My doctoral research is on the validation of computer simulations.
This requires the precise definition and modelling of validation experiments and experiments in general.
Through my research I advance the belief that validity is not a single value, but an everlasting process moderated by varying experimental conditions.
These experimental conditions are encoded in reusable ‘frames’ that are used to ascertain the conditional validity of a model,
using deep reasoning (a combination of logical reasoning and procedural programming).
I am building a proof-of-concept model management tool, that is able to handle all kinds of data related to experiments
and help system engineers design new replicable experiments and simulations using explicitly encoded knowledge.
In my master thesis I studied the modelling and verification of software deployed on embedded platforms.
I worked on a US Army-funded project, where I developed a tool to incrementally transform a model specified
in the Architecture Analysis Design Language (standardized by the SAE and at the core of the US-DoD’s modernization program),
into a more declarative form of the same language, without loss of information.
This enabled tool developers to rapidly modify instance models without worrying about complications in the declarative format.
In my bachelor thesis I studied hardware-software co-simulation, reconfigurable hardware platforms, and biomedical signal processing.
I designed and implemented novel circuits and architectures in FPGAs for power and time optimized detrending and feature extraction of
massively parallelized biomedical data sources like high-density EEGs. This work also resulted in many journal publications.
During my bachelor’s (not as part of my thesis), I studied the use and extension of the Petri net language to model C-code.
These Petri nets were used to compare the similarity of different C programs and formally prove a large range of equivalences.
I explored benefits compared to traditional finite-state-automata, in the ability of Petri nets to succinctly model parallelization.
I also worked on the feature modelling of cyber-physical systems as a late addition at the end of an EU COST Action.
As I reflect on my academic journey, I see a transition from working on tangible, real-world systems
such as hardware-software co-simulations and embedded platforms,
toward increasingly abstract domains centered around logic and reasoning.
This progression mirrors my evolving interest in the underlying essence of computing:
the ability to formalize and reason about complex systems and processes.
However, even as my work moves toward deeper abstraction, it remains firmly connected to the industrial and societal needs of today,
where reliable model validation, reasoning frameworks, and data-driven decision-making are critical.
In this synthesis lies my aspiration: to contribute to the foundational aspects of computing
while ensuring that they remain relevant and applicable to real-world challenges.
Public institutions that have funded my supervisors’ projects that I was a part of:
Corporate organizations of researchers with whom I collaborate:
