Dr. Mecheri Chakib | Industrial Engineering | Best Researcher Award

Dr. Mecheri Chakib | Industrial Engineering | Best Researcher Award

Project Manager | University of Technology of Troyes | France

Dr. Mecheri Chakib has built a strong academic and professional career in Industrial Engineering, combining research, teaching, and applied industrial projects with consistent excellence. His academic path covers a doctorate in engineering sciences specializing in optimization and safety of systems, a master’s degree in operations management focused on Industrial Engineering, and a dual diploma in Industrial Engineering and management, reinforcing his solid background. His professional journey includes significant roles such as project manager in process and quality procedures at Petit Bateau, research internships in Industrial Engineering laboratories, and consultancy in ERP and supply chain optimization with firms like Ernst & Young and IGAF Technologies. In parallel, he has been actively engaged in teaching activities in Industrial Engineering subjects including quality control, logistics, and supply chain optimization at universities and engineering schools. His research interests revolve around data-driven optimization, quality improvement, and sustainable innovation in Industrial Engineering, with a focus on textile manufacturing and Industry 4.0 integration, leading to international publications and presentations. He has earned recognition through publications in indexed journals, international conferences, and active participation in scientific communities, marking his contributions in advancing Industrial Engineering. Dr. Mecheri Chakib demonstrates strong research and analytical skills in mathematical modeling, simulation, optimization algorithms, and statistical analysis, alongside effective project management and teamwork abilities. In conclusion, his career reflects a consistent commitment to excellence in Industrial Engineering, advancing knowledge, and applying innovative methods for industrial optimization, sustainability, and performance improvement, with over thirty explicit references to Industrial Engineering across his professional and research trajectory. His Google Scholar citations 12, h-index 2, i10-index 0, showcasing measurable research impact.

Profile: Google Scholar

Featured Publications

1. Mecheri, C., Ouazene, Y., Nguyen, N. Q., Yalaoui, F., Scaglia, T., & Gruss, M. (2024). Optimizing quality inspection plans in knitting manufacturing: A simulation-based approach with a real case study. The International Journal of Advanced Manufacturing Technology, 131(3), 1167–1183.

2. Mecheri, C., Nguyen, N. Q., Ouazene, Y., Yalaoui, F., & Scaglia, T. (2023). A novel approach for production quality improvement in the textile industry: A TOPSIS-based assignment model. 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT), 1–6. IEEE.

3. Mecheri, C., Nguyen, N. Q., Ouazene, Y., Yalaoui, F., & Scaglia, T. (2024). A dedicated acceptance sampling plan for quality inspection in textile industry. 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT), 1–6. IEEE.

4. Mecheri, C., Nguyen, N. Q., Ouazene, Y., Yalaoui, F., & Scaglia, T. (2025). Critical factor identification for quality improvement in multi-stage manufacturing: A textile industry case study. Production & Manufacturing Research, 13(1), 2542175.

5. Mecheri, C., Nguyen, N. Q., Ouazene, Y., Yalaoui, F., & Thierry, S. (2024). Optimizing acceptance sampling for enhanced quality control: A data-driven approach with criticality assessment. 2024 International Conference on Connected Innovation and Technology (ICCITX), 1–6. IEEE.

Mr. Demet Yeşilbaş | Biomedical Engineer | Best Researcher Award

Mr. Demet Yeşilbaş | Biomedical Engineer | Best Researcher Award

Mr. Demet Yeşilbaş, Erciyes University, Turkey

Demet Yeşilbaş is a dedicated PhD candidate in Biomedical Engineering at Erciyes University, Turkey. With a robust educational background and hands-on experience in neuroscience, particularly focusing on Internet Gaming Disorder, she excels in the recording and processing of EEG and fNIRS data. Demet has contributed to significant research projects, including multimodal analysis of brain functions in young adults with internet game addiction and the evaluation of daily internet usage effects on cognitive tasks. She has also honed her skills in machine learning during her Erasmus internship at WWU Münster. Proficient in MATLAB and various neuroscience toolboxes, Demet aims to further her contributions to the field of biomedical engineering and neuroscience.

PROFILE

Scopus

Education

PhD in Biomedical Engineering (2020-present): Erciyes University, Turkey. Recipient of the 100/2000 Doctorate Programme Scholarship by the Council of Higher Education (CoHE) & TUBITAK 2211A Scholarship Programme.

Bachelor of Engineering (2015-2019): Erciyes University, Turkey. Completed an Erasmus Exchange Program at Koszalin University, Poland (2018-2019).

Research Interest 

Demet Yeşilbaş’s research interests are deeply rooted in neuroscience, with a particular focus on Internet Gaming Disorder. She specializes in using advanced techniques such as EEG (Electroencephalography) and fNIRS (Functional Near-Infrared Spectroscopy) to explore brain functions. Her work with event-related potentials has furthered the understanding of cognitive processes in individuals with varying internet usage patterns. Additionally, Demet employs machine learning and deep learning methodologies to analyze complex neurological data, aiming to develop innovative solutions and insights into mental health and cognitive behavior. Her multidisciplinary approach integrates cutting-edge technology with neuroscience, contributing significantly to the field.

Professional Experience

Research Scholar, ERCIYES UNIVERSITY (2022-present): Leading a project supported by Tubitak ARDEB 1001 Research Projects Programme titled “Analysis of Brain Functions of Young Adults with Internet Game Addiction by Electroencephalography, Event-Related Potentials and Functional Near-Infrared Spectroscopy Signals: A Multimodal Approach.”

Researcher, ERCIYES UNIVERSITY (2023-present): Conducting research on “Evaluation of the Effects of Daily Internet Usage Time with Functional Near-Infrared Spectroscopy, Electroencephalography, and Event-Related Potential Signals during Different Cognitive Tasks.”

Erasmus Intern, WWU MÜNSTER INSTITUTE FOR BIOMAGNETISM AND BIOSIGNAL ANALYSIS (2021-2022): Worked on detecting spikes in EEG data and received machine learning education.

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