Research Focus
My research focuses on understanding the molecular mechanisms that drive the progression of metabolic dysfunction-associated steatotic liver disease (MASLD/MASH). I develop computational approaches to reconstruct disease trajectories from large-scale transcriptomic and multi-omics datasets, with the aim of identifying the biological processes underlying disease progression and discovering biomarkers for diagnosis, patient stratification, and therapeutic intervention.
More broadly, I am interested in applying bioinformatics, machine learning, and integrative multi-omics approaches to study metabolic diseases. My work combines bulk and single-cell transcriptomics, spatial transcriptomics, network analysis, and systems biology to translate complex biological data into mechanistic insights. I also investigate adipose tissue biology and evaluate preclinical rodent models to improve their translational relevance to human disease.
Background and experience
I hold an M.Eng. in Computer Engineering and Informatics from the University of Patras, Greece, followed by an M.Sc. in Bioinformatics from the University's Medical School. During my master's studies, I joined EMBL Heidelberg, where I contributed to research investigating the therapeutic potential of RNA-binding proteins across four cancer types.
I completed my PhD at the Institute of Metabolic Science, University of Cambridge (TVP Lab), in collaboration with EMBL-EBI (Petsalaki Group). My doctoral research focused on deciphering the molecular mechanisms underlying MASLD progression and identifying the rodent models that most faithfully recapitulate human disease. Throughout my research career, I have developed expertise in transcriptomics, machine learning, statistical modelling, and integrative analysis of large-scale biological datasets.
Working at the IMS-MRL
I am currently a postdoctoral researcher at the University of Cambridge within the Institute of Metabolic Science. My research continues to focus on metabolic diseases, particularly MASLD and adipose tissue biology, through the development of computational methods that integrate high-dimensional omics data with clinical and experimental datasets.
My current work centres on modelling disease progression as a continuous molecular trajectory, identifying biomarkers that reflect disease stage and progression, and developing computational frameworks that improve our understanding of metabolic dysfunction and support translational research.
