Research

Main research theme. Since my Masters’ Degree Thesis in 2016 and through my PhD (2016-2020), post-doc (2020-2022), and assistant professor roles (2022-2026), my research has focussed on the software engineering of collective systems, especially by the computational, programming language, and distributed middleware perspectives.

Contributions. Contributions include developments of the aggregate computing paradigm (cf. concrete languages like ScaFi, and middleware models for the edge-cloud continuum like pulverisation), conceptualisation of macro-programming, investigations about artificial collective intelligence, identification and definition of self-organisation design patterns, and conceptualisation of application scenarios like crowd digital twins.

Research Themes at a Glance

• Self-* software systems: architectures and models for self-adaptation and self-organisation.
• (Unconventional) Programming Languages: programming language-based approaches for emergent, collective intelligent, and self-organising systems (cf. Macro-programming).
• (Artificial & Hybrid) Collective Intelligence: theories, models, and techniques for understanding and engineering CI in (hybrid) multi-agent systems.
• IoT, Smart Cities & Edge Computing: programming models to express computations and coordinate resources across the IoT-edge-fog-cloud continuum and in large-scale scenarios (e.g., smart cities).

Publications

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