PhD
Adrian
Hermes
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
May 24, 2026;
Data for score A3 calculation refer to period
2020-2024
(2023)
| Database |
Linked records |
Citations |
Pure citations |
Average pure citations |
| WoS |
21
|
205
|
164
|
7.81
|
| Scopus |
22
|
193
|
146
|
6.64
|
Doctoral dissertations and other final papers
Show
ARIS research and infrastructure programmes
Legend
Doc. Dr. Adrian HERMES
(also known as A. Hosseini)
Operations Research · Data Analysis · Machine Learning
Applied Mathematics · Industrial Engineering · Uncertainty
Dr. Hermes is an interdisciplinary researcher and professor working at the intersection of Industrial Engineering, Applied Mathematics, Operations Research, Optimisation, Computer Science, and Data Analytics.
His research focuses on formulating and solving complex combinatorial and industrial optimisation problems using mathematical programming, network optimisation, and hybrid strategies that integrate heuristics and metaheuristics with exact, approximation, and stochastic methods. He collaborates internationally with research teams across transportation systems, supply chains and logistics, forestry planning, systems engineering, viticulture and oenology, and biological applications — turning rigorous theoretical models into real‑world impact.
Alongside optimisation, he brings over a decade of experience in data analysis and data science, including statistical modelling, machine learning, and advanced analytics. He extracts actionable, interpretable insights from complex datasets and combines statistical theory with modern computational workflows to support model validation, system understanding, and strategic decision‑making.
By bridging optimisation and data science, he delivers robust, evidence‑based solutions that solve real problems.