doc. dr. Seyed Ahmad Hosseini

Office:
58 Dvorec Lanthieri Vipava
Phone:
05 6205 830
Consultations:
By appointment
Course principal:
  • Statistics, 2. year
    Bachelor's degree programme Engineering and Management (first cycle)
Lecturer:
  • Project 1, 1. year
    Master's degree programme Engineering and Management (second cycle)
  • Statistics, 2. year
    Bachelor's degree programme Engineering and Management (first cycle)
Assistant:

Asst. Prof. Dr. Hosseini

Theoretical and Applied Operational Research (OR)
Industrial Engineering || Mathematical Optimization || Data Analytics

  • Dr. Hosseini is primarily interested in interdisciplinary research at the intersection of Operational Research (OR), Industrial Engineering, Mathematical Optimization, Computer Science, and Data Analytics, with a focus on theoretical foundations, design methodologies, and practical implementation. With a foundation in Engineering and Mathematics, coupled with extensive international work experiences, he has actively participated in numerous interdisciplinary projects and collaborated with various international top-tier scientists in a wide array of application domains. His contributions have been impactful in areas such as Transportation, Supply Chains, System Engineering, Forestry Planning and Engineering, Logistics, Electrical Engineering, Viticulture and Enology, Linguistics, and Biology.

  • Specifically, his expertise encompasses modeling and application of Combinatorial and Industrial Optimization Problems, as well as professional Data Analysis, spanning a diverse array of fields. His research predominantly relies on effectively leveraging mathematical programming techniques and network optimization algorithms, and a fusion of heuristics/metaheuristics with exact/approximation/stochastic optimization methodologies to formulate complex problems across diverse domains and tackle intricate challenges, ultimately bridging theoretical concepts with practical applications. Furthermore, with a keen focus on Data Science and 10+ experience in Data Analysis, he also excels in extracting meaningful insights from data across various scientific fields and industries. His proficiency in utilizing Statistical Methods, Machine Learning Algorithms, and Data Analytics tools and his experience in combining theory and practice of statistics contributes to a comprehensive understanding of phenomena, supporting evidence-based decision-making in both scientific research and industrial applications. In addition to his academic pursuits, he has assumed diverse roles within the business world, serving as operations manager, logistics manager, data analyst, and supply chain consultant at various companies, providing opportunities for him to actively interact with the industry.