Using her mathematics background and multidisciplinary research experiences, she develops and applies novel machine learning algorithms that uncover the underlying dynamics of complex systems in particular those in computational biology and epidemiology.

Her main research interest is designing theoretical and computational approaches to learn good feature representations for the joint analysis of heterogenous sources of data to explore mechanisms of cancer biology. Dr. Ak is currently integrating novel, scalable, and interpretable machine learning solutions into understanding single cell analysis, at CEDAR.

During her PhD studies, she developed interpretable spatiotemporal prediction algorithms. Besides cancer, she also works on modeling spatiotemporal dynamics of COVID-19 with location-specific demographic and socioeconomic characteristics.

Cigdem Ak has a Ph.D. in Computational Sciences and Engineering from Koc University, and an M.Sc. in Mathematics from École Normale Supérieure de Lyon.