Marianna Rapsomaniki

Marianna is leading the AI for single-cell research team at IBM Research Europe in Zurich. The overarching goal of her team is modeling spatiotemporal tumor heterogeneity across different scales of biological organization, and understanding how it affects cancer initiation, progression, and response to treatment. To achieve that, her team combines machine learning and deep learning approaches to develop computational methods able to extract biologically meaningful patterns from large-scale, heterogeneous, and noisy single-cell data, with or without spatial resolution. Marianna holds a Diploma in Computer Science and Engineering and a Master's in Bioinformatics, both from the University of Patras, Greece. Her PhD research was carried out working jointly in the Cell Cycle lab of the University of Patras and the Automatic Control Lab of ETH Zurich and involved stochastic hybrid modeling of biological systems, with applications in protein mobility within the nucleus, DNA re-replication, and parameter inference from live-cell imaging data. Her research has been supported by a Swiss Government Excellence Scholarship, the State Scholarships Foundation of Greece, and the Swiss National Science Foundation (SNSF).  

Check our team's Publications, and collection of open-source tools!

News:

• Our team's paper ChromFormer: A transformer-based model for 3D genome structure prediction selected as a spotlight talk at the Learning Meaningful Representations of Life workshop in NeurIPS - watch
• Presentation of our team’s work in Applied Machine Learning Days (AMLD) - watch
• Our team was awarded an SNSF Sinergia grant PROMETEX (collab with the Kruithof-de Julio Urogenus lab, University of Bern, and the Alexandrov Spatial Metabolomics lab, EMBL).
• Read about our latest work on deciphering breast cancer heterogeneity here, or watch the related video from ReutersTV.