Veronika Thost

Veronika is working in the MIT-IBM Watson AI Lab. Her research focuses on learning over structured data, particularly, on graphs in chemistry and material science and in the context of foundation models. Current topics of interest include:

• Self-supervised learning
• Learning over small data
• Uncertainty calibration
• Integration of domain knowledge

Previously, Veronika worked as a postdoctoral researcher at TU Dresden, Germany, where she also received her Ph.D. in Computer Science in 2017. At that time, she worked on query answering over knowledge graphs, existential rules, and in description logics, mainly in terms of complexity theory. She also spent 1.5 years at IBM Research Zurich, working on AI for chemistry.