Mehret Sime | Industrial Engineering | Best Researcher Award

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Mrs. Mehret Sime | Industrial Engineering | Best Researcher Award

Mrs. Mehret Sime, Addis Ababa university, Ethiopia

Mehret Getachew Sime, born on April 24, 1993, in Addis Ababa, is a PhD candidate in Industrial Engineering at Addis Ababa University. She holds an MSc (2018) and BSc (2015) in the same field. Currently a lecturer at Dire Dawa University, Mehret has experience in University-Industry linkage and has completed externships with Coca-Cola and internships in the metal sector. Her research focuses on digital maturity in manufacturing and AI for zero-defect manufacturing. She is an active member of the International Society for Industrial Engineering and Operations Management. 💡📊

Publication profile

Orcid

Educational Background

Mrs. Mehret is a 4th-year Ph.D. candidate in Industrial Engineering at Addis Ababa Institute of Technology, Addis Ababa University. She also holds an MSc in Industrial Engineering from the same institution, completed in 2018, and a BSc from Mekelle University, obtained in 2015. Her educational journey reflects a strong foundation in industrial engineering.

Work Experience

Mrs. Mehret has been a Lecturer at Dire Dawa Institute of Technology, Dire Dawa University since 2018. In addition, she served as an officer in University-Industry Linkage and gained practical experience through externships and internships at East African Bottling Share Company (Coca-Cola) and Metal and Engineering Corporation. Her academic and industrial experiences position her well in research and teaching.

Training Certifications

Mrs. Mehret has completed various leadership and project management training courses, equipping her with essential skills for leading academic and industrial projects. She is also certified in Kaizen and entrepreneurship, further diversifying her expertise.

Conclusion

Mrs. Mehret Getachew Sime’s extensive academic background, professional experience, publications, and active involvement in industrial engineering make her a suitable candidate for the Research for Best Researcher Award. Her dedication to advancing the field and consistent contributions reflect her high potential as a researcher.

 

Publication Top Notes

  • Application of AI to Enhance Manufacturing Quality and Zero-Defect Using CRISP-DM Framework (2024) 📊🧠
  • Data Analytics in Zero Defect Manufacturing: A Systematic Literature Review and Proposed Framework (2024) 📚🔧
  • Analysis of Factors Affecting the Digital Maturity of Manufacturing Industries: Evidence from the Metal Sector in Ethiopia (2023) ⚙️📈

 

 

 

 

TRAN THI BICH CHAU VO | Industrial Engineering | Best Innovation Award

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Ms. TRAN THI BICH CHAU VO | Industrial Engineering | Best Innovation Award

PhD Candidate at National Kaohsiung University of Science and Technology, Taiwan

Tran Thi Bich Chau VO is a dedicated Vietnamese academic and researcher in Industrial Engineering and Management, currently serving as a Lecturer at Can Tho University since 2014. With a strong background in the garment and textile industry, she previously held roles as Head of the R&D Department at Thanhcong Textile Garment Investment Trading JSC and as a Work Study Staff at Garment Fashion Limited. She is pursuing her Ph.D. at the National Kaohsiung University of Science and Technology in Taiwan, focusing on improving processing efficiency through workflow process reengineering, simulation, and value stream mapping.

Publication profile :

🎓 Educational Background :

  • Ph.D. in Industrial Engineering and Management (Expected 12/2024)

    National Kaohsiung University of Science and Technology, Taiwan

    Thesis: “Improving Processing Efficiency through Workflow Process Reengineering, Simulation, and Value Stream Mapping.”

  • Master of Engineering in Industrial and Systems Engineering (2014)

    Ho Chi Minh City University of Technology, Vietnam National University

    Thesis: “Effects of Lean Manufacturing in a Garment Line at Thanhcong Textile Garment Investment Trading Joint Stock Company.”

  • Bachelor of Engineering in Garment Technology and Fashion (2011)

    Ho Chi Minh City University of Technology and Education, Vietnam

    Thesis: “Researching the Improved Pattern for the Production Department in An Phu Chau Company.”

🏢 Professional Experience :

  • Lecturer, Faculty of Industrial Management (Since 08/2014)

    Can Tho University, Vietnam

    Tran Thi Bich Chau teaches courses such as Methods Standards & Work Design, Production Planning & Scheduling, Lean Manufacturing, and Facility Layout and Location.

  • Head of Dept. Research & Development (10/2012 – 07/2014)

    Thanhcong Textile Garment Investment Trading Joint Stock Company, Ho Chi Minh, Vietnam

    She led R&D initiatives focused on operations and productivity improvements.

  • Staff, Dept. Work Study (04/2011 – 09/2012)

    Garment Fashion Limited, Bien Hoa, Vietnam

    Worked on work study projects to enhance efficiency in garment production.

🌱 Research Interests :

Tran Thi Bich Chau’s research interests include lean manufacturing, production efficiency, simulation, and supply chain optimization, particularly in the textile and aquaculture industries. She has led and participated in several significant research projects and is also an active reviewer for prestigious journals and conferences. 🌟📚👩‍🏫

Publication Top Notes :

  • Business Process Reengineering and Manufacturing Optimization: Several papers (Publications [1], [2], [9], [10], [11]) highlight improvements in business and manufacturing processes through methods like value stream mapping, workflow process reengineering, and the use of digital twin platforms.
  • Environmental and Wastewater Treatment: Research articles (Publications [3], [4], [8]) provide comprehensive reviews and case studies on aeration, wastewater treatment in aquaculture, and sustainable practices in shrimp farming.
  • Bioanalytical Sensors and Smart Health Monitoring: Publication [5] discusses recent trends in bioanalytical sensors and their applications in smart health monitoring systems, covering materials to practical uses.
  • Supply Chain and Risk Management: Publications [6], [7] address issues related to supply chain optimization and risk management in industries such as aquaculture, utilizing computational studies and risk mitigation approaches.
  • Material Science and Engineering: A series of studies (Publications [12] to [15]) focus on the development and characterization of advanced materials, including graphene oxide-coated sponges and hydrogel membranes, for applications in environmental remediation and material science.
  • Health and Food Science: Research on the health effects of coffee and the clinical applications of turmeric (Publications [16], [21]) reflects an interest in the intersection of food science and health.

 

 

 

Soroush Safarzadeh | Industrial Engineering | Best Researcher Award

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Assist Prof Dr. Soroush Safarzadeh | Industrial Engineering | Best Researcher Award

Assist Prof Dr. Soroush Safarzadeh, Quchan University of Technology, Iran

Assistant Professor Dr. Soroush Safarzadeh would be a strong candidate for the “Research for Best Researcher Award” based on the following considerations:

Publication profile

Scopus

Orcid

Google Scholar

Educational Background

Ph.D. in Industrial Engineering from Isfahan University of Technology with a thesis focused on game theory and energy efficiency. 🌟

Teaching Experience

Extensive teaching roles at Ferdowsi University of Mashhad and Quchan University of Technology, covering a range of subjects in industrial engineering and management. 📚

Research Contributions

Over 20 publications in high-impact journals such as Energy, Journal of Cleaner Production, and Applied Energy. His research spans game theory, energy efficiency, and sustainable development. 📈

Editorial and Review Roles

Active reviewer for prestigious journals including Energy Conversion and Management, Journal of Cleaner Production, and Applied Energy. 🕵️‍♂️

Awards and Honors

Recognized for academic excellence with a full scholarship during his M.Sc. and a top rank in the national entrance exam for industrial engineering schools. 🏆

Technical Consultancy

Provided expert consultancy for Khorasan Regional Electric Company and Neyrperse Company, contributing to research-oriented projects and practical industry solutions. 🛠️

Publication Top Notes

  • A group multi-criteria decision-making based on best-worst method
    • 📑 Cited by: 134 | Year: 2018
  • A game theoretic approach for pricing policies in a duopolistic supply chain considering energy productivity, industrial rebound effect, and government policies
    • 📑 Cited by: 104 | Year: 2019
  • A game theoretic approach for assessing residential energy-efficiency program considering rebound, consumer behavior, and government policies
    • 📑 Cited by: 97 | Year: 2019
  • A review of optimal energy policy instruments on industrial energy efficiency programs, rebound effects, and government policies
    • 📑 Cited by: 94 | Year: 2020
  • Solving an extended multi-row facility layout problem with fuzzy clearances using GA
    • 📑 Cited by: 56 | Year: 2017
  • A hybrid evolutionary game-theoretic and system dynamics approach for analysis of implementation strategies of green technological innovation under government intervention
    • 📑 Cited by: 39 | Year: 2022
  • Effects of governmental policies on energy-efficiency improvement of hydrogen fuel cell cars: A game-theoretic approach
    • 📑 Cited by: 38 | Year: 2022
  • A duopolistic game for designing a comprehensive energy-efficiency scheme regarding consumer features: Which energy policy is the best?
    • 📑 Cited by: 34 | Year: 2020
  • Energy supply chain empowerment through tradable green and white certificates: A pathway to sustainable energy generation
    • 📑 Cited by: 28 | Year: 2022
  • A game theoretic approach for the duopoly pricing of energy-efficient appliances regarding innovation protection and social welfare
    • 📑 Cited by: 28 | Year: 2020
  • Time-Of-Use pricing in an energy sustainable supply chain with government interventions: A game theory approach
    • 📑 Cited by: 27 | Year: 2022
  • A modified lexicographic semi-order model using the best-worst method
    • 📑 Cited by: 16 | Year: 2018
  • A heuristic scheduling method for the pipe-spool fabrication process
    • 📑 Cited by: 16* | Year: 2018
  • Producing two substitutable products under a supply chain including two manufacturers and one retailer: A game-theoretic approach
    • 📑 Cited by: 7 | Year: 2023
  • Product safety assessment in a dairy dual-channel supply chain using game theory
    • 📑 Cited by: 2 | Year: 2024
  • Vehicle pricing considering EVs promotion and public transportation investment under governmental policies on sustainable transportation development: The case of Norway
    • 📑 Cited by: 1 | Year: 2024
  • An Evolutionary Game-Theoretic Approach for Analysis of Green Innovation and Environmental Performance of Tech Firms under Stakeholders’ Policies Based on System Dynamics
    • 📑 Cited by: 1 | Year: 2024
  • Investigating big data investment in a three-level green supply chain: A game theoretic approach
    • Year: 2025
  • A game theoretic approach for green supply chain management in a big data environment considering cost-sharing models
    •  Year: 2024
  • A game theoretic approach for tradable white certificates regarding energy rebound and government intervention
    •  Year: 2024

Conclusion

Dr. Safarzadeh’s extensive research, significant teaching contributions, and active involvement in academic and industry-related activities demonstrate a high level of expertise and impact in his field. His strong publication record and roles as a journal reviewer further highlight his commitment to advancing industrial engineering research, making him a suitable candidate for the Research for Best Researcher Award.

AmelJaoua | Industrial Engineering | Industry Integration Academic Award

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Prof. AmelJaoua | Industrial Engineering | Industry Integration Academic Award

Prof. AmelJaoua, National Engineering school of tunis, Tunisia

👩‍🏫 Prof. Amel Jaoua, Ph.D., is a seasoned Industrial Engineering Professor with over 15 years of experience, specializing in Simulation Modeling, Artificial Intelligence, and Digital Twins for Smart Manufacturing. She has published extensively in high-impact journals and played a pivotal role in establishing the Erasmus Master’s Program in Next Production Revolution. With a rich background in academia and industry collaboration, she excels in teaching and research, fostering innovation in global industrial practices. Proficient in multiple programming languages and simulation software, she continues to drive advancements in her field with a dedication to excellence. Connect with her on LinkedIn for more insights.

 

Publication Profile:

Google Scholar

Education:

🎓 Prof. Amel Jaoua’s academic journey reflects a commitment to advancing industrial engineering through rigorous study and research. Her Ph.D. in Industrial Engineering from Polytechnic School of Montreal, Canada, focused on “Discrete Event Simulation Modeling for Real-Time Control of Complex Systems,” laying the groundwork for her expertise in simulation-based optimization. Prior to this, she earned her M.Sc. in Computer and Automation Engineering and B.Eng. in Computer Engineering and Informatics from the National Institute of Applied Sciences and Technology, Tunisia. Through her thesis projects, she delved into real-time traffic control optimization and robust simulation-based control models for supply chains, marking the beginnings of her scholarly pursuits. 📚

 

Experience :

👩‍🔬 Prof. Amel Jaoua’s journey in academia and industry spans over a decade, marked by impactful contributions and collaborations. As a Professor at the National Engineering School of Tunis since 2013, she’s been instrumental in shaping the minds of future engineers, crafting courses like Stochastic Processes and Digital Twin for Smart Manufacturing. Her global outlook is evident in co-developing the Erasmus Master’s Program in Next Production Revolution. Prior to academia, she delved into research consultancy at Hydro-Québec, honing simulation-based optimization techniques. Earlier, at Polytechnic School of Montreal and Pratt & Whitney Canada, she showcased prowess in industrial engineering, emphasizing simulation for real-time control and optimization. 🚀

 

Research Focus:

🔬 Prof. Amel Jaoua’s research focus primarily revolves around simulation modeling and optimization techniques to address complex logistical and industrial challenges. Her work spans various domains, including stochastic freight transportation scheduling, real-time fleet management, and intelligent control architectures for industrial systems. She explores innovative applications such as digital twins for smart manufacturing and reinforcement learning for container loading optimization. With a keen interest in interdisciplinary studies, she has contributed significantly to fields like call center management, supply chain optimization, and condition-based maintenance using machine learning. Prof. Jaoua’s diverse research portfolio demonstrates her commitment to advancing technology-driven solutions for real-world problems. 🌐

 

Publication Top Notes:

📚A simulation-optimization approach for scheduling in stochastic freight transportation(Cited by 60, 2018)
📚A simulation framework for real-time fleet management in internal transport systems (Cited by 59, 2012)
📚Specification of an intelligent simulation-based real time control architecture: Application to truck control system (Cited by 33, 2012)
📚A framework for realistic microscopic modelling of surface mining transportation systems (Cited by 29, 2009)
📚 Call-type dependence in multiskill call centers (Cited by 16, 2013)
📚Data Preparation in Machine Learning for Condition-based Maintenance (Cited by 11, 2021)
📚 New heuristic for the single container loading problem (Cited by 8, 2017)
📚New heuristic for the single container loading problem (Cited by 7, 2023)
📚Comparaison d’approches de modélisation de problèmes tests pour le pilotage du transport(Cited by 7, 2008)
📚A decision support system for on-demand goods delivery using shared autonomous electric vehicles (Cited by 6, 2019)