Kristina Ulicna , PhD

Kristina holds a BSc in Biomedical Sciences from King’s College London and is currently working on her PhD at University College London with Alan Lowe and Guillaume Charras. Her PhD research utilizes deep learning to track single cell heterogeneity within non-cancer and cancer cell lines. Kristina’s work in this area was recently accepted to Frontiers in Computer Science: https://www.frontiersin.org/articles/10.3389/fcomp.2021.734559/abstract

She also recently completed an internship at Microsoft Research Cambridge as an AI research scientist and Forbes Slovensko shortlisted her as a 2021’s under-30 laureate.

More about her work: https://github.com/KristinaUlicna

Separation of cells based on their tracking status: A colourised binary mask of a time-lapse microscopy field of view of medium confluency with individual cells highlighted as survivors if they can be tracked since the initial movie frame (cyan), incomers if they migrated into the field of view throughout the movie (yellow) or mistracks if an error occurred in the automated trajectory reconstruction (red).

Tracking Single Cells Using Deep Learning

AI-based solutions continue to gain ground in the field of microscopy. From automated object classification to virtual staining, machine and deep learning technologies are powering scientific…