Daniel Zünd
Lecturer
Department of Applied Future Technologies, Institute for Data Analysis, Artificial Intelligence, Visualization, and Simulation (DAViS)
Daniel is a data scientist and systems analyst with many years of experience in research, development and application of data-driven methods for analysing complex systems. After completing his studies in computer science and obtaining his doctorate at ETH Zurich, he worked in international research environments, including Zurich, Chicago, Singapore and South Africa.
His methodological profile includes the development of dynamic models, statistical methods, algorithmic approaches and data analysis tools. He combines elements from machine learning, artificial intelligence, network analysis, optimisation and spatial modelling. His work is characterised by an interdisciplinary approach and the transfer of theoretical concepts into practical applications.
Daniel has extensive experience in project management, scientific publication and teaching at bachelor's, master's and doctoral level. His work focuses on the question of how data-based and systemic approaches can contribute to sound decision-making and a better understanding of dynamic and social contexts.
Curriculum Vitae
Daniel is a data scientist and systems analyst with many years of experience in research, development and application of data-driven methods for analysing complex systems. After completing his studies in computer science and obtaining his doctorate at ETH Zurich, he worked in international research environments, including Zurich, Chicago, Singapore and South Africa.
His methodological profile includes the development of dynamic models, statistical methods, algorithmic approaches and data analysis tools. He combines elements from machine learning, artificial intelligence, network analysis, optimisation and spatial modelling. His work is characterised by an interdisciplinary approach and the transfer of theoretical concepts into practical applications.
Daniel has extensive experience in project management, scientific publication and teaching at bachelor's, master's and doctoral level. His work focuses on the question of how data-based and systemic approaches can contribute to sound decision-making and a better understanding of dynamic and social contexts.
