Mengying Zhang | Information Technology | Women Researcher Award

Published on by Scientific World Research Awards

Women Researcher Award

Mengying Zhang

Mengying Zhang
Affiliation Anhui University
Country China
Scopus ID 57191031563
Documents 24
Citations 330
h-index 8
Subject Area Information Technology
Event Scientific World Research Awards
ORCID 0000-0002-2789-0459

Mengying Zhang is an academic researcher associated with operational research, supply chain management, pricing strategy, and information technology studies. Her scholarly work includes investigations into online platform systems, cap-and-trade allocation models, opaque selling mechanisms, and probabilistic supply chain structures.[1]

Abstract

Mengying Zhang has contributed to research in information technology and operational research with emphasis on supply chain systems, probabilistic selling, and online marketplace structures. Her publications examine pricing models, capacity allocation mechanisms, and competitive interactions in fashion and digital commerce environments. The Women Researcher Award recognizes her scholarly participation in analytical and technology-driven research addressing modern business operations and decision-making frameworks. Her work reflects interdisciplinary engagement in optimization, platform economics, and strategic operational planning within contemporary information and management systems.[2]

Keywords

Operational Research, Supply Chain Management, Information Technology, Pricing Strategy, Marketplace Systems.

Introduction

Operational research and information technology increasingly influence modern supply chain optimization and digital marketplace systems. Mengying Zhang has participated in research exploring pricing structures, market coordination, and decision-making strategies within technology-driven commercial environments.[3]

Research Profile

Her research profile includes studies on platform supply chains, probabilistic selling, online marketplace systems, and operational optimization models. These publications contribute to analytical approaches in digital commerce and economic decision systems.[1]

Research Contributions

Mengying Zhang has contributed to research concerning cap-and-trade regulations, pricing competition in fashion supply chains, reseller marketplace strategies, and allocation mechanisms within operational systems.[4]

Publications

  • Impact of power structure on probabilistic selling in supply chains
  • Pricing and Capacity Allocation in Opaque Selling
  • Marketplace or reseller? The effect of asymmetric selling cost and demand information

Research Impact

Her research activities contribute to understanding digital commerce structures and operational management systems. The studies provide analytical perspectives applicable to platform economics, resource allocation, and supply chain decision-making processes.[5]

Award Suitability

The Women Researcher Award acknowledges academic engagement, interdisciplinary research participation, and contributions to operational research and information technology studies through peer-reviewed scholarly publications.

Conclusion

Mengying Zhang’s research profile reflects continued scholarly participation in operational research, supply chain systems, and analytical modeling relevant to digital marketplace structures and information technology applications.

References

  1. ORCID. (2026). Mengying Zhang researcher profile and publication record.
    https://orcid.org/0000-0002-2789-0459
  2. Elsevier. (n.d.). Scopus author details: Mengying Zhang, Author ID 57191031563.
    https://www.scopus.com/authid/detail.uri?authorId=57191031563
  3. International Journal of Production Economics. (2026). Impact of power structure on probabilistic selling in supply chains.
    https://doi.org/10.1016/j.ijpe.2026.109940
  4. European Journal of Operational Research. (2024). Pricing and Capacity Allocation in Opaque Selling.
    https://doi.org/10.1016/j.ejor.2024.05.022
  5. International Transactions in Operational Research. (2024). Cap allocation rules for an online platform supply chain under cap-and-trade regulation.
    https://doi.org/10.1111/itor.13268

Jianxi Zhao | Artificial Intelligence | Best Researcher Award

Published on by Scientific World Research Awards

Mr. Jianxi Zhao | Artificial Intelligence | Best Researcher Award

Beijing Information Science and Technology University, China

Mr. Jianxi Zhao is an emerging researcher recognized for his contributions to computational statistics, recurrent event analysis, and advanced statistical modeling. Affiliated with Beijing Information Science & Technology University, he has developed expertise in handling complex quantitative data through innovative analytical methodologies. His scholarly work focuses on improving statistical accuracy in situations involving intermittently observed covariates and dynamic event-driven datasets. With multiple indexed publications and a steadily growing citation record, he has demonstrated academic consistency and research capability within the field of applied statistics. His research activities emphasize methodological precision, mathematical computation, and interdisciplinary problem-solving relevant to modern scientific investigations. Through collaborations with fellow researchers and participation in scholarly publishing, he continues to strengthen his professional visibility and academic impact. Mr. Jianxi Zhao’s dedication to statistical innovation and computational research reflects strong potential for future contributions to global scientific and analytical advancement.

Professional Profile

Education

Jianxi Zhao has established a solid academic background in statistics, computational mathematics, and data-oriented scientific research. Associated with Beijing Information Science & Technology University, he has developed expertise in advanced statistical methodologies, recurrent event analysis, and mathematical modeling. His educational foundation emphasizes quantitative reasoning, analytical computation, and applied statistical interpretation, enabling him to address complex research challenges effectively. Through continuous academic engagement, he has strengthened his understanding of survival analysis, time-varying coefficient models, and intermittently observed covariate techniques. His scholarly preparation reflects dedication to methodological precision and scientific innovation. The combination of theoretical knowledge and computational capability has supported his contributions to statistical sciences and interdisciplinary analytical studies. His educational journey highlights a commitment to rigorous research practices, academic discipline, and the advancement of modern computational statistics for practical and scientific applications.

Professional Experience

Mr. Jianxi Zhao has gained valuable academic and research experience through active involvement in computational statistics and analytical modeling studies. His professional activities include conducting statistical investigations, contributing to scholarly publications, and collaborating with researchers in quantitative science disciplines. Working within the research environment of Beijing Information Science & Technology University, he has participated in projects focusing on recurrent event data, predictive modeling, and applied statistical methodologies. His experience reflects competence in handling complex datasets, developing mathematical frameworks, and interpreting analytical outcomes for scientific purposes. He has also contributed to collaborative research networks involving multiple co-authors and interdisciplinary perspectives. Through publication activities and academic engagement, he has strengthened his professional reputation within computational and statistical research communities. His growing experience demonstrates dedication to scientific inquiry, problem-solving, and the application of innovative statistical techniques in contemporary research environments.

Research Interest

The research interests of Jianxi Zhao primarily focus on computational statistics, recurrent event analysis, survival data modeling, and time-varying coefficient methodologies. His scholarly attention is directed toward developing advanced statistical approaches capable of addressing incomplete or intermittently observed covariate information in complex datasets. He is particularly interested in improving analytical accuracy and predictive reliability within biomedical statistics, longitudinal data interpretation, and mathematical computation. His work explores innovative techniques that enhance the understanding of event-driven data structures and dynamic statistical relationships. In addition, he demonstrates interest in interdisciplinary applications where computational modeling supports scientific and technological advancements. His research orientation combines theoretical development with practical implementation, contributing to the evolution of modern statistical science. By investigating sophisticated analytical frameworks, he aims to provide meaningful solutions for complex quantitative challenges across academic and applied research domains.

Award and Honor

Mr. Jianxi Zhao has earned academic recognition through his impactful research contributions in computational statistics and applied data analysis. His scholarly publications, citation record, and collaborative research activities reflect growing recognition within the scientific community. With indexed publications and measurable citation impact, he has demonstrated the quality and relevance of his research work in statistical modeling and recurrent event analysis. His contributions have strengthened his professional standing as an emerging researcher in computational and mathematical sciences. Participation in collaborative academic studies and publication in recognized scientific platforms further highlights his dedication to research excellence. Although publicly available information regarding formal awards remains limited, his academic performance, research productivity, and methodological contributions represent significant professional achievements. His growing citation influence and consistent engagement in advanced statistical research position him as a promising contributor to future scientific innovation and scholarly development within the international research landscape.

Conclusion

Mr. Jianxi Zhao demonstrates strong potential in computational statistics through impactful research, scholarly dedication, and analytical expertise. His growing academic influence and innovative statistical contributions support continued success in advanced scientific research.

Publications Top Noted

  • Title: A time-varying coefficient rate model with intermittently observed covariates for recurrent event data
    Authors: Jianxi Zhao et al.
    Year: 2025

Solomon Legesse | Computer Science | Editorial Board Member

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Assoc Prof Dr. Solomon Legesse | Computer Science | Editorial Board Member

Postgraduate Coordinator | Bahir Dar University | Ethiopia

Dr. Solomon Addisu is a leading researcher in climate change, environmental systems, soil science, and sustainable land-use management, with a strong focus on Ethiopia and the broader East African region. His extensive body of work advances understanding of how climate variability, land degradation, agricultural systems, and natural resource pressures intersect to shape environmental sustainability and community resilience. Through more than a decade of scientific contributions, he has established himself as a significant voice in climate adaptation research, soil enhancement technologies, and watershed management.A central pillar of his research explores biochar technology, soil amendments, and nutrient cycling. His studies on water hyacinth-based biochar, phosphorus biofertilizers from animal bone, and the physicochemical transformations of biomass during pyrolysis offer pioneering insights into regenerative agriculture and soil rehabilitation. These works demonstrate the potential of low-cost, sustainable inputs to improve soil fertility, reduce acidification, enhance nutrient retention, and boost crop productivity—especially in degraded highland agroecosystems.Dr. Addisu is also widely recognized for his contributions to climate modeling, hydrological forecasting, and drought analysis. His research using CMIP6 scenarios, rainfall trend evaluations, and meteorological drought assessments provides vital actionable guidance for climate adaptation planning in vulnerable regions. He applies advanced geospatial tools, remote sensing, and machine learning to analyze land-use dynamics, watershed degradation, flood risks, and invasive species monitoring—most notably in the Lake Tana basin.Another core area of his work addresses environmental pollution, urban heat island effects, charcoal production impacts, and sustainable waste management solutions. His studies integrate socioeconomic, ecological, and policy perspectives, offering comprehensive frameworks for environmental governance, community-based adaptation, and nature-based solutions.Additionally, Dr. Addisu’s extensive research on climate change perceptions, rural livelihood vulnerabilities, agricultural resilience, and livestock diversification is widely cited in the fields of sustainable development and rural poverty reduction. His work equips policymakers and communities with evidence-based strategies to build resilience in the face of increasing climate stressors.Overall, Dr. Solomon Addisu’s research portfolio bridges environmental science, climate adaptation, soil restoration, and sustainable natural resource management. His contributions significantly strengthen scientific understanding and provide practical pathways toward ecological stability, food security, and climate-resilient development across Ethiopia and East Africa.

Profiles: ORCID

Featured Publications

  1. Kohira, Y., Fentie, D., Lewoyehu, M., Wutisirirattanachai, T., Gezahegn, A., Ahmed, M., Akizuki, S., Addisu, S., & Sato, S. (2025). The sustainable management of nitrogen fertilizers for environmental impact mitigation by biochar applications to soils: A review from the past decade. Environments.

  2. Fentie, D., Mihretie, F. A., Kohira, Y., Addisu Legesse, S., Lewoyehu, M., Wutisirirattanachai, T., & Sato, S. (2025). Optimizing cropping systems using biochar for wheat production across contrasting seasons in Ethiopian highland agroecology. Agronomy.

  3. Gezahegn, A., Selassie, Y. G., Agegnehu, G., Addisu, S., Mihretie, F. A., Kohira, Y., & Sato, S. (2025). Pyrolysis temperature changes the physicochemical characteristics of water hyacinth-based biochar as a potential soil amendment. Biomass Conversion and Biorefinery.

  4. Mekonnen, G. T., Berlie, A. B., Wubie, M. A., Legesse, S. A., & Cameselle, C. (2025). Surface urban heat island intensity and urban utility consumption: Impact analysis and projections. The Scientific World Journal.

  5. Addisu, S., Aniley, E., Gashaw, T., Kelemu, S., & Demessie, S. F. (2024). Evaluating the performances of gridded satellite products in simulating the rainfall characteristics of Abay Basin, Ethiopia. Sustainable Environment.

The nominee’s contributions in computer science advance intelligent systems that enhance automation, analytics, and digital decision-making across industries. Their innovative research accelerates global technological transformation, strengthens digital infrastructures, and drives smarter, more efficient solutions for society, businesses, and future technological innovation.

Farhan Nisar | Computer Science | Best Researcher Award

Published on by Scientific World Research Awards

Dr. Farhan Nisar | Computer Science | Best Researcher Award

Lecturer | The University of Agriculture | Pakistan

Dr. Farhan Nisar, affiliated with Qurtuba University of Science & Information Technology, Peshawar, Pakistan, is an emerging scholar and researcher in wireless communications, Internet of Things (IoT) networks, and machine learning applications for network optimization. He has made notable contributions to the field through his research on Low Power Wide Area Networks (LPWANs), particularly LoRaWAN, focusing on improving network efficiency, energy consumption, scalability, and reliability. Dr. Nisar’s educational background and professional trajectory have equipped him with a solid foundation in computer science and telecommunications, enabling him to apply advanced machine learning techniques for adaptive network parameter optimization, such as spreading factor adjustment, which enhances IoT network performance in dynamic real-world environments. Professionally, he has been involved in academic research, teaching, and applied projects that bridge theoretical knowledge with practical deployment of intelligent network solutions. His research interests include wireless communication protocols, IoT architectures, network security, data-driven network management, and intelligent device integration, reflecting a multidisciplinary approach that combines computer science, engineering, and data analytics. Dr. Nisar has developed strong research skills in machine learning modeling, algorithm development, network simulation, data analysis, and performance evaluation, contributing to both academic publications and open-access research outputs. His scholarly work has resulted in six published documents, with 18 citations to date and an h-index of 3, as indexed in Scopus, demonstrating early yet impactful contributions to his field. While still in the early stages of his career, he has received recognition for his innovative approaches to network optimization and IoT research, highlighting his potential for future academic and industrial leadership. In conclusion, Dr. Farhan Nisar represents a forward-looking researcher whose interdisciplinary expertise, rigorous methodology, and practical focus on intelligent, self-optimizing networks position him as a valuable contributor to the advancement of next-generation IoT and wireless communication technologies.

Profiles: Scopus

Featured Publications

  1. Nisar, F., & [Co-authors]. (2016). Green cloud computing approaches with respect to energy saving to data centers. Journal of Information, 6(2).

  2. Nisar, F., & [Co-authors]. (2017). Native approach security issue. In Proceedings of the IEEE Comtech Conference.

  3. Nisar, F., & [Co-authors]. (2019). Location-based authentication service in smartphones. In Proceedings of the IEEE Comtech Conference.

  4. Nisar, F., & [Co-authors]. (2019). Apply ARIMA model for data center with respect to different architecture. In Proceedings of the IEEE Raees Conference.

  5. Nisar, F., & [Co-authors]. (2019). Resource utilization in data center by applying ARIMA approach. In INTAP 2019.