PhD
Seyed Ahmad
Hosseini
no.:
57501
researcher – active in research organisation
Code |
Science |
Field |
Subfield |
1.07.02
|
Natural sciences and mathematics
|
Computer intensive methods and applications
|
Optimisations
|
1.01.06
|
Natural sciences and mathematics
|
Mathematics
|
Probability and statistics
|
Code |
Science |
Field |
P001
|
Natural sciences and mathematics
|
Mathematics
|
T003
|
Technological sciences
|
Transport technology
|
P160
|
Natural sciences and mathematics
|
Statistics, operations research, programming, actuarial mathematics
|
B430
|
Biomedical sciences
|
Sylviculture, forestry, forestry technology
|
P170
|
Natural sciences and mathematics
|
Computer science, numerical analysis, systems, control
|
B110
|
Biomedical sciences
|
Bioinformatics, medical informatics, biomathematics biometrics
|
Operations Research (OR) . Combinatorial Optimization . Mathematical Modelling . Forestry Engineering . Data-Driven Optimization . Machine Learning . Data Analysis . Applied Statistics . Biostatistics . Network Flows . Algorithms . Heuristics . Logistics . Transport Networks . Uncertainty
Data for the last 5 years (citations for the last 10 years) on
October 15, 2025;
Data for score A3 calculation refer to period
2020-2024
Data for ARIS tenders (
23.05.2022 – Target research programmes,
archive
)
Database |
Linked records |
Citations |
Pure citations |
Average pure citations |
WoS |
19
|
120
|
86
|
4.53
|
Scopus |
21
|
160
|
126
|
6
|
Doctoral dissertations and other final papers
Show
ARIS research and infrastructure programmes
Legend
Doc. Dr. A. HOSSEINI
Operations Research · Data Analysis · Machine Learning
Applied Mathematics · Industrial Engineering · Uncertainty
Dr. Hosseini is primarily interested in interdisciplinary research at the intersection of Industrial Engineering, Operational Research (OR), Computer Science, and Mathematical Optimization, focusing on theory, design, and implementation. Specifically, he is strongly inclined towards the modeling and applications of Combinatorial and Industrial Optimization Problems. His expertise lies in formulating complex problems across diverse domains, enabling effective problem-solving through mathematical programming techniques. In the realm of research, he predominantly focuses on leveraging optimization techniques and network optimization algorithms, and a fusion of heuristics/metaheuristics with exact/approximation/stochastic optimization methodologies to tackle intricate challenges and provide effective solutions that bridge theoretical concepts with practical applications.
With a foundation in Engineering, Optimization, and Mathematics, coupled with extensive international work experiences, he has actively participated in numerous research projects and collaborated with various international top-tier scientists in a wide array of application domains. His contributions have been impactful in critical areas such as Transportation, Supply Chains, System Engineering, Forestry Planning and Engineering, Logistics, Electrical Engineering, Viticulture and enology, Linguistics, and Biology. As reported by Scopus, over 70% of these contributions have been published in the top 25% journals by SJR, consistently ranking within the top Q1 category.
Furthermore, with a keen focus on data science and 10+ years of experience in data analysis, he excels in extracting meaningful insights from data across various scientific fields and industries. His proficiency in utilizing advanced Statistical Methods and Data Analytics tools contributes to a comprehensive understanding of phenomena, supporting evidence-based decision-making in both scientific research and industrial applications. Apart from academia, he has also taken different roles in the business world and acted as an operations manager, logistics manager, data analyst, and supply chain consultant at different companies.
We were not given permission by the researcher to publish data.