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

Maliki Moustapha | Computer Science | Best Researcher Award

Published on by Scientific World Research Awards

Dr. Maliki Moustapha | Computer Science | Best Researcher Award

PhD | Erciyes University | Turkey

Dr. Maliki Moustapha, an accomplished researcher from Erciyes University, is recognized for his expertise in Artificial Intelligence (AI), Deep Transfer Learning, and Data Engineering, with a strong focus on the integration of intelligent algorithms and data-driven models to address real-world computational challenges. His academic background is rooted in computer science and engineering, where he developed advanced skills in machine learning, neural networks, data mining, and smart systems design. Professionally, Dr. Moustapha has been actively engaged in both research and academic mentorship, contributing to the development of innovative solutions in AI-powered automation, pattern recognition, and intelligent monitoring systems. His major research interests encompass computer vision, deep learning model optimization, spatiotemporal data analysis, and Internet of Things (IoT)-based smart healthcare systems. Among his most cited contributions is the publication titled “A Novel YOLOv5 Deep Learning Model for Handwriting Detection and Recognition” in the International Journal on Artificial Intelligence Tools (2023), which demonstrates superior accuracy and efficiency in image recognition. He has also published influential works on spatial and spatiotemporal clustering algorithms and IoT-based patient monitoring, bridging the gap between data intelligence and applied computing. His research skills span across Python programming, neural network modeling, big data analytics, data preprocessing, and model training for intelligent systems. Though early in his academic journey, Dr. Moustapha has earned recognition for his impactful work, showing promising potential in advancing AI technologies. According to Scopus and Google Scholar, he has achieved 9 citations, an h-index of 1, and several published documents reflecting growing international recognition. Dr. Moustapha’s research continues to contribute meaningfully to the fields of artificial intelligence and computational intelligence. In conclusion, his innovative approach, interdisciplinary mindset, and technological vision position him as a forward-thinking researcher committed to shaping the next generation of intelligent data systems and AI-driven innovations.

Profiles: ORCID | Google Scholar

Featured Publications

1. Moustapha, M., Taşyürek, M., & Öztürk, C. (2023). A novel YOLOv5 deep learning model for handwriting detection and recognition. International Journal on Artificial Intelligence Tools, 32(04), 2350016.

2. Moustapha, M. (2024). Spatial and spatiotemporal clustering algorithms in data mining. In Proceedings of the 3rd International Conference on Data and Electronics and Computing (ICDEC).

3. Moustapha, M. (2019). Alternative approach of patient monitoring system based on Internet of Things. In Proceedings of the II. International Science and Academic Congress (INSAC).