Mehri Bagherian | Robust Optimization | Women Researcher Award

Women Researcher Award

Mehri Bagherian
University of Guilan
Mehri Bagherian
Affiliation University of Guilan
Country Iran
Scopus ID 36105020600
Documents 18
Citations 84
h-index 5
Subject Area Robust Optimization
Event International Research Scientist Awards
ORCID 0000-0002-6870-8502

Mehri Bagherian is associated with the University of Guilan and has contributed to the field of robust optimization and decision sciences through scholarly publications and applied analytical research. Her academic profile demonstrates interdisciplinary engagement in optimization modeling, operational research, and mathematical decision-making methods. The recognition under the International Research Scientist Awards highlights her ongoing contributions to academic research and scientific development.[1]

Abstract

This article presents an overview of the academic profile and research activities of Mehri Bagherian in the area of robust optimization and operations research. Her scholarly work focuses on analytical optimization models, uncertainty management, and strategic decision-making methodologies relevant to engineering and management sciences. The article also evaluates her research influence, publication record, and suitability for recognition through the Women Researcher Award under the International Research Scientist Awards program. Her academic contributions reflect continued engagement in quantitative research and interdisciplinary scientific development.[1][2]

Keywords

Robust Optimization, Operations Research, Decision Sciences, Mathematical Modeling, Optimization Theory, Scientific Research, Women Researcher Award, Quantitative Analysis, Engineering Management, Research Recognition.

Introduction

Robust optimization has become an important research domain for addressing uncertainty and improving decision-making reliability in complex systems. Researchers working in this field contribute to optimization methodologies that support industrial planning,[1] Academic recognition programs such as the Women Researcher Award acknowledge researchers whose work contributes to scientific advancement and interdisciplinary innovation. [4]

Research Profile

Mehri Bagherian is affiliated with the University of Guilan in Iran and is academically associated with optimization-focused research areas. Her Scopus author profile indicates scholarly contributions in robust optimization and related quantitative methodologies. Her publication record demonstrates engagement in applied mathematical and operational research topics relevant to modern industrial systems.[1]

Research Contributions

The research contributions of Mehri Bagherian primarily involve optimization techniques designed to improve system reliability and strategic planning under uncertainty. Her work aligns with modern developments in operational analysis and robust decision frameworks used in engineering and management sciences.[2]

  • Development of optimization-based analytical models for uncertain environments.
  • Research on operational efficiency and mathematical decision-support systems.
  • Application of quantitative methods in engineering and industrial planning.
  • Contribution to interdisciplinary optimization and management studies.

Publications

The publication topics associated with Mehri Bagherian primarily focus on robust optimization, operational research, mathematical modeling, and decision-making under uncertainty. Her studies examine optimization strategies for improving efficiency, reliability, and analytical performance in industrial and engineering systems. The research contributes to quantitative problem-solving methodologies applicable to management sciences, logistics, and strategic operational planning.[1]

Research Impact

The research impact of Mehri Bagherian can be observed through indexed citations and continued publication activity in optimization-related domains. Citation-based indicators provide evidence of scholarly visibility and demonstrate that her work contributes to ongoing academic discussions within operational research and quantitative decision-making fields.[3] Such research areas remain relevant across engineering, industrial management, and applied mathematical sciences.[2]

Award Suitability

The Women Researcher Award recognizes individuals demonstrating sustained academic engagement, research productivity, and scholarly contribution within their respective disciplines. Mehri Bagherian’s documented publication activity, citation metrics, and specialization in robust optimization align with the evaluation criteria commonly associated with international academic recognition programs.[4]

Conclusion

Mehri Bagherian has established an academic profile centered on robust optimization and quantitative analytical research. Her indexed publications, citation record, and research engagement indicate meaningful participation in operational research and decision sciences. The Women Researcher Award article highlights her scholarly contributions and reflects the broader significance of interdisciplinary optimization research in contemporary academic environments.[1][4]

References

    1. Elsevier. (n.d.). Scopus author details: Mehri Bagherian, Author ID 36105020600. Scopus.
      https://www.scopus.com/authid/detail.uri?authorId=36105020600
    2. Bagherian, M. (2018). Unmanned aerial vehicle terrain following/terrain avoidance/threat avoidance trajectory planning using fuzzy logic. 
      https://www.researchgate.net/publication/323978826_Unmanned_Aerial_Vehicle_Terrain_FollowingTerrain_AvoidanceThreat_Avoidance_trajectory_planning_using_fuzzy_logic
    3. ORCID. (n.d.). Mehri Bagherian ORCID profile.
      https://orcid.org/0000-0002-6870-8502
    4. Zardashti, R., & Bagherian, M. (2009). A new model for optimal TF/TA flight path design problem.
      https://www.semanticscholar.org/paper/A-new-model-for-optimal-TF-TA-flight-path-design-Zardashti-Bagherian/40ac87c7d8726c7ef219048b6ae67c3a5385c535

Jafar Fathali | Operations Research | Best Researcher Award

Prof.Jafar Fathali | Operations Research | Best Researcher Award

University Professor at Shahrood University of Technology, Iran 

Professor Jafar Fathali 🎓 is a renowned academic in Operations Research and Applied Mathematics, currently serving as a Professor at the Faculty of Mathematical Sciences, Shahrood University of Technology, Iran 🇮🇷. With decades of contribution to location theory, heuristic optimization, and scheduling problems , he has become a distinguished figure in computational mathematics. A prolific researcher, Prof. Fathali has authored over 50+ peer-reviewed journal articles  in internationally recognized platforms such as EJOR, Soft Computing, and Computers & Industrial Engineering. He is actively involved in scholarly communities including the Iranian Mathematical Society and the Iranian Operations Research Society . Beyond research, he contributes as a referee for leading journals, mentoring students and advancing mathematical modeling in real-world applications. His academic journey is defined by innovation, persistence, and leadership , making him a vital contributor to the global research ecosystem .

🔹Professional Profile

SCOPUS

ORCID

📘 Education & Experience

Prof. Jafar Fathali holds a BSc in Applied Mathematics from Ferdowsi University of Mashhad , an MSc from Amirkabir University of Technology , and earned his Ph.D. in Applied Mathematics from Ferdowsi University in 2005 . With a solid foundation in mathematical theories, he began teaching at Shahrood University of Technology, where he advanced to a full professorship . Over the years, he has taught a wide array of undergraduate and graduate courses, including Operations Research, Advanced Linear & Nonlinear Programming, Combinatorial Optimization, and Numerical Analysis . His expertise spans both theoretical frameworks and practical applications, equipping students with problem-solving and analytical skills 🔍. With his academic and mentoring experience, Prof. Fathali has played a key role in shaping Iran’s next generation of mathematicians and operations research .

🚀 Professional Development

Professor Fathali has shown remarkable growth in academia through innovative research, interdisciplinary collaborations, and active journal reviewing . He has reviewed articles for top-tier journals such as European Journal of Operational Research, Transportation Research Part E, Soft Computing, and Optimization Methods and Software . He is a member of the Iranian Mathematical Society, Iranian Operations Research Society, and Iranian Statistics Society , reflecting his deep involvement in the academic community. His ability to integrate fuzzy logic, graph theory, and metaheuristic algorithms into practical models has enhanced decision-making strategies across industries . Prof. Fathali has also co-developed numerous hybrid algorithms involving genetic algorithms, ant colony optimization, and variable neighborhood search for solving complex problems . His active mentorship, editorial contributions, and research collaborations are key indicators of a career deeply committed to academic excellence, growth, and innovation .

🔬 Research Focus

Professor Jafar Fathali’s research is firmly rooted in Operations Research, with an emphasis on location theory , combinatorial optimization, and scheduling problems . He specializes in designing algorithms for complex decision-making models such as the p-median, p-center, and core location problems across graphs and trees . His methods employ heuristic techniques, metaheuristics (e.g., genetic algorithms , particle swarm optimization , and fuzzy logic  to model real-world uncertainties in logistics, network design, and resource allocation. Prof. Fathali has also explored inverse and semi-obnoxious location problems, expanding the scope of location models to account for service inefficiencies and backup facilities . His works address both theoretical and applied aspects, blending mathematical rigor with practical implementation . With continuous innovations in modeling and optimization, his contributions have significantly advanced the field of applied mathematics and operations research .

🏆 Awards & Honors

While specific awards and honors for Professor Jafar Fathali are not individually listed, his academic reputation is underscored by the impact and volume of his scholarly work . Having published in high-impact journals like European Journal of Operational Research and Soft Computing, his research has earned wide recognition and citation 🏆. Being a referee for over a dozen international journals and collaborating with well-known scholars such as R.E. Burkard, indicates peer acknowledgment and respect . His sustained publication record, editorial engagements, and frequent invitations to review complex mathematical models highlight his research excellence and international credibility . His contributions have helped define solutions for complex logistics and scheduling challenges, securing his place among Iran’s most influential operations research . With ongoing recognition from both academic institutions and scholarly circles, Prof. Fathali continues to be a role model for aspiring mathematicians and OR specialists globally .

🔹Publication of Top Notes

1.Convexity and sensitivity analysis of the median line location problem

Authors: Mehdi Golpayegani, Jafar Fathali
Year: 2025
Journal: International Journal of Systems Science: Operations & Logistics
DOI: 10.1080/23302674.2025.2529967

2.Greedy algorithms for the inverse center line location problem

Authors: Mehdi Golpayegani, Jafar Fathali
Year: 2025
Journal: Expert Systems with Applications
DOI: 10.1016/j.eswa.2025.129064

3.Fuzzy balanced allocation problem with efficiency on facilities

Authors: Azam Azodi, Jafar Fathali, Mojtaba Ghiyasi, Tahereh Sayar
Year: 2023
Journal: Soft Computing
DOI: 10.1007/s00500-022-07695-4

4.The balanced 2-median and 2-maxian problems on a tree

Authors: Jafar Fathali, Mehdi Zaferanieh
Year: 2023
Journal: Journal of Combinatorial Optimization
DOI: 10.1007/s10878-023-00997-9

5.Finding the absolute and vertex center of a fuzzy tree

Authors: Fatemeh Taleshian, Jafar Fathali, Nemat Allah Taghi-Nezhad
Year: 2022
Journal: Transportation Letters
DOI: 10.1080/19427867.2021.1909797

6.The minimum information approach to the uncapacitated p-median facility location problem

Authors: Mehdi Zaferanieh, Maryam Abareshi, Jafar Fathali
Year: 2022
Journal: Transportation Letters
DOI: 10.1080/19427867.2020.1864595

7.Fuzzy Balanced Allocation Problem with Efficiency on Servers

Authors: Azam Azodi, Jafar Fathali, Mojtaba Ghiyasi, Tahereh Sayar
Year: 2021
Type: Preprint
DOI: 10.21203/rs.3.rs-444116/v1

8.Inverse and reverse balanced facility location problems with variable edge lengths on trees

Authors: Shahede Omidi, Jafar Fathali, Morteza Nazari
Year: 2020
Journal: OPSEARCH
DOI: 10.1007/s12597-019-00428-6

9.Finding an optimal core on a tree network with M/G/c/c state-dependent queues

Authors: Mehrdad Moshtagh, Jafar Fathali, James MacGregor Smith, Nezam Mahdavi-Amiri
Year: 2019
Journal: Mathematical Methods of Operations Research
DOI: 10.1007/s00186-018-0651-3

10.The Stochastic Queue Core problem, evacuation networks, and state-dependent queues

Authors: Mehrdad Moshtagh, Jafar Fathali, J. MacGregor Smith
Year: 2018
 Journal: European Journal of Operational Research
 DOI: 10.1016/j.ejor.2018.02.026

🏁Conclusion

Professor Fathali’s research stands out due to its mathematical rigor, practical relevance, and algorithmic innovation. His work significantly advances the optimization and decision sciences field, contributing both theoretical frameworks and practical solutions. These qualities, combined with his sustained academic output, collaborative spirit, and international impact, make him an ideal candidate for the Best Researcher Award.

Prof. Dr. Wei Fang | Analytics Award | Best Researcher Award

Prof. Dr. Wei Fang | Analytics Award | Best Researcher Award

Prof. Dr. Wei Fang, Nanjing University of Information Science & Technology, China

Prof. Dr. Wei Fang is a Professor in the Department of Computer Science at Nanjing University of Information Science & Technology, China, and a member of the State Key Laboratory for Novel Software Technology, Nanjing University. He holds a Ph.D. and M.Sc. in Computer Science from Soochow University. Wei was a visiting scholar at the University of Florida in 2015-2016. His research interests include Artificial Intelligence, Big Data, Data Mining, and Meteorological Information Processing. He has led several research projects funded by the National Natural Science Foundation of China and is an active reviewer for international journals. Wei is a senior member of the CCF and ACM.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

Summary of Suitability for Best Researcher Award – Prof. Wei Fang

Prof. Wei Fang of Nanjing University of Information Science & Technology stands out as a highly meritorious candidate for the Best Researcher Award. With a solid academic foundation, national and international research exposure, and extensive contributions in Artificial Intelligence, Big Data, Computer Vision, and Applied Meteorology, his work bridges theoretical innovation with real-world application.

🎓 Education

  • Ph.D. in Computer Science – Soochow University, China

  • M.Sc. in Computer Science – Soochow University, China

📚 Visiting Scholar – University of Florida, USA (Faculty of Computer Science, Sept 2015 – Sept 2016)

💼 Work Experience

  • 👨‍🏫 Professor, Department of Computer Science, NUIST

  • 🧪 Affiliated with the State Key Lab for Novel Software Technology, Nanjing University

  • 🤝 Program Committee Member for multiple international conferences

  • 📝 Reviewer for various international journals

  • 🌍 International Research Scientist

🏆 Achievements & Honors

  • 🧠 Recognized for impactful research in:

    • Artificial Intelligence 🤖

    • Big Data & Cloud Computing ☁️📊

    • Computer Vision 👁️

    • Applied Meteorology 🌦️

  • 🔬 Project Leader of national and industrial research projects funded by:

    • National Natural Science Foundation of China

    • Guodian Nari Nanjing Control System Co., Ltd.

    • Baoshan Iron and Steel Co., Ltd.

  • 🎖️ Senior Member of CCF (China Computer Federation) & ACM

  • 📈 Cited in SCI-indexed journals

Publication Top Notes:

A rapid learning algorithm for vehicle classification

CITED: 562

A Method for Improving CNN-Based Image Recognition Using DCGAN.

CITED: 230

Efficient feature selection and classification for vehicle detection

CITED: 220

A survey of big data security and privacy preserving

CITED: 117

Survey on research of RNN-based spatio-temporal sequence prediction algorithms

CITED: 100