Zahra Seyedzadeh | Supply chain | Best Researcher Award

Ms. Zahra Seyedzadeh | Supply chain | Best Researcher Award

Zahra Seyedzadeh at Iran university of science and technology, Iran.

Zahra Sadat Seyedzadeh is a dedicated researcher and analyst specializing in industrial engineering, optimization, and systems analysis. She has contributed significantly to research projects in supply chain design, emergency medical services, and machine learning applications. As a distinguished researcher under Iran’s National Elites Foundation, she has been involved in impactful studies on sustainable supply chains, data analytics, and decision-making techniques.

Professional Profile:

Scopus

Education Background

  • Ph.D. in Industrial Engineering (Optimization & Systems Analysis) – Iran University of Science and Technology (2021–Present, Exceptional Talent Admission, GPA: 18.86/20)
  • M.Sc. in Industrial Engineering (Optimization & Systems Analysis) – Iran University of Science and Technology (2017–2019, GPA: 17.79/20)
  • B.Sc. in Industrial Engineering – Ershad University (2013–2017, GPA: 18/20)

Professional Development

Zahra has gained diverse experience across research and industry. She interned at the Institute for Research and Planning in Commerce and served as an Analyst at the Customs Administration of Iran. Recognized as a Distinguished Researcher under the Shahid Ahmadi Roshan Program, she has actively contributed to research and planning initiatives in commerce, logistics, and industrial systems.

Research Focus

Her research focuses on supply chain optimization, decision-making techniques, emergency medical services network design, data mining applications, and machine learning in supply chain forecasting. She has worked extensively on designing robust and sustainable supply chain networks under uncertainty, ranking suppliers, and preprocessing methods for diverse data types.

Author Metrics:

  • Publications in High-Impact Journals, including Science of the Total Environment (IF: 8.2, Q1) and Journal of Industrial and Systems Engineering (Q3)
  • Conference Presentations, including the 17th Iranian International Industrial Engineering Conference on emergency medical services and supply chain disruption management
  • Bibliometric Analysis Expertise using VOSviewer and CiteSpace

Awards and Honors:

  • Distinguished Researcher, Shahid Ahmadi Roshan Program, Iran’s National Elites Foundation
  • Exceptional Talent Admission, Ph.D. Program, Iran University of Science and Technology\

Publication Top Notes

1. Towards a Sustainable Viticultural Supply Chain under Uncertainty: Integration of Data Envelopment Analysis, Artificial Neural Networks, and a Multi-Objective Optimization Model

  • Journal: Science of the Total Environment (Impact Factor: 8.2, Q1)
  • Authors: Zahra Sadat Seyedzadeh, Mohammad Saeed Jabalameli, Ehsan Dehghani
  • Publication Year: 2025
  • Abstract: This study integrates data envelopment analysis (DEA)artificial neural networks (ANNs), and a multi-objective optimization model to develop a sustainable viticultural supply chain under uncertainty. It provides a robust framework for improving efficiency, resilience, and environmental sustainability in the wine industry.

2.  A Robust Scenario-Based Model for Locating Emergency Medical Services Bases

  • Journal: Journal of Industrial and Systems Engineering (Impact Factor: 0.694, Q3)
  • Authors: Zahra Sadat Seyedzadeh, Mohammad Saeed Jabalameli, Ehsan Dehghani
  • Abstract: This research proposes a robust scenario-based model for optimizing emergency medical services (EMS) base locations, addressing uncertainty, demand fluctuations, and resource allocation efficiency to enhance emergency response times and service coverage.

3.  Emergency Medical Services Network Design under Uncertainty

  • Conference: 17th Iranian International Industrial Engineering Conference
  • Authors: Zahra Sadat Seyedzadeh, Mohammad Saeed Jabalameli, Saeed Yaghoubi
  • Abstract: The study focuses on designing a resilient EMS network, incorporating stochastic demand modeling and robust optimization techniques to improve emergency response effectiveness in unpredictable environments.

4. Emergency Medical Services Supply Chain Network Design and Backup Services under Disruption

  • Conference: 17th Iranian International Industrial Engineering Conference
  • Authors: Zahra Sadat Seyedzadeh, Mohammad Saeed Jabalameli
  • Abstract: This paper examines EMS network vulnerabilities and proposes a backup service strategy to ensure continuity of care and resource allocation in cases of service disruptions due to disasters or infrastructure failures.

Conclusion

Zahra Sadat Seyedzadeh is a strong candidate for a Best Researcher Award, given her exceptional research output, interdisciplinary expertise, and recognized academic achievements. She has demonstrated high-impact research in supply chain optimization, EMS design, and machine learning applications, with publications in top-tier journals.

To further strengthen her research profile, she could focus on international collaborations, real-world applications of her models, and leadership roles in large research projects. Overall, her contributions to industrial engineering and systems optimization make her a highly deserving candidate for the award.

Pardis Roozkhosh | Supply Chain | Best Researcher Award

Dr. Pardis Roozkhosh | Supply Chain | Best Researcher Award

Lecturer at Ferdowsi University of Mashhad, Iran.

Dr. Pardis Roozkhosh is a distinguished researcher and academic in industrial management and operations research, with expertise in resilient supply chains, additive manufacturing, and machine learning applications. She has an extensive background in optimization, logistics, and decision-making systems, with numerous research contributions and teaching experience in prestigious institutions across Iran. Her work integrates advanced computational techniques with industrial engineering solutions, making a significant impact in academia and applied research.

Professional Profile:

Scopus

Orcid

Google Scholar

Education Background

  • Ph.D. in Industrial Management (Operations Research) – Ferdowsi University of Mashhad, Iran (2024)
    • Thesis: Resilient Supply Chain with Additive Manufacturing Capability Using Machine Learning Approach
    • GPA: 4.0/4.0 (19.04/20)
  • M.S. in Industrial Engineering (Systems Optimization) – Sadjad University of Mashhad, Iran (2018)
    • Thesis: Solving Partial Inspection Problems in Multistage Systems Using Double Sampling Plans Considering Uncertainty in Costs
  • B.S. in Industrial Engineering – Birjand University of Technology, Iran (2015)

Professional Development

Dr. Roozkhosh has held teaching and research positions at Ferdowsi University of Mashhad, Allameh Tabataba’i University, Sadjad University of Mashhad, and Kosar University of Bojnourd. She has taught statistics, probability theory, financial management, inventory control, and mathematics, guiding students in industrial management and engineering disciplines.

As a Research Assistant at Ferdowsi University of Mashhad since 2020, she has worked on logistics and transportation projects, including a study on Razavi Khorasan’s logistics systems. Additionally, she collaborated with the University of Sydney on Agrovoltaic modeling, optimizing solar panel applications in agricultural settings.

Research Focus

  • Resilient Supply Chain Management
  • Operations Research and Optimization Techniques
  • Machine Learning and Artificial Intelligence in Industrial Systems
  • Logistics and Transportation Modeling
  • Additive Manufacturing and Smart Production Systems
  • Simulation Techniques (Monte-Carlo, System Dynamics, etc.)

Author Metrics:

  • Google Scholar: [Profile Link]
  • h-Index: [Current h-Index]
  • Total Citations: [Number of Citations]
  • Reviewed Papers: IEEE Access, Journal of Simulation, International Journal of Productivity and Performance Management

Awards and Honors:

  • Alborz Prize (Iranian Nobel Prize) – 2024 (Oldest and most prestigious academic award in Iran)
  • Ranked in the Top 5% of Students in Iran’s Ph.D. Entrance Exam (Conquer Exam) – 2019
  • Executive Assistant at Journal of Systems Thinking in Practice (JSTINP) – 2022
  • Designed and Registered a Board Game Based on Optimization Algorithms – 2021

Publication Top Notes

1. MLP-based Learnable Window Size for Bitcoin Price Prediction

  • Authors: S. Rajabi, P. Roozkhosh, N. M. Farimani
  • Journal: Applied Soft Computing
  • Citations: 59
  • Year: 2022
  • Summary: This study utilizes a Multi-Layer Perceptron (MLP)-based model to dynamically adjust window sizes for improved Bitcoin price prediction using deep learning techniques.

2. Blockchain Acceptance Rate Prediction in the Resilient Supply Chain with Hybrid System Dynamics and Machine Learning Approach

  • Authors: P. Roozkhosh, A. Pooya, R. Agarwal
  • Journal: Operations Management Research 16 (2), 705-725
  • Citations: 49*
  • Year: 2023
  • Summary: This research integrates system dynamics and machine learning to predict blockchain adoption rates in resilient supply chains, enhancing digital transformation strategies.

3. A New Supply Chain Design to Solve Supplier Selection Based on Internet of Things and Delivery Reliability

  • Authors: A. Modares, M. Kazemi, V. B. Emroozi, P. Roozkhosh
  • Journal: Journal of Industrial and Management Optimization 19 (11), 7993-8028
  • Citations: 37
  • Year: 2023
  • Summary: The study presents a novel IoT-enabled supply chain model, improving supplier selection and delivery reliability through optimization techniques.

4. Partial Inspection Problem with Double Sampling Designs in Multi-Stage Systems Considering Cost Uncertainty

  • Authors: T. H. Hejazi, P. Roozkhosh
  • Journal: Journal of Industrial Engineering and Management Studies 6 (1), 1-17
  • Citations: 21
  • Year: 2019
  • Summary: This work introduces a double sampling inspection strategy in multi-stage production systems, addressing cost uncertainties in quality control.

5. Designing a New Model for the Hub Location-Allocation Problem Considering Tardiness Time and Cost Uncertainty

  • Authors: P. Roozkhosh, N. Motahari Farimani
  • Journal: International Journal of Management Science and Engineering Management 18 (1)
  • Citations: 20
  • Year: 2023
  • Summary: A mathematical optimization model is proposed for hub location-allocation problems, factoring in time delays and cost variability in logistics networks.

Conclusion

Dr. Pardis Roozkhosh is an outstanding researcher in resilient supply chains, AI applications in industrial systems, and logistics optimization. Her Alborz Prize, high-impact publications, interdisciplinary expertise, and leadership in academic peer review make her a strong candidate for the Best Researcher Award.

To further strengthen her profile, she can enhance international collaborations, increase citations, secure more research funding, and actively participate in global conferences. Given her achievements and ongoing contributions, she is well-deserving of this award and is a leading academic in industrial management and operations research.