What is he best known for?
The fields of study he is best known for:
- Programming language
- Algorithm
- Artificial intelligence
The scientist’s investigation covers issues in Markov chain, Theoretical computer science, Model checking, Algorithm and Probabilistic logic.
His study in Markov chain is interdisciplinary in nature, drawing from both Process calculus, Markov decision process, Temporal logic and Artificial intelligence.
His Theoretical computer science research integrates issues from Computational complexity theory, Formal specification, Dependability and Stochastic Petri net.
He interconnects Markov reward model, Protocol, Binary decision diagram, System of linear equations and Formal verification in the investigation of issues within Model checking.
His Algorithm study combines topics in areas such as Continuous-time Markov chain, Static analysis and Hybrid system.
His Probabilistic logic study combines topics from a wide range of disciplines, such as Programming language, Bisimulation, Satisfiability, Reachability and Nondeterministic algorithm.
His most cited work include:
- Model-checking algorithms for continuous-time Markov chains (684 citations)
- Interactive Markov chains: and the quest for quantified quality (325 citations)
- Interactive Markov Chains (251 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Markov chain, Theoretical computer science, Model checking, Probabilistic logic and Algorithm.
The Markov chain study combines topics in areas such as Reachability and Temporal logic.
His study in the fields of Automaton, Process calculus and Nondeterministic algorithm under the domain of Theoretical computer science overlaps with other disciplines such as Context.
His Model checking research incorporates elements of Formal verification, Formal methods, Dependability and Artificial intelligence.
Holger Hermanns has researched Probabilistic logic in several fields, including Bisimulation, Markov decision process and State space.
His biological study focuses on Computation.
He most often published in these fields:
- Markov chain (38.44%)
- Theoretical computer science (35.26%)
- Model checking (32.37%)
What were the highlights of his more recent work (between 2015-2021)?
- Model checking (32.37%)
- Markov decision process (17.63%)
- Theoretical computer science (35.26%)
In recent papers he was focusing on the following fields of study:
Holger Hermanns spends much of his time researching Model checking, Markov decision process, Theoretical computer science, Probabilistic logic and Automaton.
Model checking is a primary field of his research addressed under Algorithm.
His Markov decision process research is multidisciplinary, incorporating elements of Bisimulation, Interleaving, Mathematical optimization and Interval.
His Theoretical computer science research integrates issues from Probabilistic CTL and Markov chain.
Specifically, his work in Markov chain is concerned with the study of Markov model.
Many of his research projects under Probabilistic logic are closely connected to Context with Context, tying the diverse disciplines of science together.
Between 2015 and 2021, his most popular works were:
- The Value of Attack-Defence Diagrams (23 citations)
- Battery-Aware Scheduling in Low Orbit: The GomX–3 Case (20 citations)
- PTRebeca: Modeling and analysis of distributed and asynchronous systems (19 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Algorithm
- Artificial intelligence
His main research concerns Model checking, Markov decision process, Reachability, Theoretical computer science and Automaton.
In his papers, Holger Hermanns integrates diverse fields, such as Model checking and Formalism.
His Markov decision process research is multidisciplinary, incorporating perspectives in Probabilistic logic, Mathematical optimization, Markov chain and Pareto optimal.
The concepts of his Markov chain study are interwoven with issues in DUAL and Abstraction refinement.
His research in the fields of Nondeterministic algorithm overlaps with other disciplines such as Manifold.
His study in Automaton is interdisciplinary in nature, drawing from both Scheduling, Formal methods, Attack tree and Distributed computing.
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