Lecturers

Daniel S. Hain

Associate Professor in Innovation Studies and Data Science at Aalborg University. E-mail: dsh@business.aau.dk

Daniel is an Associate Professor in Data Science & Innovation Economics at the Aalborg University Business School, where he leads the Data Science research track at the AI:Growth lab, and coordinates teaching at the Social Data Science (SDS) master specialization. His research is dedicated to the development and application of data-driven methods to map, understand, and predict technological change, and its causes and consequences for socioeconomic systems on various levels of aggregation. His current contextual focus is the dynamics of AI research and industry.

His research is featured in leading academic journals such as Research Policy, but also attracted attention and funding from the industry, and lead to price-winning applications. Daniel is actively engaged in initiatives to educate (social science) students and researchers, professionals, and policymakers in understanding, evaluating, and applying modern Data Science and Artificial Intelligence methods for data-driven decision making.

As part of the AI:DK project, he coordinates and leads AI proof-of-concept projects within industry. His team also develops enterprise and policy software solutions for IP search and technology mapping.

Roman Jurowetzki

Associate Professor in Innovation Studies and Data Science at Aalborg University. E-mail: roman@business.aau.dk

I come from a crossdisciplinary social science background. After my master in innovation economics I was rather frustrated by the underutilization of unstructured data in the field of my PhD project. This was until I discovered Natural Language Processing in 2013. I have been utilizing text and other unstructured data ever since in my research. Recently that has beeen research related to mapping and understanding of complex technological ecosystems. Since 2018 together with Daniel Hain, I am coordinating the Social Data Science specialization at AAU, where we train business and social science students in the application of computational methods.