Valentina Sora

Valentina Sora is a Postdoc in the Machine Learning section at the Department of Computer Science, University of Copenhagen, focusing on interdisciplinary research at the intersection of machine learning and structural biology.

Research Interests

• Developing machine learning algorithms for quantum-classical simulations in computational chemistry.
• Modeling biological data with applications in autophagy, cancer genomics, and protein structure networks.
• Designing computational tools for protein interaction network analysis and high-throughput mutational scans.

Key Trends in Publications

• Her work bridges machine learning and quantum computing with structural biology, emphasizing protein dynamics, mutation effects, and biomolecular simulations.
• Recent studies apply deep learning to gene expression and genomic variant interpretation, alongside quantum embedding for molecular assemblies.

Collaborations span computational biology, quantum chemistry, and cancer research with institutions like the SCIENCE AI Centre at the University of Copenhagen and researchers such as Yevgeny Seldin and Andrea Krogh.