My research is driven by the goal of understanding and improving human work in an increasingly digital and AI-supported world. I study and design collaborative work practices and socio-technical systems for knowledge-intensive work, with a particular focus on modern information systems such as conversational and embedded AI.

From a design-oriented, human-centered information systems perspective, my work seeks to understand the complex interplay of social, cognitive, and technological factors that shape how individuals and groups collaborate toward shared goals. Building on this understanding, I develop and evaluate socio-technical solutions that support, augment, and responsibly orchestrate collaborative work practices. Ultimately, my research aims to contribute to more effective, meaningful, and sustainable forms of human–machine collaboration.
 

Eva Bittner is a Full Professor of Information Systems and Head of the Research Group Human-Centered Information Systems Engineering at the University of Zurich. She joined UZH in February 2026.

Prior to joining UZH, she was an Assistant Professor (until 2021) and subsequently a Full Professor (2021–2026) of Information Systems and Socio-Technical Design at the Department of Informatics, University of Hamburg, Germany. Wirtschaftsinformatik, Sozio-Technische Systemgestaltung (WISTS) : Fachbereich Informatik : Universität Hamburg

She received her Ph.D. in Information Systems from the University of Kassel in 2015.

Eva Bittner is a member of Germany’s Platform Learning Systems expert group on the future of work and human–machine interaction. Her research has been published in leading journals and conferences, including the Journal of Management Information Systems (JMIS), Business & Information Systems Engineering (BISE), Information & Management (I&M), and the Journal of Information Systems Education (JISE).

Her research interests span Collaboration Engineering, Human–Machine Collaboration and Hybrid Intelligence, Knowledge Work and Knowledge Management, IT Innovation Management, and Co-Creation and Social Innovation. In particular, her work focuses on the socio-technical design of collaboration processes, practices, and tools for knowledge-intensive work using modern information and communication technologies, including generative AI. She studies how AI-based systems can augment human creativity and problem-solving in complex real-world contexts, while also examining social, cognitive, and ethical implications as well as unintended side effects of human–AI collaboration. Application domains range from human–AI dyads and small teams to crowd-based collaboration in organizations and public-sector contexts, such as customer service, innovation, software development, education, citizen participation, and smart cities.