Nazli Tokatli | Computer Science and Artificial Intelligence | Innovative Research Award

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Innovative Research Award

Nazli Tokatli — Istanbul Health and Technology University,  Turkey

Nazli Tokatli
Affiliation Istanbul Health and Technology University
Country Turkey
Scopus ID 57212214663
Documents 23
Citations 88
h-index 5
Subject area Computer Science and Artificial Intelligence
Event International Research Scientist Awards
ORCID 0000-0001-9840-4211

Nazli Tokatli is a researcher affiliated with Istanbul Health and Technology University, Turkey, whose scholarly profile is associated with computer science and artificial intelligence. The available bibliometric information records 23 documents, 88 citations, and an h-index of 5 in Scopus. These indicators provide a quantitative snapshot of indexed research output and citation activity, while the researcher’s publication record offers the appropriate basis for examining individual contributions, thematic interests, and scholarly relevance. The Innovative Research Award recognizes research-related achievements within the context of the International Research Scientist Awards. [1]

Abstract

Nazli Tokatli, affiliated with Istanbul Health and Technology University in Turkey, has a research profile associated with computer science and artificial intelligence. Scopus records 23 documents, 88 citations, and an h-index of 5, providing quantitative indicators of scholarly publication and citation activity. This article summarizes the available profile information and outlines how research contributions may be assessed through publication relevance, methodological rigor, reproducibility, and potential applications. The Innovative Research Award provides a recognition framework for examining research achievements. Detailed assessment requires verification of individual publications, their subject matter, and documented contributions to the relevant scientific fields. [2]

Keywords

Computer science, artificial intelligence, machine learning, computational methods, intelligent systems, data analysis, algorithm development, and research innovation. These terms describe potential indexing categories rather than verified subjects of specific publications. The final keyword selection should be refined against the titles, abstracts, and keywords of the researcher’s indexed articles to ensure accurate representation of actual research themes.[3]

Introduction

Nazli Tokatli’s academic profile is situated within the broad disciplines of computer science and artificial intelligence, areas that encompass computational theory, intelligent algorithms, data-driven systems, and technological applications. Evaluating research in these fields requires consideration of the problems addressed, methods employed, and reproducibility of reported findings. Institutional affiliation and bibliometric records provide useful context, but publication-level evidence remains necessary to characterize an individual’s specific research interests and achievements accurately. [1]

Research Profile

Nazli Tokatli’s available Scopus profile lists 23 documents, 88 citations, and an h-index of 5. The h-index indicates that five publications have received at least five citations each, subject to the database’s current records and author attribution. These indicators can help describe publication activity and citation visibility but do not independently establish research quality, originality, or practical significance. Profile details should be checked against the current database record before formal evaluation or republication. [1] [2]

Research Contributions

Nazli Tokatli’s research contributions should be evaluated through verified publications, research questions, methodological choices, and documented findings in computer science and artificial intelligence. Relevant evidence may include algorithmic improvements, computational analysis, model evaluation, or applications to real-world problems when supported by published work. Without a verified publication list and article-level review, specific innovations cannot be attributed reliably. Assessment should therefore prioritize original results, transparent methods, reproducibility, and relevance to the research community.[3]

Publications

Nazli Tokatli’s Scopus author record reports 23 indexed documents. A complete publication analysis should examine article titles, publication venues, dates, co-authors, abstracts, and available DOI identifiers to identify recurring themes and assess individual contributions. Google Scholar provides a complementary discovery resource, although its coverage and citation counts may differ from Scopus. Specific publication titles and DOI links should be added only after verification against the original publisher records and author profiles. [1]

Research Impact

Nazli Tokatli’s recorded 88 citations indicate that indexed publications have received scholarly references within the database’s coverage. Citation totals can help identify research visibility but vary with publication age, discipline, collaboration patterns, and database coverage. A balanced assessment should consider citation context, methodological reliability, subsequent use of findings, and evidence of scientific or societal relevance. Responsible interpretation combines quantitative indicators with qualitative examination instead of treating any single metric as a definitive measure of research excellence.

Award Suitability

Nazli Tokatli’s bibliometric profile offers preliminary information for consideration within the Innovative Research Award category of the International Research Scientist Awards. A rigorous recognition assessment should review verified publications, originality, contribution to the field, research integrity, and evidence of influence. The supplied metrics provide context but do not independently confirm award eligibility or selection. Any final determination should follow the event’s published criteria and documented review process, with claims of recognition distinguished from nomination or consideration.[3]

Conclusion

Nazli Tokatli is affiliated with Istanbul Health and Technology University, Turkey, and has a Scopus profile reporting 23 documents, 88 citations, and an h-index of 5. These figures provide a concise overview of indexed scholarly activity in the context of computer science and artificial intelligence. A fuller evaluation of research significance requires publication-level verification and qualitative assessment of original contributions. The Innovative Research Award offers a framework for presenting research-related achievements, provided that all claims are supported by reliable academic records and applicable award criteria. [1]

References

    1. Elsevier. (n.d.). Scopus author details: Nazli Tokatli, Author ID 57212214663. Scopus. Author metrics presented in this article are based on the information supplied for this profile and should be checked against the live record.
      https://www.scopus.com/authid/detail.uri?authorId=57212214663
    2. ORCID. (n.d.). Nazli Tokatli: ORCID researcher identifier 0000-0001-9840-4211. ORCID.
      https://orcid.org/0000-0001-9840-4211
    3. Google. (n.d.). Google Scholar author profile. Google Scholar. Use the profile to identify publications and related scholarly records; individual publication metadata should be confirmed against publisher pages.
      https://scholar.google.com/citations?user=sOqjhTsAAAAJ&hl=en&oi=sra

Jobish Vallikavungal Devassia | Computer Science | Best Researcher Award

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Prof. Dr. Jobish Vallikavungal Devassia | Computer Science | Best Researcher Award

Professor | Tecnológico De Monterrey | Mexico

Prof. Dr. Jobish Vallikavungal Devassia is a distinguished researcher in Computer Science, specializing in scheduling algorithms, operations research, and optimization for flexible job-shop and parallel machine systems. He has authored over 10 high-impact publications in top-tier journals, including Computers & Industrial Engineering, International Journal of Production Research, and IEEE Access, accumulating more than 112 citations. His work integrates advanced techniques such as rough sets, multidimensional fuzzy logic, and dynamic scheduling methods, often in collaboration with international scholars from Mexico, Spain, and France. His research advances efficient industrial operations, resource optimization, and practical applications in manufacturing and logistics, impacting both academia and industry globally.

 

Citation Metrics (Google Scholar)

400

300

200

100

0

Citations
112

Documents
10

h-index
5

🟦 Citations 🟥 Documents 🟩 h-index

View Scopus Profile
               View ORCID Profile
             View Google Scholar Profile

Featured Publications

The generalized flexible job shop scheduling problem.

– Computers & Industrial Engineering. (2021). Cited By: 50

Flexible job-shop scheduling problem with resource recovery constraints.

– International Journal of Production Research. (2018). Cited By: 41

A parallel machine batch scheduling problem in a brewing company.

– The International Journal of Advanced Manufacturing Technology. (2016). Cited By: 32

Ei Mehdi Chakour | Computer Science | Research Excellence Award

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Dr. Ei Mehdi Chakour | Computer Science | Research Excellence Award

Research Postdoc | Université Sidi Mohamed Ben Abdellah | Morocco

Dr. Ei Mehdi Chakour is a researcher at Université Sidi Mohamed Ben Abdellah, Fez, Morocco, specializing in medical image analysis and deep learning applications for ophthalmology, particularly diabetic retinopathy detection. With four peer-reviewed publications and 16 citations, Dr. Chakour has contributed to advancements in retinal image segmentation, enhancement, and severity classification using dynamic preprocessing, mathematical morphology, and transfer learning techniques. His collaborative work involves 11 co-authors across international conferences and journals, reflecting a strong commitment to interdisciplinary research. Through the development of mobile-based deep learning systems, his work demonstrates significant societal impact by enabling earlier, accessible, and accurate diabetic retinopathy screening.

Citation Metrics (Scopus)

80

60

40

20

0

Citations
16

Documents
4

h-index
2

🟦 Citations 🟥 Documents 🟩 h-index

View Scopus Profile
             View ORCID Profile

Featured Publications


Mobile‑based deep learning system for early detection of diabetic retinopathy.

– Intelligence‑Based Medicine. Advance online publication. (2025). 

Transfer learning for severity and stages detection of diabetic retinopathy.

-Embedded Systems and Artificial Intelligence (ESAI) . (2024).

Blood vessel segmentation of retinal fundus images using dynamic preprocessing and mathematical morphology.

– International Conference on Control, Decision and Information Technologies (CoDIT). (2022). 

Jafar Fathali | Operations Research | Best Researcher Award

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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.