Martin Bicher

Martin Bicher is a PostDoc Researcher at TU Wien, affiliated with the Department of Data Science under the Faculty of Informatics. He specializes in agent-based simulation, epidemiological modeling, and decision support systems for public health crises. His work focuses on optimizing resource allocation, vaccination strategies, and policy evaluation during pandemics.

He teaches courses such as Modeling and Simulation (194.076), Modelling and Simulation in Health Technology Assessment (194.094), and Advanced Modeling and Simulation (194.056). His research is supported by projects like DynOptTestControl (2022–2026) and KLIPHA-COVID19 (2020–2021).

Key research interests include agent-based modeling frameworks, integration of machine learning into simulation systems, and multi-criteria decision support for public health interventions. His publications analyze pandemic response strategies, vaccination prioritization, and the impact of environmental factors on disease spread.

Recent work includes developing mathematical models for equitable disease testing, simulating vaccination strategies under supply uncertainties, and evaluating contact-tracing policies. He collaborates with interdisciplinary teams to address challenges in healthcare resource optimization and policy design.

Advising two students, Bicher has mentored theses on railway simulation and delay modeling. His contributions to pandemic decision support have been featured in high-impact journals like Omega and PLoS ONE.