doc. dr. Adrian Hermes
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Decision support models and systems, 1. year
Master's degree programme Engineering and Management (second cycle) -
Decision support models and systems, 2. year
Master's degree programme Engineering and Management (second cycle) -
Experimental design and analysis, 1. year
Master’s study programme Viticulture and Enology -
Statistics, 2. year
Bachelor's degree programme Engineering and Management (first cycle)
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Decision support models and systems, 1. year
Master's degree programme Engineering and Management (second cycle) -
Decision support models and systems, 2. year
Master's degree programme Engineering and Management (second cycle) -
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)
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Individual Project, 2. year
Master's degree programme Leadership in Open Education (second cycle) -
Decision support models and systems, 1. year
Master's degree programme Engineering and Management (second cycle) -
Decision support models and systems, 2. year
Master's degree programme Engineering and Management (second cycle) -
Digital resource & document management, 1. year
Bachelor's degree programme Engineering and Management (first cycle) -
Introduction to Computer and Information Science, 1. year
Bachelor's programme in Viticulture and Enology (first cycle) -
Business information systems, 2. year
Bachelor's degree programme Engineering and Management (first cycle) -
Individual research project 2, 2. year
Master's degree programme Engineering and Management (second cycle)
Adrian Hermes, PhD
Industrial Engineering · Mathematical Optimization · Applied Statistics
Operations Research (OR) · Machine Learning · Data Analytics
Dr. Adrian Hermes is an interdisciplinary researcher working at the intersection of Operations Research (OR), Industrial Engineering, Mathematical Optimization, Computer Science, and Data Analytics. His work integrates theoretical modelling, algorithmic development, statistical analysis, and practical implementation, with a particular emphasis on bridging methodological research and real-world applications.
With an academic background in Engineering and Mathematics and extensive international research experience, he has collaborated with researchers and institutions across multiple scientific and industrial domains. His research contributions and collaborations have included applications in transportation systems, logistics, forestry planning, systems engineering, viticulture, enology, sustainability, automotive component manufacturing, and data-driven decision support.
His primary research interests focus on combinatorial optimization, network optimization, mathematical programming, and industrial optimization problems. He is particularly interested in the modelling and solution of complex decision-making problems using exact methods, approximation algorithms, stochastic optimization, heuristics, and metaheuristics. His work frequently combines optimization theory with computational implementation and applied analytics to support efficient and robust decision-making in industrial and scientific environments.
In addition to optimization and industrial engineering, Dr. Hermes has 9+ years of professional experience in data analysis, business analytics, and applied statistics. His research and applied work involve statistical modelling, multivariate analysis, machine learning, and data mining across interdisciplinary datasets. He is especially interested in combining statistical reasoning with machine learning methodologies to extract meaningful insights from complex data and support evidence-based research and operational decisions.
Dr. Hermes welcomes industrial collaboration, project management, and graduate thesis supervision in areas related to:
- Sustainability Analytics and Data-Driven Modelling
- Decision Analysis and Decision Support Systems
- Operations Research and Industrial Engineering
- Mathematical and Combinatorial Optimization
- Network Optimization and Graph Algorithms
- Machine Learning for Industrial Applications
- Data Analytics for Industrial Applications
- Logistics and Transportation Systems
- Applied Statistics and Biostatistics
- Inventory and Stock Management
- Business and Industrial Analytics
- Optimization under Uncertainty
Research Keywords
Operations Research (OR) · Industrial Engineering · Combinatorial Optimization · Mathematical Programming · Applied Statistics · Machine Learning · Data Analysis · Decision Analysis · Decision Support Systems · Logistics · Transportation · Inventory Management · Network Flows · Graph Algorithms · Heuristics · Metaheuristics · Biostatistics · Uncertainty Modelling · Sustainability Analytics
Technical and Analytical Tools
GAMS · MATLAB · OPL · AIMMS · R · Python · SPSS · Minitab · XLSTAT · Weka · Jamovi · JASP · GNU PSPP · Tableau · JMP Pro · Power BI · OriginPro · SIMCA · GraphPad Prism · PanelCheck · MetaboAnalyst · Gephi · DEXi · Web-HIPRE · LiPS IDE · SQL · HTML
🟢 ORCID Research Profile
🔗 Sessionize Speaker Profile
🎓 COBISS/CRIS Research Profile
📘 Editorial Board Member — Mathematics (MDPI)