About
I am Professor of History and Philosophy of Mathematics and Computer Science at the University of Copenhagen, specializing in the intersection of mathematical practice, artificial intelligence, and digital humanities methods.
My work explores how computational approaches and machine learning can illuminate philosophical questions about mathematics, computation, and scientific practice. I direct the DH4PMP research group, pioneering the use of big data and AI to study mathematical research at scale.
Research Focus
My research sits at the crossroads of philosophy, computer science, and data science. I investigate how algorithms shape mathematical practice, how machine learning can inform philosophical inquiry, and what computational methods reveal about the nature of formal sciences.
Key areas:
- Philosophy of mathematical practice and computerization
- Digital humanities methods for studying scientific practice
- Machine learning and AI in philosophical research
- History and philosophy of algorithms and computation
- Ethical and social dimensions of AI and computational systems
Digital Humanities for Philosophy (DH4PMP)
I lead a research group that develops and applies machine learning, natural language processing, and big data methods to answer philosophical questions about how mathematics is actually practiced, communicated, and evolves.
Our work includes automated analysis of mathematical publications, network analysis of conceptual development, diagram detection using computer vision, and large-scale textual analysis of mathematical discourse.
Capabilities:
- Text mining and NLP for mathematical and scientific texts
- Network analysis of research communities and concepts
- Machine learning for pattern detection in research practice
- Computer vision for diagram and notation analysis
- Topic modeling and sentiment analysis at scale
Consultation & Collaboration
I work with researchers, institutions, and organizations at the intersection of AI, computational methods, and humanistic inquiry.
Areas of expertise:
- Designing computational research methodologies
- Applying AI/ML to humanities and social science questions
- Philosophy of AI, algorithms, and computational systems
- Research ethics in AI and data science
- Teaching and curriculum development in computational thinking
Collaboration opportunities:
- Grant applications and research design
- Methodological consultation for digital humanities projects
- Advisory roles on AI ethics and philosophy
- PhD supervision in computational approaches to philosophy
- Workshops and training in digital methods
Publications & Impact
I have published extensively on philosophy of mathematical practice, computational methods in philosophy, and the history of algorithms. My work on digital approaches to studying science has appeared in leading journals and has been recognized with the Montucla Prize from the International Commission on the History of Mathematics.
Selected topics:
- Formalization and computerization in mathematics
- Computational approaches to studying scientific practice
- Historical development of algorithmic thinking
- Philosophy of machine learning and AI systems
- Collaboration and communication in formal sciences
Teaching & Supervision
I teach courses on philosophy of computer science, machine learning, and history of computation at both graduate and undergraduate levels. I supervise projects that bridge computational methods and philosophical inquiry.
Current courses:
- Philosophy of Computer Science and Machine Learning
- Philosophy of Computer Science & Economics
- History of Computer Science
I welcome inquiries from students interested in computational philosophy, digital humanities, philosophy of AI, or history and philosophy of mathematics.
