Dr. Jörg Osterrieder
Lecturer
Swiss Institute for Information Science (SII), Department of Applied Future Technologies
Jörg Osterrieder has been involved in research and teaching for many years, focusing on topics at the intersection of artificial intelligence, digital finance, fintech, computational and data science, digital innovation and IT. His research interests include the use of data-driven methods and machine learning to understand complex systems, improve decision-making processes and develop innovative solutions in business, technology and society.
His projects include ‘Narrative Digital Finance,’ which examines market and media narratives and their influence on decision-making processes; ‘Anomaly and Fraud Detection in Blockchain Networks,’ which develops methods for detecting fraud and anomalies in digital infrastructures, and ‘Network-Based Credit Risk Models in P2P Lending,’ which explores network-based methods for assessing risks in platform economies.
He holds a PhD in Mathematics (ETH Zurich), an MSc in Mathematics (Syracuse University, USA) and a Master's degree in Business Mathematics (University of Ulm). He began his professional career in investment banking and asset management, where he held quantitative positions at Man Investments, Credit Suisse, Goldman Sachs and Bank of America Merrill Lynch. Most recently, he was Professor of Finance and Artificial Intelligence at the Bern University of Applied Sciences.
Jörg Osterrieder's teaching covers a broad spectrum, ranging from mathematical and quantitative fundamentals, statistics, data science and financial mathematics to application-oriented courses in artificial intelligence, machine learning, natural language processing and digital finance. He combines sound theory with practical applications by integrating case studies, programming projects and current research into his teaching.
One focus is on teaching programming and modelling skills, especially with Python and modern machine learning frameworks, to prepare students for research and practice-relevant issues. He also promotes interdisciplinary teamwork, for example in group projects related to economics, technology and regulation.
In addition to traditional lectures, his teaching activities also include practical projects in cooperation with companies and international organisations, giving students early insights into real-world applications. He also supervises bachelor's, master's and doctoral theses and is involved in the development of new curricula on topics such as AI in financial markets, digital transformation and digitalisation.
As Chair of the COST Action ‘FinTech and AI in Finance’ and Coordinator of the Marie Sklodowska-Curie Industrial Doctoral Network ‘Digital Finance’, he took on international coordination tasks and built up an extensive research network. In addition, he was principal investigator for several Swiss National Science Foundation (SNSF) projects and led Innosuisse projects dealing with the practical implementation of artificial intelligence and digital innovation in Swiss companies. He is also a member of the steering committee of the Luxembourg National Research Fund (NCER Financial Technologies).
His collaborations with international partners from academia, politics and industry aim to translate machine learning methods into practical applications and address technical, organisational and regulatory issues.
In addition, he is lead editor of the journal Management and Marketing and a member of several editorial boards of scientific journals, including Digital Finance (Springer), Frontiers in Artificial Intelligence in Finance and the Journal of Investment Strategies.
Curriculum Vitae
Jörg Osterrieder has been involved in research and teaching for many years, focusing on topics at the intersection of artificial intelligence, digital finance, fintech, computational and data science, digital innovation and IT. His research interests include the use of data-driven methods and machine learning to understand complex systems, improve decision-making processes and develop innovative solutions in business, technology and society.
His projects include ‘Narrative Digital Finance,’ which examines market and media narratives and their influence on decision-making processes; ‘Anomaly and Fraud Detection in Blockchain Networks,’ which develops methods for detecting fraud and anomalies in digital infrastructures, and ‘Network-Based Credit Risk Models in P2P Lending,’ which explores network-based methods for assessing risks in platform economies.
He holds a PhD in Mathematics (ETH Zurich), an MSc in Mathematics (Syracuse University, USA) and a Master's degree in Business Mathematics (University of Ulm). He began his professional career in investment banking and asset management, where he held quantitative positions at Man Investments, Credit Suisse, Goldman Sachs and Bank of America Merrill Lynch. Most recently, he was Professor of Finance and Artificial Intelligence at the Bern University of Applied Sciences.
Jörg Osterrieder's teaching covers a broad spectrum, ranging from mathematical and quantitative fundamentals, statistics, data science and financial mathematics to application-oriented courses in artificial intelligence, machine learning, natural language processing and digital finance. He combines sound theory with practical applications by integrating case studies, programming projects and current research into his teaching.
One focus is on teaching programming and modelling skills, especially with Python and modern machine learning frameworks, to prepare students for research and practice-relevant issues. He also promotes interdisciplinary teamwork, for example in group projects related to economics, technology and regulation.
In addition to traditional lectures, his teaching activities also include practical projects in cooperation with companies and international organisations, giving students early insights into real-world applications. He also supervises bachelor's, master's and doctoral theses and is involved in the development of new curricula on topics such as AI in financial markets, digital transformation and digitalisation.
As Chair of the COST Action ‘FinTech and AI in Finance’ and Coordinator of the Marie Sklodowska-Curie Industrial Doctoral Network ‘Digital Finance’, he took on international coordination tasks and built up an extensive research network. In addition, he was principal investigator for several Swiss National Science Foundation (SNSF) projects and led Innosuisse projects dealing with the practical implementation of artificial intelligence and digital innovation in Swiss companies. He is also a member of the steering committee of the Luxembourg National Research Fund (NCER Financial Technologies).
His collaborations with international partners from academia, politics and industry aim to translate machine learning methods into practical applications and address technical, organisational and regulatory issues.
In addition, he is lead editor of the journal Management and Marketing and a member of several editorial boards of scientific journals, including Digital Finance (Springer), Frontiers in Artificial Intelligence in Finance and the Journal of Investment Strategies.
