Jafar Fathali | Operations Research | Best Researcher Award

Prof.Jafar Fathali | Operations Research | Best Researcher Award

University Professor at Shahrood University of Technology, Iranย 

Professor Jafar Fathali ๐ŸŽ“ 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 ๐Ÿ‡ฎ๐Ÿ‡ท. 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 articlesย  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 .

๐Ÿ”นProfessional Profile

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๐Ÿ“˜ 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 ๐Ÿ”. With his academic and mentoring experience, Prof. Fathali has played a key role in shaping Iranโ€™s next generation of mathematicians and operations research .

๐Ÿš€ 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 .

๐Ÿ”ฌ Research Focus

Professor Jafar Fathaliโ€™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 logicย  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 .

๐Ÿ† 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 ๐Ÿ†. 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 .ย 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 researchย . 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 .

๐Ÿ”นPublication 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
ย Journal: European Journal of Operational Research
ย DOI: 10.1016/j.ejor.2018.02.026

๐ŸConclusion

Professor Fathaliโ€™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.

Dr.Syed Luqman Ali | Bioinformatics | Excellence in Research

Dr.Syed Luqman Ali |Bioinformatics| Excellence in Research

Researcher , Abdul Wali khan university Mardan , Pakistan

Syed Luqman Ali ๐Ÿ‡ต๐Ÿ‡ฐ is a passionate computational biologist and lecturer dedicated to vaccine design, drug discovery, and cancer biomarker research. With a strong foundation in bioinformatics, immunoinformatics, and proteomics, he actively contributes to tackling infectious diseases and cancer ๐ŸŽฏ. Currently serving as a part-time lecturer at Metanoia College ๐Ÿง‘โ€๐Ÿซ and a Research Associate at Abdul Wali Khan University Mardan ๐Ÿ›๏ธ, Syed thrives in multidisciplinary collaboration. His research integrates molecular modeling, machine learning, and systems biology tools ๐Ÿง . A proactive scholar, reviewer, and content creator โœ๏ธ, he aims to shape the future of next-generation therapeutics and public health solutions. ๐Ÿ’Š๐Ÿงช.

Professional Profile

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Education & Experience

Syed Luqman Ali earned an MPhil and BS in Biochemistry from Abdul Wali Khan University Mardan ๐Ÿ“˜, with research focusing on cancer biomarkers, machine learning, and vaccine design ๐Ÿ’ก. He also holds a diploma in Digital Information Technology from Peshawar ๐Ÿ–ฅ๏ธ. As a part-time lecturer ๐Ÿง‘โ€๐Ÿซ at Metanoia College, he teaches bioinformatics, microbiology, and molecular biology. His role as a Research Associate at AWKUM involves in silico vaccine and drug development, proteomic analysis, and transcriptomics ๐Ÿงฌ. With hands-on experience in wet-lab and computational techniques, Syed combines education and research to drive innovation in biomedical sciences ๐Ÿงซ๐Ÿ”.

Professional Development

Syed Luqman Ali has actively pursued continuous development through global certifications and tech training ๐ŸŽ“. He holds a TEFL certificate for English proficiency, alongside certifications in R, Python, and Linux for data analysis ๐Ÿ“Š๐Ÿ’ป. His technical toolkit includes ClusPro, Gromacs, PyRx, AutoDock, Pymol, and SWISS-MODEL for molecular modeling ๐Ÿงช. He’s completed workshops on vaccine development, health safety ๐Ÿงค, and academic research via the Web of Science Academy ๐ŸŒ. Syed also gained skills in scientific writing and digital communication โœ๏ธ via DigiSkills. His proactive learning attitude reflects a commitment to excellence in computational biology and medical research ๐ŸŒŸ๐Ÿง .

Research Focus

Syed Luqman Aliโ€™s research centers around computational vaccine and drug design ๐Ÿ’‰๐Ÿงฌ, cancer biomarker discovery, and systems biology. He applies immunoinformatics, proteomics, and transcriptomics to develop novel therapeutics targeting infectious diseases and tumors ๐ŸŽฏ. Skilled in docking, molecular dynamics, and HLA ligand prediction, Syed integrates tools like ClusPro, Gromacs, and Desmond in his workflows ๐Ÿ’ป๐Ÿงช. His work spans gene expression profiling, KEGG pathway analysis, and in silico screening, enabling precision biomedicine ๐Ÿง . Through interdisciplinary methods and machine learning applications ๐Ÿค–, he contributes to next-gen innovations in health, disease resistance, and therapeutic development ๐Ÿš€.

Awards & Honors

Syed Luqman Ali has received notable accolades, including the Young Scientist Award ๐Ÿ† for his outstanding contributions to biomedical research. He has published multiple papers in Q1 and Q2 peer-reviewed journals ๐Ÿ“ฐ and serves as a reviewer for respected journals such as Frontiers in Immunology, World Journal of Gastroenterology, and Applied Biochemistry & Biotechnology ๐Ÿง‘โ€๐Ÿ”ฌ. Syedโ€™s interdisciplinary research has gained international recognition, particularly in cancer diagnostics and computational vaccine development ๐ŸŒ. With a strong publication record, teaching excellence, and peer-review activities ๐Ÿง‘โ€๐Ÿซ, he stands out as a rising star in bioinformatics and translational research ๐Ÿ”ฌ๐ŸŽ–๏ธ.

Publication Top Notes

1. Vaccinomics-based Next-Generation Multi-Epitope Chimeric Vaccine Models Prediction Against Leishmania tropica

Authors: S Aiman, A Ahmad, AA Khan, AM Alanazi, A Samad, SL Ali, et al.
Journal: Frontiers in Immunology, Vol. 14, 2023 | Cited by: 27
Summary: This study applied subtractive proteomics and immunoinformatics to develop multi-epitope vaccine constructs targeting Leishmania tropica. The proposed vaccines were validated via molecular docking, highlighting their therapeutic potential.

2. Mutational Screening of GDAP1 in Dysphonia Associated with Charcot-Marie-Tooth Disease

Authors: U Manzoor, A Ali, SL Ali, et al.
Journal: Journal of Genetic Engineering and Biotechnology, 21(1):119, 2023 | Cited by: 26
Summary: Focuses on GDAP1 gene mutations in patients with Charcot-Marie-Tooth disease and associated dysphonia. Findings provide insight into phenotype-genotype correlations in neuropathic disorders.

3. Genomic Annotation and Immunoinformatics-Guided Vaccine Design Against Songling Virus

Authors: SL Ali, A Ali, A Alamri, M Dusmagambetov, et al.
Journal: Frontiers in Immunology, Vol. 14, 2023 | Cited by: 21
Summary: This work involves screening the entire genome of the Songling virus to identify novel vaccine targets and construct a computational multi-epitope vaccine using reverse vaccinology.

4. Biological Modalities in Diabetes Management โ€“ A Comprehensive Review

Authors: A Ali, U Manzoor, SL Ali, et al.
Journal: Journal of Population Therapeutics & Clinical Pharmacology, 30(18), 2948โ€“70, 2023 | Cited by: 11
Summary: Reviews current and future bio-based therapies for various types of diabetes, including peptide therapies, gene editing, and stem cell interventions.

5. IgG Antibodies and Their Role in Food Tolerance & Autoimmune Disorders

Authors: A Ali, U Manzoor, SL Ali, et al.
Journal: Int. J. of Natural Medicine and Health Sciences, 3(1), 2023 | Cited by: 10
Summary: Investigates how IgG antibodies and their receptors influence food tolerance and autoimmune responses, with potential implications in immunodiagnostics.

6. AI-Powered Tuberculosis Vaccine Candidate Development

Authors: L Zhuang, A Ali, SL Ali, et al.
Journal: Infectious Medicine, 3(4):100148, 2024 | Cited by: 7
Summary: Integrates AI and CAD to design next-gen multi-epitope vaccines targeting tuberculosis. Emphasizes structural modeling and immune simulation workflows.

7. ZL9810L: A Bioinformatics-Based Tuberculosis Vaccine Model

Authors: L Zhuang, Y Zhao, SL Ali, et al.
Journal: Decoding Infection and Transmission, 2, 100026, 2024 | Cited by: 6
Summary: Introduces the ZL9810L vaccine through immunoinformatics pipelines. Covers antigenicity prediction, MHC binding, and molecular docking validation.

Conclusion

Syed Luqman Ali exemplifies the spirit of the Excellence in Research Award through his impactful research, global collaborations, and integration of next-generation technologies in biomedical science. His publications, reviewer roles, and scientific rigor highlight a career devoted to innovation and advancement in health research. He is not only highly deserving but also an emerging leader in the fields of computational biology and immunoinformatics.