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doc. dr. Seyed Ahmad Hosseini

Office:
58 Dvorec Lanthieri Vipava
Phone:
05 6205 830
Consultations:
By appointment
Course principal:
Lecturer:
  • Experimental design and analysis, 1. year
    Master’s study programme Viticulture and Enology
  • 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:

Doc. Dr. A. Hosseini

Industrial Engineering || Mathematical Optimization || Biostatistics
Operations Research (OR) || Data Analysis || Machine Learning

  • 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, Forestry Planning, Supply Chains, Logistics, System Engineering, Viticulture, Enology, and Biology.

  • Specifically, his expertise encompasses modeling and application of Combinatorial and Industrial Optimization Problems. 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 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 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.

  • Keywords: Operations Research (OR) · Industrial Engineering · Mathematical Programming · Logistics · Transportation · Inventory Management · Combinatorial Optimization · Network Flows and Algorithms · Heuristics · Biostatistics · Applied Statistics · Machine Learning · Data Mining · Data Analysis · Uncertainty · Decision Analysis · Decision Support Systems · HTML · Weka · Minitab · Matlab · IBM SPSS Statistics · XLSTAT · Linear Program Solver (LiPS IDE) · R (Programming Language) · Power BI · SIMCA · GraphPad Prism · Gephi · Tableau · JMP Pro · Origin Pro · PanelCheck · MetaboAnalyst · GAMS · OPL · AIMMS · SQL · DEXi · Web-HIPRE