Marco Monti


Research Scientist


Dr Marco Monti is a senior managing consultant and a research scientist at IBM Cognitive and Advanced Analytics Group and IBM Research Center for Computational Behaviour. He has been also an adjunct researcher at the Max Planck Institute for Human Development of Berlin within the Adaptive Behaviour and Cognition group led by Prof. Gerd Gigerenzer and a research fellow at the University of Aberdeen, Knowledge Technology Group – Department of Computing Science, led by Prof. Jeff Pan. Marco’s research and consulting activities focus on the role of Knowledge Graphs and AI to support decision-making processes in the in Fin-tech and Healthcare industries. He also collaborates with interdisciplinary groups of researchers investigating the concept of ecological rationality within the novice-expert relationship, such as the customer-financial advisor or patient-doctor interactions. Dr. Monti’s academic research and teaching interests lie in the area of knowledge representation, pattern recognition, decision theory and cognitive sciences, as well as in behavioural economics and human-computer interaction. Marco holds a bachelor’s degree and both a master’s and Ph.D in Economics from the Bocconi University of Milan, Italy. He is an adjunct professor at Catholic University of Milan.

Talks and Events

2022 Workshop: KGC Healthcare and Life Sciences Symposium

We seek original contributions describing theoretical and practical methods and techniques for building and maintaining health knowledge graphs for the healthcare and life sciences domain. The symposium will cover topics around data integration, data profiling, data curation, querying, knowledge discovery, ontology mapping, matching, reconciliation, machine learning approaches, and applications. We will have several invited speakers who are thought leaders in the healthcare and life sciences space. Furthermore, we plan to have a panel discussion comprising experts from industry, government, and academia. In summary, the primary objectives of this symposium will be to provide a platform to discuss:

  • Characterisation of healthcare and life sciences knowledge graphs
  • Opportunities for the application of knowledge graphs in healthcare and life sciences
  • Challenges of creating and maintaining such knowledge graphs
  • Opportunities for knowledge graph research in this space