Zhiqi Wu | Engineering | Best Researcher Award

Published on by Innovation Technologist

Ms. Zhiqi Wu | Engineering | Best Researcher Award

Student at Anhui University of Science and Technology | China

Zhiqi Wu is a Master’s student in Electrical Engineering at Anhui University of Science and Technology, specializing in computer vision applications for intelligent coal gangue detection. His research emphasizes developing lightweight, high-performance models that improve automation and efficiency in mining operations. Zhiqi proposed a novel model integrating multispectral imaging with knowledge distillation, achieving a precision increase of up to 6% while reducing model size by 21.8%, enabling deployment on mobile and edge devices for real-time sorting. This approach advances intelligent coal industry practices by combining computational efficiency with practical industrial applicability. Zhiqi’s work exemplifies the translation of advanced AI techniques into actionable solutions for industrial automation, with a focus on scalability, accuracy, and sustainability. His contributions are recognized in the research community, with 1 citation for his published work, highlighting its impact and relevance. To date, he has contributed to 4 documents in his research portfolio, reflecting his engagement in ongoing innovation and knowledge dissemination. While his h-index currently stands at 1, it represents a promising start in a career dedicated to applied AI in mining technologies. Zhiqi continues to explore methods for optimizing computer vision systems in industrial contexts, advancing automation, operational safety, and resource efficiency. His work bridges theoretical research and practical deployment, positioning him as an emerging researcher making measurable contributions to intelligent mining technologies.

Profile: Scopus

Featured Publications

Yan, P. (2025). Transformer fault diagnosis based on LIF technology and COA-GRU algorithm. Engineering Research Express, 7(2), 25409.

ABLA CHAOUNI BENABDELLAH | Engineering | Best Researcher Award

Published on by Innovation Technologist

Assist. Prof. Dr. ABLA CHAOUNI BENABDELLAH | Engineering | Best Researcher Award

BEST RESEARCHER at International University of rabat, Morocco

Abla Chaouni Benabdellah is an Assistant Professor of Supply Chain Management and Information Systems at Rabat Business School, International University of Rabat (UIR). She holds a Ph.D. in Industrial Engineering from Moulay Ismail University, Meknes, and a Master’s in Mathematics and Statistics from Mohamed V University, Rabat. With extensive teaching experience across various institutions including EUROMED University and Private University of Fez, she specializes in project management, risk management, and supply chain strategies.

Publication Profile : 

Scopus

🎓 Educational Background :

  • Ph.D. in Industrial Engineering (2016 – 2019), Moulay Ismail University, ENSAM, Meknes
  • Master in Mathematics and Statistics (2012 – 2014), Mohamed V University, Rabat
  • Bachelor in Applied Mathematics (2009 – 2012), Moulay Ismail University, Faculty of Science, Meknes
  • Baccalaureate in Mathematics (2008 – 2009), Moulay Ismail College, Meknes

💼 Professional Experience :

  • Assistant Professor of Supply Chain Management & Information Systems (Since 2022), Rabat Business School, International University of Rabat (UIR), Rabat
  • Human Resources Consultant (2021), Expert Human Capital (EHC), Casablanca
  • Professor (2020), School of Digital Engineering and Artificial Intelligence (EIDIA), EUROMED University, Fez
  • Professor (2020), Private University of Fez, Fez
  • Seminar Presenter (2020), “Holonic Multi-Agent Systems for Decision Making -Application to Knowledge Management-“, ENSAM, Meknès
  • Doctoral Course Instructor (2019), Statistical Modeling with R Software, ENSAM-Meknès
  • Coordinator (2018), Artificial Intelligence and Data Science Master, SUPMTI, Meknes
  • Professor (2016), Higher School of Management, Telecommunications and IT (SUPMTI), Meknes

📚 Research Interests : 

  • Supply Chain Management
  • Industrial Engineering
  • Digital Supply Chains
  • Blockchain Technology
  • Artificial Intelligence and Data Science
  • Statistical Modeling

📝 Publication Top Notes :

  1. Blockchain Technology in Supply Chains: Discusses blockchain’s role in enhancing digital supply chains and evaluates implementation barriers.
  2. Big Data Analytics in Supplier Selection: Explores a multi-agent system for supplier selection using big data analytics.
  3. Smart Product Design and Digital Agility: Develops an ontology for managing agility in digital product design.
  4. Blockchain and Smart Contracts in Automotive Supply Chains: Examines how blockchain and smart contracts can optimize automotive supply chains.
  5. Medical Waste Management Optimization: A multi-agent system approach for improving medical waste management.
  6. Sustainable Supplier Selection in Circular Economy: Uses an ontology-based model to improve supplier selection under a circular economy framework.
  7. Environmental Supply Chain Risk Management: Proposes a data mining framework for managing supply chain risks in Industry 4.0.
  8. Lean and Green Practices in Supply Chains: Integrates lean and green practices to enhance sustainable and digital supply chain performance.
  9. Digital Technologies and Circular Economy: Investigates how digital technologies support sustainable supply chain management post-COVID-19.
  10. Circular Digital Supply Chain Design: Focuses on sustainable design practices within digital supply chains.
  11. Supplier Selection Ontology: Develops an ontology for effective supplier selection in digital supply chains.
  12. Intersection of Design for X and Business Strategies: Analyzes the integration of design techniques and business strategies for product lifecycle management.
  13. Knowledge Discovery for Sustainability: Discusses methods for enhancing sustainability through knowledge discovery in design processes.