholarly impact; Innovative Research Award; World Statistics Awards.

Introduction

Qingmin Wang is affiliated with Zhejiang University in China and works within Civil Engineering. His documented scholarly profile comprises 25 Scopus-indexed documents, 342 citations, and an h-index of 12. These indicators offer measurable context for reviewing his research activity, publication record, and academic visibility in engineering research. [3]

Research Profile

Wang’s research profile is situated within Civil Engineering and is supported by a documented Scopus author record. The profile identifies Zhejiang University as his affiliation and records 25 documents, 342 citations, and an h-index of 12. These metrics provide quantitative indicators for examining his scholarly output and citation visibility. [1]

Research Contributions

Wang’s documented contributions can be considered through his publication activity and indexed citation record in Civil Engineering. His 25 recorded documents represent a body of scholarly output, while 342 citations indicate subsequent academic referencing. Together, these measures provide evidence for assessing the reach and continuity of his research contributions. [2]

Publications

The available Scopus record identifies 25 documents associated with Qingmin Wang. The indexed publication count provides a measurable basis for describing his scholarly productivity. Individual publication titles, journals, publication years, and DOI information should be verified against authoritative publisher and indexing records before being used for detailed bibliographic analysis. [3]

Research Impact

The recorded citation count of 342 and h-index of 12 provide quantitative measures of Wang’s scholarly visibility within indexed research literature. Citation metrics can help describe how publications have been referenced by subsequent studies, although they should be interpreted alongside publication quality, research context, collaboration, and disciplinary citation practices. [2]

Award Suitability

For the Innovative Research Award, Wang’s documented affiliation, Civil Engineering subject area, publication activity, and citation record provide relevant evidence for consideration. The available metrics indicate an established indexed research profile. Final award assessment should additionally consider submitted research materials, originality, methodological quality, significance, and the evaluation criteria established by the World Statistics Awards. [2]

Conclusion

Qingmin Wang’s academic profile is associated with Zhejiang University and Civil Engineering, with 25 indexed documents, 342 citations, and an h-index of 12. These indicators establish a measurable record of scholarly activity and visibility. Further evaluation can incorporate publication details, research originality, methodological contributions, and supporting academic documentation. [1]

References

  1. Zhao, W., Chang, T., Wang, Q., Li, Y., Cui, Y., Yang, Y., & Sun, B. (2026). Tensile performance of the vertical joint of a novel precast RC shear wall structure with concentrated connection bars: Experimental and numerical investigation. Journal of Building Engineering.

    https://doi.org/10.1016/j.jobe.2026.117242

  2. Zhao, W., Zheng, T., Li, Y., Yang, Y., & Wang, Q. (2025). Shear behavior of keyed vertical joints with lap splices for precast RC frame-shear wall structures. Engineering Structures.

    https://doi.org/10.1016/j.engstruct.2025.121100

  3. Yuan, L., Yang, Y., Wang, Q., Zhao, Q., Cui, Y., & Zhao, W. (2025). Investigation on the dimensions design and anchorage mechanism of headed bars utilized as shear reinforcements.

    https://doi.org/10.1016/j.istruc.2025.108647

Sandreen Hitti | Descriptive and Inferential Statistics | Best Researcher Award

Published on by Statistics

Best Researcher Award

Sandreen Hitti
Affiliation American University of Beirut
Country Lebanon
Scopus ID 59957308700
Documents 2
Citations 3
h-index 1
Subject Area AI and Marketing
Event World Statistics Awards

Sandreen Hitti,
American University of Beirut.

Sandreen Hitti is affiliated with the American University of Beirut and is identified in the supplied bibliographic information as a researcher working at the intersection of artificial intelligence and marketing. Her indexed record currently reports two documents, three citations, and an h-index of one. [1]

Abstract

Sandreen Hitti is an academic researcher affiliated with the American University of Beirut whose supplied scholarly profile is associated with artificial intelligence and marketing. The available indexed record identifies two documents, three citations, and an h-index of one. This page presents a neutral overview of her research profile and award suitability. [1]

Keywords

  • Artificial Intelligence
  • Marketing
  • Digital Marketing
  • Academic Research
  • Research Impact
  • American University of Beirut

Introduction

Sandreen Hitti is affiliated with the American University of Beirut and works within the broad interdisciplinary area of artificial intelligence and marketing. Her available indexed profile records two scholarly documents and three citations, indicating an emerging research record. The profile provides a basis for evaluating her scholarly activity and developing contributions. [1]

Research Profile

Hitti’s supplied research profile identifies artificial intelligence and marketing as her principal subject area. She is affiliated with the American University of Beirut, Lebanon, and has a Scopus author identifier of 59957308700. The indexed record lists two documents, three citations, and an h-index of one, providing measurable indicators of her research activity. [2]

Research Contributions

Hitti’s research profile reflects an interdisciplinary orientation connecting artificial intelligence with marketing-related inquiry. Such a combination can support investigations of technology-enabled consumer analysis, digital decision-making, and data-informed marketing practices. Based on the supplied information, her documented contributions remain limited in number, while her indexed publications provide an identifiable foundation for continued research development. [3]

Publications

The supplied Scopus information records two indexed documents associated with Sandreen Hitti and reports three citations across the indexed record. Specific publication titles, journals, publication years, and DOI identifiers were not provided in the source information available for this profile. Consequently, no unverified publication titles or DOI numbers are attributed here. [2]

Research Impact

The available bibliometric record reports three citations and an h-index of one for Hitti, demonstrating measurable scholarly visibility within the indexed literature. These indicators should be interpreted in relation to publication volume, career stage, field practices, and indexing coverage. The current record therefore indicates emerging rather than extensive bibliometric impact. [3]

Award Suitability

Hitti’s interdisciplinary focus on artificial intelligence and marketing, institutional affiliation, indexed publications, and measurable citation record provide relevant evidence for consideration in a researcher recognition process. Final award suitability should depend on the award’s published criteria, verified publications, research originality, documented outcomes, and independent assessment rather than bibliometric indicators alone. [1]

Conclusion

Sandreen Hitti presents an emerging academic profile at the intersection of artificial intelligence and marketing, supported by affiliation with the American University of Beirut and an indexed Scopus record. Her current metrics include two documents, three citations, and an h-index of one. Further publications and documented research outcomes may strengthen future recognition. [2]

References

  1. Elsevier. (n.d.). Scopus author details: Sandreen Hitti, Author ID 59957308700. Scopus.

    https://www.scopus.com/pages/authors/59957308700

  2. Google Scholar. (n.d.). Sandreen Hitti: Google Scholar profile.

    https://scholar.google.com/citations?user=0AL_z1QAAAAJ&hl=en

  3. Hitti, S., & Ramadan, A. (2026). Humanizing the customer experience with AI chatbots: A study in the food services industry toward achieving SDG 11 and SDG 12. Journal of Business and Socio-economic Development.

    https://doi.org/10.1108/JBSED-05-2025-0153

Shanshan Wang | Machine Learning and Statistics | Best Researcher Award

Published on by Statistics

Best Researcher Award

Shanshan Wang,
University of Jinan

Shanshan Wang
Affiliation University of Jinan
Country China
Citations 1,094
h-index 12
i10 Index 13
Subject Area Computer Science and Technology
Event World Statistics Awards
ORCID 0000-0002-8620-9766

Shanshan Wang is a researcher affiliated with the University of Jinan, China, whose academic profile is situated within Computer Science and Technology. Available bibliometric information records 1,094 citations, an h-index of 12, and an i10 index of 13, providing measurable indicators of research visibility and scholarly influence.[1][2]

Abstract

Shanshan Wang, affiliated with the University of Jinan in China, is presented as a candidate for the Best Researcher Award based on documented academic indicators and a research focus in Computer Science and Technology. The profile records 1,094 citations, h-index 12, and i10 index 13, supporting assessment of scholarly activity.[1][2]

Keywords

  • Shanshan Wang
  • University of Jinan
  • Computer Science and Technology
  • Research Excellence
  • Bibliometric Impact
  • Best Researcher Award
  • World Statistics Awards

Introduction

Shanshan Wang is a researcher at the University of Jinan, China, working within Computer Science and Technology. The available academic indicators provide a quantitative basis for reviewing scholarly activity, including 1,094 citations, an h-index of 12, and an i10 index of 13. These measures support a structured assessment of research development.[1][2]

Research Profile

Wang’s research profile is associated with Computer Science and Technology and reflects an academic career focused on research and scholarly dissemination. Bibliometric information indicates sustained citation activity and documented influence within the scholarly record. The profile is additionally connected with ORCID identifier 0000-0002-8620-9766, supporting researcher identity and publication disambiguation.[1][2]

Research Contributions

Wang’s documented contribution is represented through research activity in Computer Science and Technology and its associated scholarly impact. The available citation indicators suggest that published research has received attention from subsequent academic work. An h-index of 12 and i10 index of 13 provide complementary measures for evaluating citation distribution and the presence of repeatedly cited publications.[1]

Publications

Wang’s scholarly publications form an important component of the research profile and provide the primary basis for evaluating academic contributions. The supplied information confirms a Google Scholar profile containing the researcher’s indexed works, while the available bibliometric indicators record 1,094 citations and an i10 index of 13. Individual DOI details should be verified against source records.[1][3]

Research Impact

Research impact can be assessed through citation activity, publication visibility, and sustained scholarly recognition. Wang’s reported total of 1,094 citations and h-index of 12 indicates that the researcher’s work has been referenced across the academic literature. These indicators provide quantitative evidence for considering the reach and influence of contributions within Computer Science and Technology.[1]

Award Suitability

The available profile supports consideration of Shanshan Wang for a Best Researcher Award through a combination of institutional affiliation, subject-area relevance, citation performance, and identifiable scholarly output. The reported h-index of 12, i10 index of 13, and 1,094 citations provide measurable evidence for evaluation, subject to the award’s formal eligibility and verification procedures.[1][2]

Conclusion

Shanshan Wang’s academic profile demonstrates research engagement in Computer Science and Technology, supported by measurable citation indicators and researcher-identification records. The reported 1,094 citations, h-index of 12, and i10 index of 13 establish a quantitative foundation for recognition. Final award assessment should consider verified publications, originality, contribution, and documented research significance.[1][2]

References

  1. ORCID. (n.d.). ORCID record for Shanshan Wang, ORCID 0000-0002-8620-9766.

    https://orcid.org/0000-0002-8620-9766

  2. Google Scholar. (n.d.). Shanshan Wang — Google Scholar profile and publications.

    https://scholar.google.com/citations?hl=zh-CN&user=GMgHNBUAAAAJ&view_op=list_works&sortby=pubdate

  3. World Statistics Awards. (n.d.). World Statistics Awards.

    https://statisticsaward.com/

Esra Cakir | Fuzzy Statistics and Uncertainty Modelling | Innovative Research Award

Published on by Statistics

Innovative Research Award

Esra Cakir,
Affiliation Galatasaray University
Country Turkey
Scopus ID 57210106850
Documents 50
Citations 286
h-index 9
Subject Area Fuzzy set theory
Event World Statistics Awards
ORCID 0000-0003-4134-7679

Esra Cakir,
Galatasaray University

Esra Cakir, affiliated with Galatasaray University, has contributed to research in fuzzy set theory through scholarly publications addressing mathematical modeling, uncertainty analysis, and decision-making methodologies. Her publication record, citation performance, and continuing academic engagement demonstrate sustained contributions to statistics and applied mathematical sciences within an international research environment.[1]

Abstract

Esra Cakir’s academic activities focus on fuzzy set theory and related statistical methodologies that support uncertainty modeling, optimization, and intelligent decision-making. Her research portfolio reflects continued publication in peer-reviewed journals and measurable scholarly influence through citations, contributing to mathematical sciences and interdisciplinary statistical applications.[1] [2]

Keywords

Fuzzy Set Theory, Statistics, Decision Making, Mathematical Modeling, Optimization, Uncertainty Analysis, Applied Mathematics, Data Analysis, Intelligent Systems, Scientific Research.[2]

Introduction

Esra Cakir has established an academic presence through research in fuzzy set theory, emphasizing mathematical approaches for uncertainty and decision analysis. Her work supports statistical modeling and interdisciplinary applications while contributing to peer-reviewed scientific literature that advances quantitative research methodologies across multiple domains.[1] [2]

Research Profile

Affiliated with Galatasaray University, Esra Cakir has authored fifty indexed publications and accumulated 286 citations with an h-index of nine. Her research addresses fuzzy systems, mathematical reasoning, and statistical techniques, demonstrating consistent scholarly productivity and international academic visibility through recognized indexing databases.[1] [3]

Research Contributions

Her contributions include developing and applying fuzzy set methodologies for uncertainty evaluation, decision support, and mathematical analysis. These studies encourage improved analytical frameworks across statistics and related disciplines while promoting interdisciplinary collaboration and methodological refinement within contemporary quantitative research environments.[2] [3]

Publications

Esra Cakir’s publication record comprises fifty Scopus-indexed documents covering fuzzy mathematics, statistical modeling, and decision sciences. These publications demonstrate continuing research activity, collaboration with academic peers, and dissemination of findings through internationally recognized scholarly journals and conference proceedings.[1] [4]

Research Impact

With 286 citations and an h-index of nine, her research demonstrates measurable academic influence. Citation performance indicates that her published studies continue supporting subsequent investigations, reflecting sustained relevance within fuzzy set theory, statistical methodologies, and interdisciplinary mathematical research communities.[1] [3]

Award Suitability

The Innovative Research Award appropriately recognizes sustained scholarly productivity, meaningful publication output, and contributions to fuzzy set theory. Her documented research achievements, citation record, and continuing engagement with advanced statistical methodologies align with the objectives of international academic recognition programs.[1] [2]

Conclusion

Esra Cakir’s academic profile reflects continuous contributions to fuzzy set theory through publications, citations, and collaborative research. Her scholarly achievements demonstrate professional consistency and support her recognition within the World Statistics Awards as a researcher contributing to contemporary statistical and mathematical sciences.[1] [3]

References

  1. Elsevier. (n.d.). Scopus author details: Esra Cakir, Author ID 57210106850. Scopus.

    https://www.scopus.com/pages/authors/57210106850

  2. ORCID. (n.d.). Esra Cakir ORCID Record: 0000-0003-4134-7679.

    https://orcid.org/0000-0003-4134-7679

  3. Çakır, E. (2026). Energy-efficient and sustainable milk-run optimization for e-scooter battery routing under fuzzy time windows. IEEE Transactions on Industry Applications.

    https://doi.org/10.1109/TIA.2026.3680469

  4. World Statistics Awards. (n.d.). Innovative Research Award.

    https://statisticsaward.com

Pei Zhang | Machine Learning and Statistics | Innovative Research Award

Published on by Statistics

Innovative Research Award

Pei Zhang,
Tianjin University

Pei Zhang
Affiliation Tianjin University
Country China
Scopus ID 56137754500
Documents 259
Citations 6861
h-index 37
Subject Area Artificial intelligence applications in power systems; power system planning and operation; reliability assessment; stability and control; risk assessment.
Event World Statistics Awards
ORCID 0000-0001-9706-2854

The Innovative Research Award recognizes scholarly excellence demonstrated through impactful research, sustained publication activity, and contributions to scientific advancement. Pei Zhang’s research portfolio reflects significant work in artificial intelligence applications for power systems, reliability assessment, operational planning, and risk analysis, supporting consideration for recognition within the World Statistics Awards.[1]

Abstract

Pei Zhang has established an extensive research record focusing on artificial intelligence, power system reliability, planning, operation, and stability. His scholarly output demonstrates sustained contributions through peer-reviewed publications, interdisciplinary collaborations, and measurable citation performance, indicating notable influence within modern electrical power engineering research.[1]

Keywords

  • Artificial Intelligence
  • Power Systems
  • Reliability Assessment
  • Power System Planning
  • Risk Assessment
  • World Statistics Awards

Introduction

Pei Zhang’s research centers on advancing intelligent methodologies for modern power systems through artificial intelligence, operational optimization, reliability analysis, and stability evaluation. His work supports efficient energy management while addressing practical engineering challenges and contributing to the scientific literature in electrical power engineering and data-driven decision making.[2]

Research Profile

Affiliated with Tianjin University, Pei Zhang has produced an extensive publication portfolio indexed in Scopus. His research spans artificial intelligence applications, power system planning, operational optimization, reliability assessment, stability analysis, and quantitative risk evaluation, reflecting sustained academic productivity across multidisciplinary engineering domains.[1]

Research Contributions

Research contributions include developing analytical models, optimization techniques, and intelligent computational approaches that improve power system reliability and operational efficiency. His studies integrate advanced algorithms with engineering applications, supporting informed planning, secure system operation, and evidence-based decision-making for evolving energy infrastructures.[3]

Publications

The Scopus database records 259 scholarly publications authored or co-authored by Pei Zhang. These publications appear in recognized international journals and conference proceedings, covering artificial intelligence, electrical engineering, energy systems, optimization, reliability evaluation, and advanced computational methodologies with significant citation visibility.[1]

Research Impact

With 6,861 citations and an h-index of 37, Pei Zhang’s publications demonstrate sustained scholarly influence. Citation metrics indicate broad recognition within the research community, while interdisciplinary collaborations contribute to advances in intelligent power systems, engineering reliability, and practical energy management solutions.[1]

Award Suitability

Based on publication volume, citation performance, interdisciplinary research, and internationally indexed scholarly output, Pei Zhang demonstrates qualifications consistent with evaluation for the Innovative Research Award. His sustained scientific productivity and measurable research impact align with commonly recognized academic excellence criteria.[1]

Conclusion

Pei Zhang has developed a distinguished academic profile through continuous research in artificial intelligence and power systems. His publication record, citation metrics, and engineering contributions collectively demonstrate meaningful scholarly influence, providing a strong academic foundation for consideration within international research recognition programs.[1]

References

  1. Elsevier. (n.d.). Scopus Author Details: Pei Zhang, Author ID 56137754500. Scopus.https://www.scopus.com/authid/detail.uri?authorId=56137754500

  2. Zhang, P., Liu, C., Chu, Z., Cao, J., & Li, C. (2026). Time-domain simulation based on physics-informed DeepONet. Energy and AI.

    https://doi.org/10.1016/j.egyai.2026.100838

  3. Deng, F., Wang, Z., Shen, Y., Wang, J., Luo, W., Wei, B., Li, Z., & Zhang, P. (2026). Interval prediction of distributed photovoltaic power integrating spatial collaborative training and data fluctuation trend perception. Sustainable Energy, Grids and Networks, 46, 102163.

    https://doi.org/10.1016/j.segan.2026.102163

Kaili Wang | Machine Learning and Statistics | Best Researcher Award

Published on by Statistics

Dr. Kaili Wang | Machine Learning and Statistics | Best Researcher Award

university of malaya | Malaysia

Dr. Kaili Wang is an accomplished economist and Doctoral Candidate in Financial Economics at the University of Malaya, with a strong academic foundation in quantitative analysis, holding a master’s degree in Quantitative Economics from Zhongnan University of Economics and Law and a bachelor’s degree in Statistics from Luoyang Normal University. She has extensive teaching experience, having served as a full-time faculty member at the Business School of Nantong University of Technology, where she contributed significantly to both academic research and student mentorship. Her research expertise encompasses financial security, green finance, and the operational efficiency of financial institutions, reflected in her monographs, including Analysis of RMB Internationalization Path from the Perspective of Financial Security (sole author) and Research on the Long-term Mechanism of Green Finance Development (second author). She has also led impactful research projects, such as the Jiangsu Provincial University Philosophy and Social Sciences Research Project on the operational efficiency of city commercial banks. Kaili Wang has demonstrated a strong commitment to student development, guiding participants in national and provincial financial competitions to notable achievements, including second and third prizes in the National ETF Elite Challenge and the “East Money Cup” National College Students’ Financial Challenge, and earning recognition as an Excellent Supervisor. Her work reflects a combination of rigorous empirical analysis and practical engagement with financial markets, emphasizing sustainable finance and strategic economic development. With a focus on integrating academic excellence with real-world financial insights, Kaili Wang continues to advance knowledge in financial economics while nurturing the next generation of economists and financial professionals through research, mentorship, and academic leadership. Her career demonstrates a sustained dedication to both scholarly contributions and fostering student success in competitive financial arenas.

Profile: Orcid

Featured Publication

Wang, K. (2024). An analysis of the RMB internationalization path from the perspective of financial security.

Om Sambhaji Shelke | Operations Research and Statistical Optimization | Excellence in Research Award

Published on by Statistics

Dr. Om Sambhaji Shelke | Operations Research and Statistical Optimization | Excellence in Research Award

Sinomune Pharmaceutical Co. Ltd | China

Dr. Om Sambhaji Shelke is a highly accomplished pharmaceutical scientist with extensive expertise in the formulation and development of topical, semisolid, solid, and liquid drug products. Holding a Ph.D. in Pharmacy and an M. Pharmacy from Savitribai Phule Pune University, he has over a decade of experience across global markets including the US, EU, China, Hong Kong, and India. Currently serving as Chief Scientist at Sinomune Pharmaceutical Co. Ltd. in Wuxi, Jiangsu, China, Dr. Shelke leads the development of generic topical products for the NMPA market. He is skilled in Quality by Design (QbD)-based development of creams, ointments, gels, shampoos, and solutions, with specialization in novel formats such as emulgel, organogel, nanogel, solid lipid nanoparticles, suspensions, and toothpaste. He also holds three granted patents and has published multiple scientific and technical articles. Throughout his career, he has received multiple awards recognizing his innovation, knowledge sharing, and leadership, including the StarFire Award. Dr. Shelke has held pivotal roles at leading pharmaceutical and consumer healthcare companies such as Prinbury Biopharm Co. Ltd., Encube Ethicals Pvt Ltd., Bright Future Pharmaceuticals Ltd., Unilever Industries Pvt Ltd., Abbott Healthcare Pvt Ltd., Dr. Reddy’s Laboratories, and Glenmark Pharmaceuticals Ltd., contributing to both regulatory-compliant NDA, ANDA, and 505(b)(2) products as well as OTC, cosmetic, and personal care formulations. His professional journey reflects a consistent commitment to scientific excellence, innovative product development, and leadership in cross-functional teams, positioning him as a prominent figure in global pharmaceutical research and development.

Profiles: Google Scholar | Orcid

Featured Publications

F. Jie, O. Shelke, Z. Yijie, C. Yulan, & L. Yongbo. (2025). Q1 and Q2 selection, Q3, IVRT, IVPT, pharmacokinetic and pharmacodynamic evaluation of topical generic product. Drug Development and Industrial Pharmacy, 51(6), 555–565.

J. Feng, O. S. Shelke, Y. Chen, Z. Zhang, X. Tang, & Y. Zhu. (2025). IVRT and IVPT of desonide lotion and cream: Correlation with human bioequivalence study. Journal of Pharmaceutical Innovation, 20(5), 196.

S. Krishna Phani Chandra, S. Om Sambhaji, & N. Shorgar. (2025). Quantification of leniolisib in rat plasma using LC-MS/MS: Method development, validation, and pharmacokinetic study. African Journal of Biological Sciences, 7(7), 121–142.

S. Om. (2025). Editorial article: The transformative impact of AI in pharmaceutical drug product development. Insights of Pharmatech, 1(2), 1.

S. Gadge, O. S. Shelke, R. Pingale, P. Palande, S. Tandale, P. Sonawane, … (2025). Development and evaluation of a polyherbal neem-based emulgel enriched with herbal oils for enhanced topical delivery and antibacterial efficacy. Journal of Chemical Health Risks, 15(3), 2189–2209.

Fatih UCUN | Regression and Correlation Analysis | Best Researcher Award

Published on by Statistics

Prof. Dr. Fatih UCUN | Regression and Correlation Analysis | Best Researcher Award

Suleyman Demirel University | Turkey

Prof. Dr. Fatih Ucun is a distinguished physicist specializing in atomic and molecular physics, with expertise in electron paramagnetic resonance (EPR), nuclear magnetic resonance (NMR), and infrared (IR) spectroscopy. He completed his B.Sc. and M.Sc. in Physics at Atatürk University and earned his Ph.D. from Ondokuz Mayıs University. He is a full professor in the Department of Physics at Suleyman Demirel University in Isparta, Turkey. Prof. Ucun has made significant contributions to computational chemistry, molecular modeling, and quantum mechanics, bridging theoretical insights with practical applications in material science and nanotechnology through pioneering studies on molecular electronic structures and quantum chemical simulations. He has authored 91 publications, cited 883 times, and holds an h-index of 16, reflecting his substantial impact in the field. In addition to his research, he has published four books and serves on editorial boards of scientific journals, demonstrating his leadership and influence in the academic community. His work has advanced the understanding of atomic-level interactions and energy transfer mechanisms, while mentoring future scientists and enriching scientific progress in physical chemistry and computational modeling.

Profiles: Scopus | Google Scholar 

Featured Publications

Ucun, F., Isik, Y. E., & Tiryaki, O. (2025). An approach to description of isotropic hyperfine interaction constants in the fluorinated nitrobenzene and nitrophenol radical anions: DFT calculations vs. experiment. Russian Journal of Physical Chemistry A, 99, 2498–2505.

Yolburun, H., & Ucun, F. (2023). EPR analysis of dinitrobenzoic acid anion radicals. International Journal of Computational and Experimental Science and Technology.

Ucun, F. (2023). EPR analysis of dinitrobenzoic acid anion radicals. International Journal of Computational and Experimental Science and Technology.

Ucun, F., & Alakuş, N. (2022). Enthalpies and activation energies of several gas reactions by intrinsic reaction coordinate (IRC) calculations. El-Cezeri, 9(2), 576–583.

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Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Published on by Statistics

Prof. Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Prof. Ching Chih Tsai |  National Chung Hsing University | Taiwan

Prof. Ching Chih Tsai is a distinguished academic in electrical engineering and control systems, currently serving as a Life Distinguished Professor at the Department of Electrical Engineering, National Chung Hsing University (NCHU), Taiwan. He earned his Ph.D. from Northwestern University in 1991. Dr. Tsai has held significant leadership roles, including serving as the President of the Chinese Automatic Control Society (CACS), the Robotics Society of Taiwan (RST), and the International Fuzzy Systems Association (IFSA). He has also been a Board of Governors member of IEEE Systems, Man, and Cybernetics Society (SMCS) and is currently the Dean of the College of Electrical Engineering and Computer Science at NCHU. An IEEE Fellow, his research focuses on intelligent control systems, mobile robotics, and automation intelligence. Dr. Tsai has published over 700 technical articles, with more than 20 in the International Journal of Fuzzy Systems since 2005. His recent work includes a 2025 paper on intelligent adaptive formation control for multi-quadrotors, introducing a hybrid controller combining Output Recurrent Fuzzy Broad Learning Systems (ORFBLS), reinforcement learning, and adaptive backstepping sliding mode control. According to Scopus, he has an h-index of 29, with 3,902 citations from 272 documents.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Two-layer intelligent learning control using output recurrent fuzzy neural long short-term memory broad learning system with RMSprop. IEEE Access.

Tsai, C.-C., Hung, C.-C., Mao, C.-F., Wu, H.-S., & Chen, C.-H. (2025). Fuzzy neural LSTM-RBLS for fractional-order PID sliding-mode motion control of autonomous mobile robots with four ISID wheels. International Journal of Fuzzy Systems.

Tsai, C.-C., Mao, C.-F., & Hussain, K. (2025). Intelligent adaptive formation control using ORFBLS and reinforcement learning for uncertain tilting multi-quadrotors. International Journal of Fuzzy Systems. =

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Intelligent MIMO ORFBLS-based setpoint tracking control with its application to temperature control of an industrial extrusion barrel. International Journal of Fuzzy Systems.

Tsai, C.-C., Huang, H.-C., Chen, H.-Y., Hung, C.-C., & Chen, S.-T. (2024). Intelligent collision-free formation control of ball-riding robots using output recurrent broad learning in industrial cyber-physical systems. IEEE Transactions on Industrial Cyber-Physical Systems.